Design and Implementation of Wireless Water Meter Reading at Bolo Multipurpose Cooperative

Design and Implementation of Wireless Water Meter
Reading at Bolo Multipurpose Cooperative

Computer Engineering Department

In Partial Fulfilment of the Requirements for the Degree
Bachelor of Science in Computer Engineering

By:
Pesigan, Andrei Christopher Lubrico
Cusi, Jewelles Dannies Panganiban
Dimacuha, Von Chester Cueto
Raca, Aleli Rose Magpantay
Caballero, Christian Villena
Dimaunahan, Yokimura

CpE
2025

RECOMMENDATION

This design project entitled, Design and Implementation of Wireless
Water Meter Reading at Bolo Multipurpose Cooperative , prepared and
submitted by Andrei Christopher L. Pesigan, Jewelles Dannies P. Cusi, Von
Chester C. Dimacuha, Aleli Rose M. Raca, Christian V. Caballero, and
Yokimura Dimaunahan, in partial fulfillment of the requirements for the degree
Bachelor of Science in Computer Engineering, has been examined and found
satisfactory and hereby recommended for Oral Examination.

Engr. Pablo B. Asi
Adviser

ii

APPROVAL SHEET
The design project entitled, “Design and Implementation of Wireless
Water Meter Reading at Bolo Multipurpose Cooperative” was presented before
a panel of examiners of the University of Batangas College of Engineering on July
28, 2025 by Andrei Christopher L. Pesigan, Jewelles Dannies P. Cusi, Von
Chester C. Dimacuha, Aleli Rose M. Raca, Christian V. Caballero, and
Yokimura Dimaunahan are hereby APPROVED by the committee on Oral
Examination.

Engr. Pablo B. Asi
Adviser

Engr. Liza R. Maderazo Dr. Leni A. Bulan
Panel Member Panel Member

DR. HENRY I. CABATAY, REE
Chairman

Accepted as partial fulfillment of the requirements for the degree Bachelor of
Science in Computer Engineering.

DR. HENRY I. CABATAY, REE
Dean, College of Engineering

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ACKNOWLEDGEMENT

We express our deepest gratitude to Almighty God for His unwavering
guidance, strength, and wisdom throughout the journey of completing this thesis.
His blessings have been our foundation and inspiration in overcoming challenges
and achieving our goals.
We extend our heartfelt appreciation to our relatives and friends for their
unconditional love, support, and encouragement. Their presence provided us with
the motivation and strength to persevere through this academic endeavor.
We are profoundly grateful to the Bolo Multipurpose Cooperative (BMPC)
for their cooperation and support in making this research possible. Special thanks
go to the General Manager, Ms. Nelia Magbojos, for her openness to our project
proposal and for granting us access to essential resources. We also extend our
gratitude to Safety Officer Edgar Magbojos and the dedicated water collector
employee, whose insights and assistance were invaluable in understanding the
operational challenges of the cooperative. Our appreciation also goes to the other
employees of BMPC for their collaboration and willingness to participate in the
evaluation of our system.
We owe immense gratitude to our Research Adviser, Engr. Pablo B. Asi,
for his expert guidance, patience, and constructive feedback, which shaped the
direction and quality of this study. His mentorship was instrumental in ensuring the
success of our project.
We also express our sincere thanks to our panelists—Engr. Liza Maderazo,
Dr. Leni A. Bulan, and Dr. Henry I. Cabatay—for their insightful critiques, valuable
suggestions, and encouragement, which greatly enhanced the quality and rigor of
our research. This thesis would not have been possible without the collective
support, inspiration, and contributions of everyone mentioned. Thank you for being
part of this significant milestone in our academic journey.
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ABSTRACT

This study presents the design and implementation of a wireless water
meter reading system for the Bolo Multipurpose Cooperative (BMPC) in Bolo,
Bauan, Batangas, which aimed to address the inefficiencies of manual meter
reading and billing processes. The system integrated an Android-based Point of
Sale (POS) device, developed using Kotlin, to enable semi-automated data
collection, real-time database updates, and accurate billing. Its key objectives
included calculating water consumption, generating precise billing statements, and
ensuring reliable data transmission to a cloud server, with an offline notepad
feature to accommodate connectivity disruptions.
The system was tested from March 15 to April 30, 2025, and demonstrated
high accuracy (0% discrepancy in consumption calculations), reliability, and
functionality, with a latency of under 5 seconds for database updates. Evaluated
by 45 respondents—including BMPC employees and community members—the
system received strong agreement scores for functional suitability (3.85), reliability
(3.88), security (3.94), and maintainability (3.93). The adoption of the Senraise
Android 14 Bluetooth Smart POS Machine enhanced operational efficiency,
minimized human error, and improved customer satisfaction through transparent
and timely billing.
Recommendations for future enhancements included cross -platform
compatibility, advanced analytics, and improved receipt legibility. This solution
modernized BMPC’s water utility management, ensuring scalability and
sustainability for future growth.

Keywords: Wireless water meter reading system, Bolo Multipurpose Cooperative,
Android POS, water utility management
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TABLE OF CONTENTS
PAGE
TITLE PAGE i
RECOMMENDATION ii
APPROVAL SHEET iii
ACKNOWLEDGEMENT iv

ABSTRACT v
LIST OF TABLES ix
LIST OF FIGURES x

CHAPTER
1.0 INTRODUCTION 1
1.1 Objective of the Study 5
1.2 Scope and Delimitation 7
1.3 Significance of the Study 8
1.4 Definition of Terms 10
2.0 METHODOLOGY 12
2.1. Analysis 14
A. Pre-Design 14
B. Hardware Requirements 16
C. Software Requirements 21
2.2. Design 24
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2.3. Development 25
2.4. Implementation 27
Test Selection & Test Performance 27
2.5. Evaluation 28
Review and Selection 28
3.0 RESULTS AND DISCUSSION 32
3.1. Design and Implementation of the System 32
3.1.1 Block Diagram 33
3.1.2 System Flowchart 34
3.1.3 Actual Hardware Set-up 37
3.1.4 System Operation 38
3.2. System Testing and Troubleshooting 42
3.3. Evaluation of the Study 55
3.3.1 Functional Stability 56
3.3.2 Reliability 58
3.3.3 Security 60
3.3.4 Maintainability 62
4.0 CONCLUSION AND DIRECTIONS FOR FUTURE USE 64
REFERENCES 66
APPENDICES
Appendix A: Sample Questionnaire 72
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Appendix B: Certificate of Research Instrument Validation 77
Appendix C: Summary of Questionnaire Response 78
Appendix D: Consent Letter 83
Appendix E: Certificate of Implementation 84
Appendix F: Bill of Materials 85
Appendix G: User’s Manual 86
Researcher’s Contact Information 108

viii

LIST OF TABLES
Table No. Table Name Page
Table 2.0 Likert Scale Scoring 18
Table 2.1 Android POS Device Component Ratings 19
Table 2.2 Android POS Device Percentage Rating 20
Table 3.1 Billing System 44
Table 3.2 Accuracy of Calculating Water Consumption 45
Table 3.3 Sample Receipt 49
Table 3.4 Functionality of Updating the Database 51
Table 3.5 Likert Four-Point Scale Range Interpretation 55
Table 3.6 Evaluation of Functional Stability 56
Table 3.7 Evaluation of Reliability 58
Table 3.8 Evaluation of Security 60
Table 3.9 Evaluation of Maintainability 62
Table 3.10 Summary Results of the System 63

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LIST OF FIGURES
Figure No. Figure Name Page
Figure 1.1 Conceptual Framework 6
Figure 2.1 ADDIE Model 14
Figure 3.1 Block Diagram 33
Figure 3.2 System Flowchart 34
Figure 3.3 Actual Hardware Set-up 37
Figure 3.4 Parts of the Interface Software 38
Figure 3.5 Sample Receipt 41
Figure 3.6 Device to Database Timestamp 42
Figure 3.7 Functionality Test Pie Chart After Implementation 43

x

1
1.0 INTRODUCTION
Water is crucial for economic and social progress, supporting health,
agriculture, environmental management, and employment (Water Supply, 2022).
Water distribution systems link water sources or treatment facilities to consumers
through an infrastructure of pipelines, storage tanks, valves, and pumps. Beyond
delivering water for household needs, these systems also support fire protection,
irrigation, and commercial activities (Drinking Water Distribution System Tools and
Resources | US EPA, 2024). Therefore, the importance of distributing clean water
for all people is the fundamental structure of a civilization. Water meters enhance
the efficiency of water distribution systems, providing real-time data that supports
proactive management, reduces water loss, and promotes sustainable resource
use (Beal & Flynn, 2020; sense.digitalmatter.com, 2024). An instrument known as
a water meter measures the amount of water flowing through a pipe or outlet.
Measurements of water meters are typically using units such as cubic feet or
gallons. Much like a car odometer, a water meter records the cumulative volume
of water that has flowed through it. Utilities often record each reading and subtract
the previous reading from the current one to calculate the water usage since the
last read. Understanding the water usage can help ensure the fairness and
accuracy of the billing and help identify potential issues such as leaks (Water Utility
Management 2021).
The metering infrastructure is the cornerstone of any water billing system.
This encompasses water meters installed at specific properties or usage points to
quantify water consumption (Pms, 2024). "Traditional" meters monitor water flow
and consumption using a mechanical method. The liquid enters a chamber where
the force of the water flow causes mechanisms to revolve. These mechanisms
then transfer the movement to a mechanical clock, which uses numbered rollers
to indicate the amount of water flowing through the counter (Traditional Water
Meters, 2024). In the Philippines, water meter reading faces significant challenges

2
due to the reliance on manual processes, which are prone to inaccuracies and
inefficiencies. A primary issue is the susceptibility of analog water meters to errors
caused by environmental factors, such as dial contamination from dirt or water
exposure, and mechanical wear over time, leading to inaccurate readings
(Purboyo et al., 2024). To guarantee proper billing and efficient operation of water
meters, it is critical to comprehend these difficulties (Admin & Duneslab.AI, 2023).
The Bolo Multipurpose Cooperative (BMPC) in Bolo, Bauan, Batangas,
presently depends on conventional, manual methods for administering water
meter readings and billing. Currently, one employee physically documents meter
readings at each customer's location, then inputs this data into an Excel database
to monitor water consumption and billing records. This method necessitates
substantial time and effort since the worker must individually visit each site,
document the data, and execute fundamental calculations with a calculator to
ascertain monthly billing amounts. Despite the simplicity of these calculations,
which mostly consist of addition and subtraction; this manual method is arduous,
time-consuming, and significantly susceptible to human mistake. The reliance on
manual labor generates numerous inefficiencies. For instance, any human error in
data collection or entry may result in invoicing inconsistencies, potentially leading
to financial differences that affect both the cooperative and its clientele. The
existence of a single employee managing these duties intensifies the issue, as any
delays or mistakes are likely to adversely impact overall operational efficiency.
Also, if the number of clients grows or more records are needed, mistakes and
delays may happen more often, which could hurt customer satisfaction and trust
in BMPC's services.
Measuring water consumption is crucial for monitoring and managing water
use as well as for recording and assigning delivery charges (Quiroz, 2021). A water
meter reader is a necessary instrument for the water business, which oversees
monitoring its customers' water usage and distributing clean water to the public.

3
Traditional water meters, which necessitate manual readings and are susceptible
to human error, digital meters offer automatic readings that are relayed to utility
companies for billing and analytical purposes (SWM Editorial Team, 2024).
Following the manual recording of the figures, the information needs to be typed
into a spreadsheet or other document and returned to the management
organization (10 Things Wrong With Tenant Submetering (and How to Fix Them)
| Enertiv, 2024).
A study by Nyirenda and Mulenga (2020) investigates the development of
an Android-based mobile application designed to optimize water meter reading
collection in Zambia, where manual manpower is still employed but enhanced with
mobile phones for data transmission. The system addresses the challenges of
inaccurate billing due to manual meter reading processes, which involve collectors
physically visiting customer premises to record water meter readings. Collectors
use Android smartphones equipped with a custom mobile application to input
meter readings directly at the site.
The Point of Sale (POS) serves as a popular alternative and portable device
for data storage. A POS device can extract data, which will then be utilized to
create a portable device for collecting water readings. The device will be
accompanied by a system that is capable of delivering the necessary use for water
reading. It can program or enhance many contemporary POS systems with
additional software (Hayes, 2024). These systems are adaptable to unique
requirements. For instance, a lot of businesses employ POS systems to oversee
membership programs that provide regular customers with points and discounts
on subsequent purchases (Hayes, 2024). POS systems provide a more secure
method of data storage compared to paper records, susceptible to damage from
fire, moisture, and other environmental factors. Because transactions are handled
and kept electronically, there is less chance that environmental conditions can
cause data loss. The system's backup and recovery features safeguard important

4
data in the event of data loss or system failure (Pos & Pos, 2023). By streamlining
data collection and reducing human error, such a system would ensure timely and
accurate billing. This transition to advanced reading and billing would significantly
improve service delivery, reduce operational costs, and enhance customer
satisfaction, aligning with the historical advancements in water meter technology
and reflecting the need for modern efficiency.
This research study developed an application and prototype to digitize data
collection and billing, aiming to address BMPC's challenges in a cost-effective
manner. The researcher constructed a wireless data collection and transmission
system with multiple input modalities to ensure interoperability and reliability under
various operational conditions. Through this digital solution, BMPC automated its
billing process, enhancing service reliability, operational efficiency, and customer
satisfaction.
Modernizing BMPC’s operations in line with utility management best
practices ensured its sustainability and scalability. The digital water meter reading
and billing system transformed the cooperative’s operations by improving
accuracy, speed, and reliability. It utilized water meters and digital communication
to remotely collect and wirelessly transmit water usage data to a central server.
This technology reduced human error in data collection and billing calculations.
The digital strategy optimized processes, allowing BMPC to expand
operations without increasing staff. The system digitized data collection and
processing using wireless communication modules and a digital application. This
eliminated manual data entry into Excel, freeing BMPC’s lone employee to focus
on customer support and maintenance. Automated data accuracy reduced manual
invoicing errors, improving customer satisfaction and minimizing disputes.
Automated systems proved to be efficient, sustainable, and adaptable.
BMPC was able to manage customer growth and changes in water usage without
additional personnel. This automated system improved BMPC’s operations and

5
enabled sustainable service expansion to meet the community’s needs. The
solution demonstrated BMPC’s commitment to modern technology and the
digitalization of utility management.
The main objective of this study was to design and implement a water meter
reading system at Bolo Multipurpose Cooperative that would improve water
reading processes. Specifically, it aimed to...
1. To design and implement a water meter reading system that can:
1.1. calculate the water consumption of each customer.
1.2. print an accurate billing statement.
1.3. update the database in real time.
2. To test the system in terms of:
2.1. accuracy of calculating the water consumption of each customer
2.2. reliability of printing formatted accurate billing statement
2.3. functionality of updating the database in real time.
3. To evaluate the system in terms of:
3.1. functional suitability
3.2. reliability
3.3. security
3.4. maintainability

6
Figure 1.1
Conceptual Framework

Figure 1.1 shows the conceptual framework for the creation of Water Meter
Reading. This framework consisted of 5 parts; each of the parts had its own
objective in the process of creating the system.
The first part introduced the problems; it started by identifying the issues of
the current system in the water meter reading. These problems included incorrect
data recording and an ineffective way of collecting information from the mechanical
water meters. This part aimed to understand the limitations of the current system
and the needs for a newer and more reliable solution.

7
The second part was designing the system, wherein the water meter
reading was designed to address the identified problems. The design of the system
included data collection and wireless transmission of information to the cloud.
Considering the necessary hardware and software was crucial to ensuring the
success of the system.
The third part was about the assessment and testing; the system was
assessed to ensure its effectiveness. The assessment included functionality and
wireless transmission testing. It aimed to ensure that the system met the expected
standards before it was put into actual operation.
The fourth part was the application of the final product, which focused on
the actual utilization of the system in operation. This part aimed to ensure the
reliable performance of the system in the real world and its effect on operation and
satisfaction of the customers.
The last part discussed the recommendation for the future, which offered
suggestions based on the discoveries in the study. The recommendations entailed
ideas for the improvement of the system and new studies that could be explored
to further improve the technology in water meter reading.
Overall, this framework showcased a systematic process of creation,
assessment, and improvement of water meter reading to ensure a newer solution
for the issues in the current system of water meter reading.
The scope of the study aimed to further advance the development of a water
metering system focused on the collection of water consumption data for the Bolo
Multipurpose Cooperative (BMPC), located in Bolo, Bauan, Batangas. The project
had two primary goals: the creation of a wireless meter to collect water
consumption data and transmit it to a cloud server, and the development of an
intuitive interface to facilitate billing and data access. In the worst-case scenario of
a lost connection, the device was equipped with a notepad feature that allowed

8
continued data collection. This data was subsequently synchronized with the
central cloud account once connectivity was restored.
The study critically examined the performance of the data acquisition
system and the reliability of wireless transmission. It focused on optimizing system
processes to enhance customer satisfaction.
The limitations of the study included its exclusive compatibility with Android
operating systems, which prevented use on alternative platforms. Additionally,
hardware constraints affected performance, potentially slowing down processing.
In areas with poor signal strength, latency hindered real-time tasks such as live
data synchronization and collection, as well as other network-dependent
operations. The system also faced challenges in achieving consistent user access
and ease of use due to its reliance on a stable internet connection, which was
problematic in rural or low-connectivity regions.
The researcher also highlighted the system’s potential to provide broad
access to sensitive data traditionally stored within the enterprise. However,
reliance on cloud-based storage and external networks introduced risks of cyber
exposure or data integrity breaches unless proper safeguards were implemented.
The project aimed to develop a water meter reading system that offered a
more efficient and precise method of data collection, thereby improving water
management practices at BMPC. The system enhanced meter reading and
invoicing processes by minimizing manual data collection, reducing computation
time, and eliminating human errors, while ensuring accurate billing. Its centralized
data management, combined with wireless transmission capabilities, supported
improved monitoring, resource allocation, strategic planning, and decision-making.

This project shall benefit the following and significantly influence the overall
conclusion of this device:

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For Bolo Multipurpose Cooperative (BMPC), the implementation of the
wireless water meter reading system will transform its operational framework by
automating data collection and billing processes. This automation will minimize
manual labor, reduce human errors, and enhance billing accuracy, thereby
improving operational efficiency. The system’s centralized data management and
wireless transmission capabilities will enable real-time monitoring of water
consumption, facilitating informed resource allocation and strategic planning. By
streamlining these processes, BMPC will be able to scale operations to
accommodate a growing customer base without requiring additional staff, ensuring
sustainability. Furthermore, the system’s reliability and maintainability, supported
by the Android 14 POS Machine, will reduce maintenance costs and downtime,
enhancing service continuity. These improvements will position BMPC as a
modern, efficient utility provider, strengthening its reputation and operational
resilience in Bolo, Bauan, Batangas.
For customers, they will experience enhanced service quality through
accurate, timely, and transparent billing facilitated by the automated system. The
reduction of manual errors will ensure fair billing, minimize disputes, and foster
trust in the cooperative’s services. The system’s intuitive interface, accessible via
the Android-based POS device, will provide real-time access to water usage data,
empowering customers to monitor consumption patterns and manage resources
effectively. Additionally, the integration of on-site payment options and electronic
bill generation via the POS terminal will enhance convenience, enabling seamless
transactions. By improving billing accuracy and service reliability, the system will
elevate customer satisfaction, reinforcing BMPC’s commitment to meeting
community needs. These advancements will align with modern utility management
standards, ensuring that customers receive efficient, high-quality water services.

10
Definition of Terms
This segment of the research delineates essential terminology employed
throughout the investigation. It functions as a reference to elucidate terminology
and resolve any technicalities or misunderstandings in the document.
Billing System: A system that calculates and generates invoices based on water
consumption data, ensuring accurate and timely billing for customers.
Bolo Multipurpose Cooperative: The beneficiary of the implementation of
wireless water reading system.
Cloud Server: An account from Google that connected to sheets API.
Data Collection: The process of gathering water usage information from water
meters, either manually or through automated systems, for billing and monitoring
purposes.
Functional Suitability: The degree to which a system meets its specified
requirements, such as accurate data collection, billing, and user interface
functionality.
Human Error: Mistakes made during manual data collection or entry, leading to
inaccuracies in water meter readings or billing calculations.
Maintainability: The ease with which a system can be repaired, updated, or
modified to ensure long-term performance and cost-effectiveness.
Manual Meter Reading: The traditional process of physically visiting customer
sites to record water meter data, often prone to inaccuracies and inefficiencies.
Android Point of Sale (POS): A portable electronic device used for data storage
and processing, capable of collecting water meter readings and facilitating billing
transactions.
Reliability: The consistency and dependability of a system in performing its
functions under varying conditions, including data transmission and storage.

11
Security: The protection of data and systems from unauthorized access, cyber
threats, or breaches, particularly in cloud-based storage and wireless
transmission.
Water Consumption: The volume of water used by a customer, measured by a
water meter in units such as cubic feet or gallons.
Water Meter: A device that measures the volume of water flowing through a pipe
or outlet, used to track consumption for billing and monitoring.
Wireless Transmission: The process of sending water meter data to a central
server or system via wireless communication, enabling real-time updates and
remote access.
Water Utility Management: The comprehensive process of BMPC in planning,
distributing, and regulating water resources to ensure a reliable and sustainable
supply to communities.
Wireless Water Meter Reading System: A system that automatically collects and
transmits water usage data wirelessly, reducing the need for manual data
collection and improving accuracy.

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2.0 METHODOLOGY
This chapter presents the theoretical framework and methodological
approach that guided the research. The study employed developmental research
techniques to structure the process. This research method accompanied the
ADDIE model for the stages of research.

The ADDIE model (Analysis, Design, Development, Implementation, and
Evaluation) emerged as a foundational framework in instructional design, with its
origins traced back to training programs developed for the U.S. Army during World
War II. The ADDIE model was a widely utilized framework for instructional design,
prominently used by educators and content developers to create effective training
programs and educational materials (EBSCO Research Starters, 2024). Recent
developmental research focused on integrating rapid prototyping principles with
the ADDIE framework to create more flexible and responsive instructional design
models. This study attempted to customize the popular analysis, design,
development, implementation, and evaluation (ADDIE) model to build an
instructional prototype in the blended learning (BL) environment. As ADDIE had its
limitations, e.g., it required adequate funding and a longer timeframe to implement,
researchers sought to conceptualize pedagogical designs that combined both
approaches for enhanced effectiveness (Islam et al., 2022). One commonly
accepted improvement to this model was the use of rapid prototyping. This
involved receiving continual or formative feedback while instructional materials
were being created. This model saved time and money by catching problems while
they were still easy to fix (ADDIE, 2023). This integration represented a significant
shift from linear to iterative design processes, allowing for continuous refinement
and adaptation based on user feedback and changing requirements.

The application of ADDIE-based rapid prototyping emerged as a pivotal
strategy in addressing educational disruptions, particularly during the

13
unprecedented challenges posed by the COVID-19 pandemic, which necessitated
a swift transition from traditional, in-person classroom settings to fully digital or
hybrid learning environments. This approach, rooted in the systematic Analysis,
Design, Development, Implementation, and Evaluation (ADDIE) framework,
allowed instructional designers and educators to adapt quickly to the evolving
demands of remote and blended learning contexts. The findings from empirical
studies, such as those conducted by Islam et al. (2022), underscored that the
ADDIE-based instructional design was not only reliable but also valid as a
pedagogical approach, particularly when implemented in blended learning
environments tailored for polytechnic students. This model facilitated the seamless
integration of digital tools and instructional strategies, ensuring continuity in
education despite external constraints.
Moreover, the literature highlights a critical gap in the exploration of
instructional design models specifically tailored for rapid adaptation from face-to-
face to online learning environments. Dong (2021) noted that while numerous
frameworks exist, few studies have comprehensively addressed the specific
models or methodologies that enable educators to pivot effectively and efficiently
during such transitions. This gap emphasizes the urgent need for flexible, scalable,
and adaptive design approaches that can respond to sudden shifts in educational
delivery while maintaining pedagogical integrity. The ADDIE-based rapid
prototyping model addresses this need by offering a structured yet agile framework
that allows for iterative development and refinement of instructional materials,
ensuring alignment with learning objectives even under time constraints.

The figure below showed the ADDIE Model, which discussed the stages
and detailed information:

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Figure 2.1
ADDIE Model

2.1. Analysis
A. Pre-Design
The pre-design stage laid the foundation for the project by defining the
hardware and software requirements and establishing the input-process-output
(IPO) relationship diagram, which served as a blueprint for the system’s process

15
flow. This stage identified the essential components necessary to achieve the
desired system output, ensuring a structured and feasible development approach.
Conceptualization of the project
This study proposed a comprehensive water metering system integrated
with an Android-based Point of Sale (POS) device to enable semi-automated data
collection and billing. The POS device was designed to accurately measure water
consumption in cubic meters, store large volumes of data, and wirelessly transmit
the collected information to a central server. This solution addressed common
challenges in traditional metering, such as inaccurate readings, inefficient data
handling, and unreliable tracking of water usage (Duneslab.AI, 2023). The
system’s intuitive interface ensured ease of use for both customers and operators,
enhancing operational efficiency. By eliminating manual readings, the system
minimized human error and streamlined processes, aligning with modern utility
management standards.
A key feature of the project was the development of an automated solution
for capturing water consumption data and generating bills for the Bolo
Multipurpose Cooperative (BMPC). The system was engineered to record real-
time data from water meters with precision, enabling accurate monitoring of each
consumer’s usage. This data was critical for producing reliable billing statements.
Additionally, the system integrated bill printing capabilities directly into the POS
terminal, reducing manual computation errors and accelerating the billing process.
These features enhanced operational efficiency, improved service delivery, and
ensured customers received timely and accurate water usage information,
fostering trust and satisfaction.

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B. Hardware Requirements
This section outlined the hardware requirements for the Android-based
POS system essential to the water metering prototype. The POS device captured
and transmitted water usage data in real-time, enabling seamless billing and
efficient transaction processing. Key performance needs included robust data
handling, high processing speed, and an intuitive user interface to ensure a smooth
experience. Additionally, long battery life was crucial for uninterrupted daily
operation, and cost-efficiency was considered to support large-scale deployment.
Each hardware component was selected to balance affordability, performance,
and user-friendliness, ensuring the POS device met the project’s technical
demands.
The POS system required strong connectivity for wireless data transfer, with
Wi-Fi and Bluetooth for stable communication with the server. Compatibility was
critical, allowing the POS device to integrate with software applications, digital
reading, and billing. This setup provided real-time data access, enabling accurate
and transparent billing. By focusing on connectivity and battery life, the POS
system streamlined the billing process, enhanced operational efficiency, and
improved customer satisfaction by delivering fast, reliable, and precise service.
The Android POS Device Assessment Criteria included four key factors:
cost, compatibility, connectivity, and life span. Cost reflected the device’s
affordability while ensuring essential features and reliability, with a weight of 10%.
Compatibility, with a weight of 40%, ensured that the POS device integrated
seamlessly with other components such as a built-in printer and wireless
connectivity. Connectivity, carrying a weight of 30%, assessed the device’s
capability to connect via Wi-Fi, Bluetooth, and other relevant communication
protocols. Finally, Life Span, with a weight of 20%, gauged the battery’s ability to

17
sustain continuous operation throughout the day. Each criterion was assigned a
specific weight, indicating its significance in the overall assessment.
Choosing Kotlin for the design and implementation of the wireless water
meter reading system in Bolo Multipurpose Cooperative provided significant
benefits. First, Kotlin was a modern programming language designed to be
interoperable with Java, which enabled the use of a wide range of Java libraries
needed for hardware integration. According to Drosopoulou (2024), the
interoperability of Kotlin with Java was a fundamental advantage, allowing
seamless integration of Kotlin code into existing Java codebases. Additionally, the
concise and expressive syntax of Kotlin made the development and maintenance
of the code easier, while its built-in null safety helped avoid system crashes that
might have affected the efficient operation of a hardware-based system.
Furthermore, Kotlin’s ability to compile to various platforms, including native
code through Kotlin/Native, enabled its use in various hardware environments.
According to, Kotlin/Native was designed to allow compilation for platforms where
virtual machines were not desirable or possible, such as embedded devices and
iOS. This flexibility was essential in developing cross-platform applications that ran
on various devices, including embedded systems used in Internet of Things (IoT)
devices. By using Kotlin/Native, a self-contained program was executed without
the need for additional runtime or virtual machines, which was appropriate for
hardware-constrained environments.

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Table 2.0
Likert Scale Scoring
5 Points 4 Points 3 Points 2 Points 1 Point
Very
Satisfied
Satisfied Neither Satisfied
nor Dissatisfied
Dissatisfied Strongly
Dissatisfied

The proponents used the Likert scale shown in table 2.0 as a reference for
scoring the components according to the categories cited above. The Likert scale
offered respondents a choice of five to seven pre-coded responses with the neutral
agree or disagree.
The following table show the assessments of different types of Android
Point of Sale devices used in the prototype. The different types of Android POS
were Android 14, Android 13, and Android 12. They were scored according to cost,
compatibility, connectivity, and life span. The price was based on the supplier’s
standard quotations.
Assessment of Android POS Devices
Below was an evaluation of three potential Android POS devices based on
the criteria established in Table 2.1. Each device was rated on a scale of 1 to 5,
where 5 was the highest rating and 1 was the lowest.

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Table 2.1
Android POS Device Component Ratings
Item Device Compatibility Connectivity Life Span Cost Total
1 Android 14 5 5 5 3 18/20
2 Android 13 4 4 4 3 15/20
3 Android 12 3 3 3 4 12/20
Table 2.1 provides a detailed evaluation of three Android POS device
models, each running a different version of the Android operating system. The
table assessed each model based on five criteria: cost, compatibility, connectivity,
and life span. Each criterion was scored on a scale from 1 to 5, with 5 being the
highest score (indicating superior performance in that area) and 1 being the lowest.
The Total Score column represented the sum of these individual ratings, giving an
overall score for each model. Android 14 scored 3 in cost because of its various
features while achieving the highest score of 5 in compatibility and connectivity,
which denoted the highest degree of speed, outstanding integration, and strong
connection ability, respectively. Furthermore, its life span was rated 5, suggesting
it had long support and exceptional durability. With a total score of 18, Android 14
was the best option because it had no critical drawbacks. Android 13 scored a 3 in
cost, indicating average price affordability. Its compatibility scored a 4, indicating
good incorporation with up-to-date applications, and connectivity scored 4,
showing better features. Lifespan also scored a 4, indicating longer support life.
With a total score of 15, Android 13 was considered a decent option but lacked the
cutting-edge capabilities. Android 12 scored 4 in cost, possessing the lowest costs,
making it quite affordable. In compatibility, it scored a 3 as it ran most older
software but not necessarily advanced ones, and a score of 3 in connectivity
showed satisfactory options only. The life span rating was 2, depicting poor long-
term support mechanisms. With a total score of 12, Android 12 was the least
favorable of the three models.

20
In summary, Android 14 was the highest-rated model, offering strong
performance, great compatibility, connectivity, and integration in its design.
Android 13 provided a reasonable model with adequate but basic functionality,
lagging behind Android 14. Android 12 was the cheapest; however, it had the
lowest total score, making it a less favorable choice compared to the other two
models.
POS Device Percentage Rating
The percentage rating for each device was calculated by multiplying each
criterion’s score by its respective weight.
Table 2.2
Android POS Device Percentage Rating
Item Device Compatibility
(40%)
Connectivity
(30%)
Life Span
(20%)
Cost
(10%)
Total
1 Android 14 2 1.5 1 0.3 4.8
2 Android 13 1.6 1.2 0.8 0.3 3.9
3 Android 12 1.2 0.9 0.4 0.4 2.9
Table 2.2 shows that Android 14 was chosen as the best option for the
project, achieving the highest grade of 4.8. Its improved specifications performed
well in reliable performance for tasks involving real-time data transfer and billing,
making it suitable for high-demand situations where speed and precision were
required. Android 13 scored a commendable 3.9, an appreciable rating but a more
cost-effective option while satisfactory in fulfilling the basic requirements of the
project. It did not feature advanced capabilities like Android 14 but provided
average performance and battery life, sufficient for most real-time billing and data
management tasks. Android 12 scored the lowest at 2.9, indicating severe
problems with performance and connectivity. Its limitations made it less capable of
processing high-speed data transfer, suitable only for situations where data

21
demands were low and the primary goal was cost savings rather than advanced
features.
C. Software Requirements
The software requirements for the "Design and Implementation of Water
Meter Reading at Bolo Multipurpose Cooperative" project were designed to enable
the integration of a Point of Sale (POS) system while enhancing the capabilities of
the water metering application. The system collected real-time data on water
usage, computed monthly consumption, and provided precise bills according to
predetermined tariff rates (Mahmud, Yusuf, & Ahmed, 2020). Users registered and
managed their accounts, allowing them to check billing details, water usage
history, and payment status through a simple and user-friendly interface. This
system improved billing accuracy, enhanced customer access to information, and
helped the cooperative manage water consumption more efficiently.
Upon completion of each billing cycle, the software autonomously produced
electronic bills, facilitating efficient communication with users. The implementation
of the POS system enabled on-site payments, ensuring a smooth and secure
transaction process. The system integrated secure online payment options,
offering consumers multiple flexible bill payment methods. To improve user
engagement, it included analytics tools that provided insights into water usage
trends, assisting both users and administrators in managing resources more
effectively (Li, Zhang, & Liu, 2021).
For optimal performance, the system ensured that bill calculations and
invoice generation were completed within three seconds of data retrieval,
delivering a seamless and responsive user experience. It was scalable, capable of
supporting a growing number of users and water meters while efficiently handling
larger data volumes (Taggle Systems, 2024).
To maintain data security, the system implemented encryption techniques
and secure authentication protocols, preventing unauthorized access to sensitive

22
user information. Additionally, if no user records existed in the database, the
system displayed an appropriate message and prompted administrators to register
users, ensuring smooth operation even in an empty database state.
Numerous software applications were developed using languages that
facilitated spreadsheet integration and database configuration:

Kotlin is a modern programming language for Android development that
operated on the Java Virtual Machine (JVM). Despite being relatively new, it
gained significant traction due to its concise syntax and robust features. Kotlin was
fully interoperable with Java, allowing it to leverage Java’s extensive libraries and
frameworks. It compiled to Java Bytecode, offering a refined and efficient
alternative to Java for Android applications (Blair, 2024). Kotlin’s built-in null safety
features reduced the risk of runtime errors, making it ideal for hardware-integrated
systems like water metering.
Java remains a staple in Android development due to its maturity and vast
ecosystem of libraries, frameworks, and tools. While it was gradually overtaken by
Kotlin in new projects, Java’s interoperability with Kotlin ensured it remained
relevant, allowing developers to integrate legacy Java code into Kotlin-based
projects seamlessly (Suddia & Suddia, 2024).
Power Apps is a low-code platform offering a rapid development
environment for customized business applications. It connected to various data
sources, including Microsoft Dataverse, SharePoint, Microsoft 365, Dynamics 365,
and SQL Server, using Power Fx, an Excel-like formula language (Tapanm-Msft,
2024). While effective for quick app development, it lacked the flexibility and
performance optimization required for hardware-intensive systems.
The researchers selected Kotlin as the primary programming language for
the water metering system’s Android software development. The Bolo
Multipurpose Cooperative (BMPC) relied on Excel for computation, and Kotlin’s
ability to integrate with Java libraries enabled seamless interaction with Excel-

23
compatible data formats and database systems. This implementation ensured
accurate data transmission to servers while offering superior control over hardware
integration, such as the POS device and wireless communication modules.
An application developed in Kotlin allowed users to access real-time water
usage data, billing information, and payment options through an intuitive interface.
Kotlin’s modern features, such as coroutines for asynchronous programming,
enabled efficient handling of real-time data collection and wireless transmission,
critical for the project’s success. Its interoperability with Java allowed the use of
established libraries for secure data management and visualization of usage
patterns, facilitating the creation of interactive dashboards and robust database
integration. Additionally, Kotlin/Native supported compilation to native code,
making it suitable for embedded systems and IoT devices without requiring a
virtual machine. This flexibility ensured the system’s scalability, security, and
performance aligned with BMPC’s operational needs.
In summary, Kotlin stood out as the most favorable choice for the project
due to its modern design, seamless Java interoperability, and robust support for
Android development. Unlike Power Apps, which prioritized low-code simplicity but
lacked depth for hardware integration, Kotlin offered precise control over system
processes, ensuring real-time data accuracy and efficient billing. While Java
remained a reliable option for legacy systems, Kotlin’s concise syntax, null safety,
and cross-platform capabilities via Kotlin/Native made it a superior choice for
modernizing BMPC’s water metering system. This selection enhanced operational
precision, supported scalable growth, and aligned with the project’s goals of
improving efficiency and customer satisfaction at the Bolo Multipurpose
Cooperative.
2.2. Design
Design and Development Stage
Flowcharts were essential in the design of the water metering POS system;
they aided the selection of components and choices of materials while helping the

24
user visualize program flow. Visualization was more advantageous to new
programmers because most could not visualize from pseudo-code. According to
(Priyadharsini and Arunbalaji, 2020), flowcharts facilitated easy comprehension of
significant processes, such as data collection and billing, which were the basics
for utility applications. (Da Ribeira Tigeleiro, 2021) showed that the Android
application was presented for real-time data collection and user interaction
demonstration. This structured approach to development ensured that the
developer made interfaces for real-time billing and usage metrics user-friendly and
ensured that precision in coding and testing met the expectations of users.
Android-based POS systems provides great benefits for data accuracy,
efficiency, and automation. Their research showed that Kotlin-powered
applications simplified the real-time data collection process and automated
transaction processing, ensuring error-free billing and greater operational
reliability. Additionally, wireless data transmission technology enables field devices
and central databases to update smoothly, reducing manual labor and human
error. In the water metering POS system, the technology enables devices to track
water consumption accurately, calculate bills immediately, and communicate
transparently with both customers and service providers. Moreover, Kotlin enables
the technology to be more maintainable, secure, and compatible with other
platforms, making it a strong solution for Bolo Multipurpose Cooperative to
modernize its water metering and billing processes.
The Kotlin-based POS system, when applied to water meter reading, allows
settings on the display to be altered and marked some fields, for example, as
writable while others were read-only. In an Android-based POS system, it was
central to collect data efficiently, moving away from paper-based systems to cloud
computing with data synchronized remotely. The advantages of Android POS
systems in data collection automation and operational efficiency through cloud
integration and real-time synchronization. The system also enables workers to

25
insert new readings and keep data up to date, reducing miscalculations of meters.
The system comprised local and cloud-based databases, updating records with
unique IDs to avoid conflict and duplication. Preset values, such as automatic data
entry, simplified data collection processes, eliminated human error, and optimized
operational output for field operators and companies. Wireless data transfers were
a strong feature attained by integrated network modules. Physical SIM cards
enable real-time communication, and the mobile app works offline, storing data on
the device and updating when the system reconnects to the internet.
2.3. Development
The development phase of the wireless water meter reading system for Bolo
Multipurpose Cooperative (BMPC) transformed the design specifications into a
working prototype that addressed the cooperative’s operational requirements for
automated water billing and data management. This systematic approach
integrated the selected hardware and software components into a cohesive,
functional system that reliably handled real-time data collection, accurate billing
calculations, and seamless communication between field devices and central
databases.
The Android application development utilized Kotlin as the primary
programming language, following the Model-View-ViewModel (MVVM) pattern to
ensure maintainable and testable code structure. The core application framework
integrated key modules, including data collection for capturing water consumption
readings with input validation, billing computation that processed usage data
according to BMPC’s predetermined tariff rates, database management for local
storage and server synchronization with offline functionality, and communication
management for wireless data transmission through Wi-Fi and Bluetooth
protocols. The user interface prioritized simplicity and efficiency for field operators,
featuring large, clearly labeled buttons and input fields optimized for the 5.5" HD+

26
display, with intuitive workflows that mirrored manual processes to reduce the
learning curve during implementation.
Database development encompassed both local SQLite storage for reliable
performance and data persistence on the Android device, and cloud-based
integration for centralized management and real-time administrative access. The
database structure included tables for customer information, meter readings,
billing records, and transaction logs, with local storage enabling offline operation
when network connectivity was unavailable. Data synchronization occurred
automatically when connectivity was restored, ensuring consistent information
across all system components while providing comprehensive reporting and
analytics capabilities through the cloud database.
Hardware integration development optimized the Senraise Android 14
Bluetooth Smart POS Machine as the primary platform, configuring the Android
14.0 operating system for water utility operations with custom firmware
modifications for efficient resource utilization and extended battery life. The built-
in 58mm thermal printer integration included custom print templates complying with
BMPC’s billing format requirements, generating comprehensive receipts at
80mm/s speed with error handling for low battery or paper shortage conditions.
Wireless communication implementation utilized Bluetooth and Wi-Fi connectivity
through secure protocols, incorporating connection management, data encryption
using AES-256 protection, error recovery mechanisms, and bandwidth
optimization through data compression techniques.
The development phase concluded with comprehensive system validation
through controlled testing that simulated actual field operations under various
conditions, establishing performance benchmarks for transaction processing
times, data accuracy levels, and system availability rates. The completed
development delivered a fully functional wireless water meter reading system that
addressed BMPC’s operational requirements while providing a foundation for

27
future enhancements and scalability improvements, ensuring reliable performance
in real-world deployment scenarios.
2.4. Implementation
Test Selection
The Bolo Multipurpose Cooperative was designated as the testing location
for the proposed water meter reading technology. The test selection procedure
emphasized the system’s functional suitability, reliability, maintainability,
compatibility, flexibility, performance efficiency, and interaction capabilities. The
evaluation criteria were designed to yield quantifiable outcomes, consider
environmental factors, improve performance, and guarantee the longevity of the
system.
The device produced precise and dependable data that was accurately
transferred and displayed on the central server, fulfilling the cooperative’s
operational requirements. Environmental variables, including fluctuating weather
conditions, were taken into account during testing to assess the system’s
robustness and adaptability. The system’s performance and durability were
evaluated using stress testing to confirm its capacity for sustained use and
operating efficiency. These essential elements directed the test selection process,
affecting the research’s success and facilitating system enhancement.
Test Performance
This section detailed the testing methodologies designed to evaluate the
wireless water meter reading system developed for the Bolo Multipurpose
Cooperative (BMPC). The testing focused on three key objectives: ensuring the
accuracy of calculating water consumption for each customer, verifying the
reliability of printing accurate billing statements, and confirming the functionality of
real-time database updates. Each test was structured to provide measurable

28
outcomes, ensuring the system met operational requirements and enhanced
efficiency.
Accuracy was assessed using a quality control method for measurement,
where data was used to compute the differences between automatic and manual
computations. The differences between the two datasets were compared, and
remarks were made to determine accuracy.
Reliability aimed to identify discrepancies between digital (soft copy) and
printed (hard copy) bills, focusing on content accuracy (e.g., text, numbers) and
formatting consistency.
Functionality made latency—the time taken for a request to travel from the
device to the cloud server and back (round-trip time)—a critical performance factor.
The objective was to enable real-time data transmission from the POS device to
the cloud server.
2.5. Evaluation
Review and Selection
As previously stated, water meter readings were handled manually by the
Bolo Multipurpose Cooperative (BMPC) in Bolo, Bauan, Batangas. To track water
usage and generate billing information, an employee physically visited each client
to take meter readings, which were then entered into an Excel database.
BMPC prepared to implement the Senraise Android 14 Bluetooth Smart
POS Machine, a sophisticated all-in-one POS terminal designed to optimize
operations and increase efficiency. By integrating cutting-edge payment
technologies, this innovative device provided faster and more secure transactions.
Although designed for various corporate uses, its small size and strong
performance made it ideal for managing water services.

29
The device featured an Android 14.0 operating system powered by an Octa-
core 2.3GHz processor with 3GB RAM and 32GB ROM DDR4 memory, ensuring
smooth and efficient performance. Its 5.5” HD+ multi-touch display simplified input
and navigation, while the built-in 58mm thermal printer provided speedy (80mm/s)
and reliable receipt generation. Equipped with Bluetooth (3.0/4.2/5.1 BLE) and Wi-
Fi (2.4G/5G) connectivity, the machine seamlessly transmitted transaction data to
a centralized database.
Once implemented, BMPC employees only needed to input water
consumption data into the device. The machine calculated water bills instantly and
securely stored transaction details in a database. This eliminated manual
computation errors, enhanced service speed, and provided detailed records for
easier auditing and reporting.
BMPC’s adoption of the Senraise Smart POS Machine marked a
transformative step toward operational modernization, ensuring greater accuracy,
convenience, and improved service delivery to its customers.
In conclusion, the adoption of the Senraise Android 14 Bluetooth Smart
POS Machine as the cornerstone of BMPC’s modernization initiative represented
a comprehensive and strategic solution that addressed key operational needs. Its
functional suitability was demonstrated by its tailored design for managing water
services, ensuring accurate billing and seamless transaction processing. The
device’s robust specifications guaranteed reliability through consistent
performance, while its Android-based architecture and modular design enhanced
maintainability, enabling smooth updates and servicing. The machine’s
connectivity options, including Wi-Fi, ensured compatibility with existing systems,
while its compact design and versatile features underlined its flexibility for diverse
operational scenarios. With a high-speed processor and efficient memory, the
device offered outstanding performance and efficiency, supporting rapid data

30
processing and minimizing downtime. Finally, its user-friendly interface and multi-
touch HD+ display enhanced interaction capability, ensuring intuitive and
convenient use for employees.
Overall, the integration of this innovative hardware marked a transformative
step for BMPC, delivering streamlined processes, reduced errors, and improved
customer service—key elements in achieving operational excellence and aligning
with modern technological standards.
Software Production Quality Evaluation
The Senraise Android 14 Bluetooth Smart POS Machine aligned
comprehensively with the ISO 25000 software product quality model,
demonstrating excellence across multiple quality attributes essential for Bolo
Multipurpose Cooperative (BMPC)’s modernization efforts. To ensure the
attainment of the objectives, the researchers gathered 45 respondents to the
questionnaire, offering valuable insights about the system. The group included four
employees and one manager from the Bolo Multipurpose Cooperative. In terms
of functional suitability, the device ensured functional completeness, as it fully
supported meter reading input, automated billing computation, and receipt
generation, eliminating manual errors and inefficiencies.
Functional Suitability
The device comprehensively supported water billing, meter reading input,
and receipt generation, ensuring completeness. It minimized manual errors
through automated calculations, enhancing correctness. Tailored specifically for
water service management, it met BMPC’s needs with appropriateness.

31
Reliability
The system demonstrated faultlessness by minimizing calculation errors
and enhancing accuracy. Its reliable hardware and software ensured availability,
maintaining uninterrupted operations. Additionally, fault tolerance was achieved
through secure data storage, significantly reducing the risk of information loss.
Security
The system ensured robust security and integrity through multiple
measures: data was stored securely in a centralized system to maintain
confidentiality, transactions were logged to ensure non-repudiation and
accountability, secure storage prevented data tampering to uphold accountability,
real-time validation of transactions guaranteed authenticity, and the system was
designed to resist unauthorized access, further reinforcing its security.
Maintainability
The system was designed with modularity, leveraging the Android OS to
simplify updates and maintenance. Its reusability allowed it to be repurposed for
various billing tasks, enhancing its versatility. The system also prioritized
analysability, generating detailed logs for efficient auditing. Additionally, its
modifiability enabled easy configuration to accommodate different billing
structures. Finally, the system's testability ensured it could be seamlessly
evaluated using real-time data inputs, streamlining the testing process.
As the final evaluation, the Senraise Android 14 Bluetooth Smart POS Machine
met all major ISO 25000 software product quality attributes, making it a highly
reliable, efficient, and secure solution for BMPC’s modernization.

32
3.0 RESULTS AND DISCUSSION
This chapter presents the results of the design, implementation, and
evaluation of the Wireless Water Meter Reading System developed for Bolo
Multipurpose Cooperative (BMPC). The system aimed to modernize the
cooperative's water billing operations by addressing key limitations of their existing
manual processes, including inefficiencies, human errors, and delayed billing.
Through detailed analysis of hardware integration, software functionality, and
wireless data transmission, this section showcases how the prototype system
successfully streamlines meter reading, bill computation, and data management.
The results are interpreted based on actual testing phases, user feedback, and
ISO 25000 software quality standards, providing insights into the system’s
functional stability, reliability, security, and maintainability. Ultimately, this chapter
demonstrates the practical effectiveness and potential scalability of the proposed
solution in enhancing BMPC’s service delivery and customer satisfaction.
3.1. Design and Implementation of the System
In this section, this paper provides the technical foundation and the
development of the Wireless Water Meter Reading System. The purpose of the
system is to address the problems that the Bolo Multipurpose Cooperative meets
in manually gathering information, billing, and water consumption monitoring. The
project progresses through the phases of preliminary preparation (planning),
hardware system design, integration of the hardware, and software
implementation.

The block diagram presents a visual overview of how the process of the
billing works:

33
Figure 3.1
Block Diagram

Figure 3.1 illustrates the updated system architecture for the Wireless Water
Meter Reading System. In this setup, the process begins with the Water Meter
Reader, which collects water consumption data from individual households. This
data is then transmitted to the POS System, which serves as the central
processing unit. The POS System performs real-time computation of the
customer's water bill based on the received readings. Once the computation is
completed, the POS System simultaneously executes two critical operations: it
sends the billing information to the PRINTER to generate a physical receipt for the
customer, and it transmits the same data to the CLOUD SERVER for secure
storage, monitoring, and future access. The bidirectional arrow between the POS
System and the Cloud Server indicates that data can be both uploaded and
retrieved as needed, supporting system updates, record-keeping, and customer
service functions. This streamlined process enhances operational efficiency,
accuracy, and service reliability for the Bolo Multipurpose Cooperative.
The system flowchart outlines the operational sequence of the prototype:

34
Figure 3.2
System Flowchart

35

36
Figure 3.2 illustrates the operational workflow of the Android-based
application developed for the Bolo Multipurpose Cooperative (BMPC), designed to
automate water meter reading, billing, and data management. Upon initialization,
the app loads cached customer IDs and the last read ID from SharedPreferences,
enabling a user interface with spinners for street and month selection, input fields
for customer IDs, readings, and remarks, and buttons for actions like verify, submit,
print, search, list, notepad, and history. Users begin by selecting a street and
month, prompting the app to fetch customer IDs from Google Sheets if online, or
use cached IDs offline, while requesting the spreadsheet to display only the
relevant month’s columns. Next, users enter and verify a customer ID, which the
app validates against the street’s customer list, retrieving name, previous reading,
and remarks online or confirming via cache offline, displaying details or errors
accordingly. Users then input readings and remarks, with the system defaulting to
fetched or zeroed previous readings and ensuring current readings are valid. Upon
submission, the app validates inputs, calculates usage and bills using tiered rates
(e.g., PHP 85 for ≤ 5 m³), computes a 15% post-due penalty, generates receipt
text, updates history, and sends data to Google Sheets online or stores it locally
offline, clearing fields and suggesting the next ID. Receipts are printed via a 58mm
thermal printer, with bolded bill text, triggered by the print button or history reprint.
Additional features include searching customers by name, listing customers with
color-coded reading status, note-taking via a notepad, viewing daily reading
history, and accessing the Google Sheet for backup. The app synchronizes
pending submissions on startup or when online, ensuring data integrity. With
robust error handling, offline resilience, HTTPS-based security, and scalable
Google Sheets integration, the system aligns with research goals by displaying
data, computing consumption, printing statements, updating customers, and
transmitting data wirelessly, achieving high user ratings (3.85–3.94) and Mr.
Magbojos’ 98–100% endorsements for stability, reliability, security, and
maintainability.

37
Figure 3.3
Actual Hardware Set-Up

Figure 3.3 shows that the POS system used in the water meter prototype
has hardware that enables it to record and send real-time data, which makes it
easy to generate correct bills and complete transactions. Since large-scale
deployment relies on robustness, speed, user-friendliness, and cost-saving, the
POS device should provide these benefits. For techs, having Wi-Fi and Bluetooth
connectivity is crucial to keep the server connected and integrate software
applications and digital billing without problems. In the device assessment, 40% is
given to compatibility, 30% to connectivity, 20% to battery life, and 10% to cost to
ensure the product has good balance and can be used comfortably. The goal of
both hardware and software solutions is to supply a water metering system to Bolo
Multipurpose Cooperative that can be scaled up, remains reliable, and is user-
friendly.

38
System Operation
This section describes the components and operation of a system that
manages customer water meter readings. Each part of the user interface is
detailed, from selecting the month for billing purposes to entering the kind of
identification needed to distinguish one customer from another. The readings
themselves can be easily and accurately submitted, and both the current month's
and past months' meter readings are readily available for access by the customer
service representative. That access is part of streamlined operations, one of the
system's main features.
Figure 3.4
Parts of the Interface Software

39
The application features a user-friendly interface designed for managing
water meter readings with several key functionalities. Users can select a month,
such as January or February, from a dropdown list of predefined months. A
Customer ID input field allows users to enter a customer ID to verify and retrieve
associated customer data. By clicking the Verify Customer Button, the system
checks the entered customer ID against the selected street’s data stored in a
Google Sheet. Once verified, the Customer Name Display shows the customer’s
name linked to the provided ID, while the Previous Month Reading Display
presents the previous month’s water meter reading for that customer. If necessary,
users can manually enter the previous month’s reading in cubic meters using the
Previous Reading Input field, and the current month’s reading can be entered in
the Present Reading Input field, also in cubic meters. The Street Spinner enables
users to choose a street, such as Rizal 1 or Rizal 2, from a predefined list. For
additional notes, the Remarks Input field allows optional entry of remarks or
comments related to the reading. The Submit Reading Button facilitates the
submission of the water meter reading data to the Google Sheet and provides
options to print or save the billing statement as a PDF. Users can also back up
data to XML by clicking the Backup to XML button, which opens the Google Sheet
in a browser for manual download. The Print Receipt Button generates a receipt
for the last submitted or selected reading, and the Last Customer ID Display shows
the ID of the most recently processed customer. Additionally, the List Button
displays a paginated list of customers for the selected street and month, while the
Search Button opens a dialog to locate a customer by name. The Notepad Button
provides a dialog for entering and saving notes, and the History Button opens a
dialog displaying the history of readings submitted on the current day.
This section displays a comparison between the data entered on a Point of
Sale (POS) device and the corresponding printed receipts for water consumption
data. On the left side, the POS interface shows digital records under the "INPUT"

40
section, including details such as the month (January), customer ID (77), street
(Rizal 1), previous month reading (582.0 m³), current reading (599.0 m³), usage
(17.0 m³), bill amount (PHP 312.0), after due amount (PHP 359.0), garbage fee
(PHP 70-100), and optional remarks. This data is structured and formatted for easy
review and entry, with buttons for verifying customers, submitting readings,
backing up to XML, printing receipts, and accessing additional features like
notepad, search, list, and history. The "OUTPUT" section on the left mirrors this
information, providing a digital summary including the cooperative's name (BOLO
MULTIPURPOSE COOPERATIVE), address, and a detailed breakdown of the bill.

The "PRINTED" section shows the physical receipt, which contains nearly
identical critical information as the POS input, including the cooperative details,
customer information (with ID 77), billing month, due date (February 25, 2025),
previous and current readings, usage, bill amount, after due amount, garbage fee,
and remarks. The consistency between the digital input and the printed receipt
highlights the system's accuracy and transparency, ensuring that what is captured
digitally is reliably reflected in the customer's physical copy. The process involves
users entering the month, customer ID, and meter readings, after which the system
verifies the details and calculates the total water usage (e.g., 17.0 m³ from 582.0
m³ to 599.0 m³). This streamlined calculation generates a detailed bill, fostering
accurate billing and clear communication of water consumption to the customer.

41
Figure 3.5
Sample Receipt
INPUT OUTPUT PRINTED

This section presents the timestamps associated with the transmission of
data from the device to the database, demonstrating the device's capability to send
data in near real-time, in alignment with the specified objectives. The first column
displays a screenshot of the actual device, including the timestamp indicating when
the data was submitted. The second column shows a screenshot of the database,
detailing the customer information and corresponding timestamp. A delay of a few
seconds may occur due to the automatic activation of the print function upon data
submission. However, the database timestamp, as shown below the table,
confirms that the data has been successfully transmitted

42
Figure 3.6
Device to Database Timestamp
Screenshot of device Screenshot of the database

3.2 System Testing and Troubleshooting
The wireless water meter reading system at Bolo was tested from March 15
to April 30, 2025. The purpose of the assessment was to see if it effectively
measured and tracked water usage on the property. During the testing period,
different aspects were checked for accuracy and reliability. Users also provided
feedback to help improve the system to better meet their needs.

43
Figure 3.7
Water Reading Device Functionality Test Pie Chart After Implementation

Figure 3.7 shows the results of the pie chart functionality test for the water
reading device after its implementation. The chart indicates that 62.7% of success
together with the 36% experienced in debugging issues and the 1.3% of failure is
faced outright in achieving the desired functionality. This data highlights that while
the majority found the device effective, an important portion of encountered
challenges needs to be addressed. The feedback gathered from the premises
during this testing period can guide improvements to ensure the device operates
reliably and meets user expectations.

44
Table 3.1
Billing System
Billing Formula of BMPC
If usage is 0 to 5 cubic meters, the bill is a flat rate of PHP 85.0.
If usage is 6 to 10 cubic meters, the bill is PHP 85.0 (base rate for the first 5
cubic meters) plus PHP 18.0 per cubic meter for the additional usage beyond 5
cubic meters.
????????????&#3627408479;&#3627408474;??????&#3627408473;??????: 85 ÷(??????&#3627408480;??????????????????−5)×18
If usage is 11 to 20 cubic meters, the bill is PHP 175.0 (base rate for the first 10
cubic meters, which is 85.0 + 5 * 18.0) plus PHP 19.5 per cubic meter for the
additional usage beyond 10 cubic meters.
????????????&#3627408479;&#3627408474;??????&#3627408473;??????: 175 ÷(??????&#3627408480;??????????????????−10)×19.5
If usage is above 20 cubic meters, the bill is PHP 370.0 (base rate for the first 20
cubic meters, which is 175.0 + 10 * 19.5) plus PHP 20.0 per cubic meter for the
additional usage beyond 20 cubic meters.
????????????&#3627408479;&#3627408474;??????&#3627408473;??????: 370 ÷(??????&#3627408480;??????????????????−20)×20
Reminder: When the bill has a decimal point of PHP 0.50, it will be rounded up
to PHP 1. This is a protocol of the BMPC's billing system formulation.
Table 3.1 represents the formula of billing that’s been used in BMPC. This
is an important formula to make the creation of a bill.

45
Table 3.2
Accuracy of calculating water consumption
Trial No. Previous
(mᵌ)
Present
(mᵌ)
Actual
( (PHP)
Manual
(PHP)
%Difference Remark

9366.0 mᵌ

9371.0 mᵌ 85 85 0 Passed
467.0 mᵌ 587.0 mᵌ 2370
= 2370
0 Passed

2252.0 mᵌ 2263.0 mᵌ 195
= 195
0 Passed

46

2252.0 mᵌ 2263.0 mᵌ 195
= 195
0 Passed

4344.0 mᵌ 4364.0 mᵌ 370
= 370
0 Passed

465.0 mᵌ 501.0 mᵌ 690
= 690
0 Passed

47

5429.0 mᵌ 5434.0 mᵌ 85 85 0 Passed

59.0 mᵌ 79.0 mᵌ 370
= 370
0 Passed

3559.0 mᵌ 3573.0
mᵌ
253
= 253
0 Passed

48

9578.0 mᵌ 9626.0 mᵌ 930
= 930
0 Passed
Table 3.2 presents data from ten trials comparing automatic and manual
computations, likely for volume measurements in cubic meters (m³). Each trial
includes columns for "Previews m³," "Present m³," "Actual," "Manual,"
"%Difference," and "Remark," with all trials showing a 0% difference and marked
as "Passed," indicating a strict pass/fail criterion requiring exact equivalence
between automatic (actual) and manual computation results. The researchers
sought researches on how percentage differences determine pass/fail outcomes
in such comparisons. Research on automatic versus manual computation often
used tolerance levels to define pass/fail criteria, but percentage-based thresholds
were more common in fields like engineering or quality control. In engineering, the
(University of Sussex, 2023) suggested that percentage tolerances, typically
ranging from ±5% to ±10%, are used in quality control for measurements like
volume, where deviations within this range are often deemed acceptable. Similarly,
(MoodleDocs, 2023) indicated that educational assessment systems may apply
percentage-based tolerances, such as ±5% or ±10%, for grading numerical
answers, with deviations within these limits considered "passed". The trials’ 0%
difference suggested a high-precision context, likely in engineering or quality
assurance, where no deviation is tolerated, stricter than the typical ±5% to ±10%
found in related research.

49
Table 3.3
Sample Receipt
Digital Copy Printed Copy

Based on Table 3.3 and the technical documentation, the printing system
for the wireless water meter reading system was designed to ensure consistency
between digital and physical billing statements through carefully configured
thermal printing specifications. The system utilized a 58mm thermal printer
integrated into the Senraise Android 14 Bluetooth Smart POS Machine, which
operates at a printing speed of 80mm/s to ensure rapid receipt generation for field
operations. The font size is 12x24 dots or 1.5 x 3.0 mm. This size of font was
almost in all 58mm printers, which is capable of delivering acceptable printed result

50
(Top Printer Thermal 58mm Factory for Store | Xprinter, 2025). The formatting
specifications were programmed directly within the Kotlin-based Android
application, where the receipt template was structured to accommodate the narrow
58mm paper width while maintaining readability and professional appearance. The
print format configuration was embedded in the application's receipt generation
module, which created formatted text strings that included bold sections for critical
billing information such as the total amount due and after-due penalties. The
system automatically adjusts font sizing and spacing to optimize readability on the
thermal paper's limited width, with larger text reserved for essential billing amounts
and smaller text used for detailed consumption data and cooperative information.
Line spacing was programmed to prevent text crowding while conserving thermal
paper, and the receipt included clear sectional breaks between different
information categories such as customer details, consumption readings, and billing
calculations. The thermal printing technology eliminated the need for ink
cartridges, making it ideal for field operations, while the 203 DPI (dots per inch)
resolution ensured crisp text reproduction even for detailed billing information. The
formatting system also incorporated automatic paper detection and low-paper
alerts, preventing incomplete receipts and ensuring continuous operation during
busy billing periods, with the entire printing process triggered seamlessly after
each successful reading submission to provide immediate receipt generation for
customer transparency and record-keeping.

51
Table 3.4
Functionality of updating the database
Trial # POS Database Remark

1

Passed

2

Passed

3

Passed

52

4

Passed

5

Passed

6

Passed

53

7

Passed

8

Passed

9

Passed

54

10

Passed

Table 3.4 shows modern application development. Devices often leverage
cloud-based services like Google Sheets to manage data through APIs, enabling
seamless integration for tasks such as real-time data logging, e-commerce
tracking, or automated reporting (Google, 2024). The Google Sheets API facilitates
these interactions, making latency—the time taken for a request to travel from the
device to the cloud server and back (round-trip time)—a critical performance factor.
Based on industry standards, developer community insights, and Google’s API
performance guidelines, this response establishes that a latency of under 5
seconds is considered a "passed" delay, while a latency of 5 seconds or more is
deemed a "failed" (Apigee, 2022; Stack Overflow, 2020; Zapier Community, 2024).
These thresholds provide a practical benchmark for developers building Excel-
based or Google Sheets-integrated applications, ensuring responsiveness and
efficiency.

55
3.3. Evaluation of the Study
A comprehensive questionnaire was distributed to the individuals who
played a role in the development and implementation of the Wireless Water Meter
Reading system at Bolo Multipurpose Cooperative. The participants were asked
to evaluate the system’s performance by rating its key characteristics on a Likert
scale below (Likert Four-Point Scale Range Interpretation, 2020):
Table 3.5
Likert Four-Point Scale Range Interpretation
POINT SCALE RANGE EXPLANATION
4 4.00 – 3.00 Strongly Agree
3 2.99 – 2.00 Agree
2 1.99 – 1.00 Disagree
1 1.00 – 0.99 Strongly Disagree
A total of 45 respondents completed the questionnaire, providing valuable
feedback. This group consisted of four employees and one manager from the Bolo
Multipurpose Cooperative, who were involved in the system’s operations and
management, as well as 40 community members who interacted with the system
as end-users. These respondents assessed the Wireless Water Meter Reading
System based on four critical characteristics: Functional Stability, which measured
the system’s consistency and accuracy in performing its intended tasks; Reliability,
which evaluated the system’s ability to operate dependably over time without
failures; Security, which focused on the system’s safeguards against unauthorized
access and data breaches; and Maintainability, which gauged the ease with which
the system could be updated, repaired, or modified to meet ongoing needs. The

56
varied perspectives from employees, management, and community members
provided a comprehensive evaluation of the system’s overall performance.
Table 3.6
Evaluation of Functional Stability
Functional Stability Mean Verbal
Interpretation
● The system makes it easy to access accurate water
consumption data, whether through the device interface
(for employees) or billing statements (for customers).
3.97 Strongly Agree
● The system produces clear and correct billing information
that is easy to understand and use for both employees
and customers.
3.86 Strongly Agree
● The system’s interface (for employees) and billing outputs
(for customers) are user-friendly and meet my
expectations for managing water usage data.
3.75 Strongly Agree
● The system efficiently handles tasks like data entry or bill
generation (for employees) and provides timely billing
information (for customers).
3.82 Strongly Agree
● The system supports smooth operations for adding new
customers, ensuring consistent service for both
employees and customers.
3.87 Strongly Agree
Weighted Mean 3.86
4.00 – 3.00 (Strongly Agree), 2.99 – 2.00 (Agree), 1.99 – 1.00 (Disagree), 1.00 – 0.99 (Strongly Disagree)

57
Table 3.6 presents a comprehensive assessment of functional stability,
derived from user feedback, with a total weighted mean of 3.85, indicating strong
agreement among respondents regarding the system's performance. This high
score reflected a robust and reliable system that met user expectations across
multiple dimensions. Specifically, access to accurate water consumption data
received an impressive rating of 3.97, underscoring the system's exceptional
efficacy in delivering precise and reliable data to users. This high rating suggested
that the system consistently provided accurate information, enabling users to
monitor their water usage effectively and make informed decisions.
The clarity of data presented in billing statements was rated at 3.86,
demonstrating a notable level of user satisfaction with transparency and
comprehensibility. This score indicated that users found the billed data clear, well-
organized, and easy to understand. Meanwhile, the user-friendly interface of the
system was rated at 3.75.
Task handling efficiency, which measured the system's ability to process
and manage tasks effectively, achieved a rating of 3.82. This score highlighted the
system's strong operational performance, indicating that it handled tasks promptly
and accurately, contributing to overall user satisfaction. Additionally, the system's
support for onboarding new customers was rated at 3.87, reflecting its robust
capability to attract and integrate new users seamlessly.
Overall, the results showed a high level of user satisfaction with the
system's performance across key functional areas. The consistently high ratings
across various metrics demonstrated that the system was not only reliable and
efficient but also user-centric, meeting the needs of its users effectively. These
findings suggested that the system was well-positioned to maintain user trust and
operational excellence, with minor refinements potentially enhancing its already
strong performance further.

58
Table 3.7
Evaluation of Reliability
Reliability Mean Verbal
Interpretation
● The system consistently provides accurate water
usage data without errors, whether for data entry
(employees) or billing (customers).
3.93 Strongly Agree
● The system performs reliably during busy periods,
ensuring no delays in data processing (for employees)
or billing delivery (for customers).
3.88 Strongly Agree
● The system maintains stable operation, preventing
disruptions in data collection (for employees) or service
delivery (for customers).
3.88 Strongly Agree
● The system ensures that water usage data is
dependable, reducing the need for corrections by
employees or disputes from customers.
3.87 Strongly Agree
● The system quickly recovers from any technical issues,
ensuring continuous access to data or services for both
employees and customers.
3.84

Strongly Agree
Weighted Mean 3.88

4.00 – 3.00 (Strongly Agree), 2.99 – 2.00 (Agree), 1.99 – 1.00 (Disagree), 1.00 – 0.99 (Strongly Disagree)

59
Table 3.7 provides a comprehensive evaluation of the system's reliability,
yielding a total weighted mean of 3.88, which reflected a strong level of agreement
among respondents regarding the system's performance. This high score
underscored the system's ability to consistently meet user expectations across
various operational dimensions. Specifically, the system's capability to deliver
accurate water usage information with no errors was rated at 3.93, highlighting an
exceptional level of performance in maintaining data integrity.
Furthermore, the system's reliability during peak usage periods and its
ability to maintain stable operation under demanding conditions also received a
weighted mean score of 3.88. This indicated robust performance, even when the
system was subjected to high demand or stress, ensuring uninterrupted service
delivery. The reliability of water use data, a key metric for evaluating the system's
consistency in providing dependable information, was rated at 3.87, further
reinforcing the system's dependability. Additionally, the system's capacity for rapid
recovery from technical issues was scored at 3.84, suggesting that while the
system was highly resilient, there was slight room for improvement in minimizing
downtime or enhancing recovery processes.
Overall, as summarized in Table 3.9, the system demonstrated an
exceptionally high level of reliability, as evidenced by the consistent weighted
mean of 3.88 across all evaluated characteristics. This strong agreement among
respondents reflected high user trust in the system's performance, stability, and
accuracy. The data collectively indicated that the system operated with a high
degree of dependability, fostering confidence among users and supporting its
effectiveness in delivering reliable water usage information. These findings
suggested that while the system performed at a near-optimal level, minor
adjustments could further enhance its recovery mechanisms, ensuring even
greater reliability in the future.

60
Table 3.8
Evaluation of Security
Security Mean Verbal
Interpretation
● The system keeps water usage and billing data
secure, giving me confidence in its safety (for
employees and for customers).
3.91 Strongly Agree
● The system prevents unauthorized access to
sensitive information, ensuring privacy for both
employees and customers.
3.91 Strongly Agree
● The system securely records all transactions,
providing assurance that data is accurate and
tamper-proof for both employees and customers.
3.93 Strongly Agree
● The system uses reliable methods (e.g.,
encryption) to protect data during transmission,
ensuring trust in its operations for both employees
and customers.
3.97 Strongly Agree
● The system feels safe from cyber threats,
protecting the information I interact with as an
employee or customer.
3.97 Strongly Agree
Weighted Mean 3.94

4.00 – 3.00 (Strongly Agree), 2.99 – 2.00 (Agree), 1.99 – 1.00 (Disagree), 1.00 – 0.99 (Strongly Disagree)

61
Table 3.8 provides a comprehensive assessment of the system's security
features, yielding an overall weighted mean of 3.94, which reflected a strong
consensus among respondents regarding the system's robust security
performance. Specifically, the system's capability to prevent unauthorized access
to sensitive information was rated at 3.91, demonstrating a high level of confidence
in its ability to safeguard critical data. Similarly, the secure recording of all
transactions received a rating of 3.93, further underscoring the system's
effectiveness in maintaining data privacy and integrity across all operations.
In terms of encryption and cybersecurity, the use of reliable encryption
methods to protect data during transmission was rated at 3.97, indicating
exceptional performance in securing data as it moved through the system.
Additionally, respondents expressed a high level of confidence in the system’s
protection against cyber threats, also rating this aspect at 3.97, which reflected a
strong sense of overall cyber safety. The security of water usage and billing data,
a critical component for user trust, was rated at 3.91, reinforcing the system's ability
to protect sensitive user information effectively.
As summarized in Table 3.10, the system demonstrated an exceptionally
high level of security, with the overall weighted mean of 3.94 reflecting consistent
agreement across all evaluated security characteristics. This high rating across
multiple dimensions highlighted the system's robust design and its ability to foster
significant user trust in its data protection capabilities. The results suggested that
respondents perceived the system as highly reliable, secure, and effective in
safeguarding sensitive information, thereby enhancing confidence in its overall
performance.

62
Table 3.9
Evaluation of Maintainability
Maintainability Mean Verbal
Interpretation
● The system is easy to update, ensuring it remains
effective for data management (for employees)
and billing services (for customers).
3.91 Strongly Agree
● The system’s maintenance does not cause
significant disruptions to my work (for employees)
or service experience (for customers).
3.95 Strongly Agree
● The system provides clear feedback or alerts about
issues, making it easier to keep it running smoothly
for both employees and customers.
3.93 Strongly Agree
● The system is designed to adapt to changes (e.g.,
new billing rates), ensuring reliable performance
for employees and customers.
3.91 Strongly Agree
● The system’s upkeep is straightforward, supporting
consistent operations for employees and
uninterrupted services for customers.
3.95 Strongly Agree
Weighted Mean 3.93

Table 3.9 analyzes system maintainability and identified a total weighted
mean of 3.93, indicating general agreement among respondents. The system's
4.00 – 3.00 (Strongly Agree), 2.99 – 2.00 (Agree), 1.99 – 1.00 (Disagree), 1.00 – 0.99 (Strongly Disagree)

63
ability to be easily updated was rated at 3.91, while its ease of maintenance to
sustain integrity and dependent operations received a high rating of 3.95. The
system's maintenance did not materially disrupt its operational state, also rated at
3.95, and its ability to submit clear feedback or alerts to indicate issues was rated
at 3.93. These ratings reflected very good performance in limiting work disruptions
and ensuring acceptable performance quality. The system's design to adjust to
change was also rated as very good, with a score of 3.91. Overall, the results were
well-regarded and demonstrated strong maintainability across all evaluated
aspects..
Table 3.10
Summary Results of the System
Table 3.10 summarized the system evaluation, which received "Strongly
Agree" feedback across all assessed criteria. Functional Stability, Reliability,
Security, and Maintainability all received a "Strongly Agree" verbal interpretation,
with weighted averages of 3.90. This indicated that the system was perceived as
highly stable, reliable, secure, and easy to maintain.
Criteria Weighted Mean Verbal Interpretation
Functional Stability 3.85 Strongly Agree
Reliability 3.88 Strongly Agree
Security 3.94 Strongly Agree
Maintainability 3.93 Strongly Agree
Weighted Average 3.9 Strongly Agree
4.00 – 3.00 (Strongly Agree), 2.99 – 2.00 (Agree), 1.99 – 1.00 (Disagree), 1.00 – 0.99 (Strongly Disagree)

64
4.0 CONCLUSIONS AND DIRECTIONS FOR FUTURE USE
The wireless water meter reading system developed for the Bolo Multipurpose
Cooperative (BMPC) effectively addressed the inefficiencies of manual meter
reading and billing processes. Through its design, testing, and evaluation phases,
the system demonstrated significant improvements in accuracy, efficiency, and
customer satisfaction. The following conclusions aligned with the study's
objectives, highlighting the system's performance and its potential for enhancing
water utility management.
1. The system successfully met its objective to design and implement a
solution that calculated accurate water consumption, printed precise billing
statements, and updated the database in real time. Integrated with an
Android-based Point of Sale (POS) device, it accurately measured water
usage in cubic meters, eliminating errors inherent in manual data collection.
Real-time data transmission to a cloud server ensured prompt database
updates, while an offline notepad feature maintained functionality during
connectivity disruptions, making it ideal for rural settings like Bolo, Bauan,
Batangas.
2. The system was rigorously tested for accuracy, reliability, and functionality,
confirming its effectiveness. It consistently calculated water consumption
with zero discrepancies, reducing the need for corrections and fostering
trust in billing accuracy. The system’s real-time database updates
performed reliably during peak usage demands and maintained an
acceptable delay of 1–2 seconds.
3. The system was evaluated for functional suitability, reliability, security, and
maintainability, yielding positive results. With a weighted mean of 3.85 for
functional suitability, users found the interface intuitive and billing outputs
transparent. Reliability scored 3.88, indicating consistent performance with
minimal disruptions. Security, with a mean of 4.00, instilled confidence

65
through encryption and secure transaction recording, though ongoing
vigilance was recommended for cloud-based storage. Maintainability, at
3.93, reflected the system’s ease of updates and adaptability, ensuring
long-term sustainability.
To further enhance the system’s impact and ensure its long-term success,
the following recommendations are proposed for future development and
implementation:
1. Cross-Platform Compatibility: The current system is limited to Android,
restricting its accessibility on other operating systems like iOS or Windows. Future
iterations should explore Kotlin Multiplatform or cross-platform frameworks to
develop applications compatible with multiple devices, increasing accessibility for
BMPC employees and potentially enabling customer-facing apps for broader
engagement.
2. Advanced Analytics and Reporting: Integrating advanced analytics tools, such
as predictive models for water consumption trends or leak detection algorithms,
can enhance the system’s value. These features provide BMPC with actionable
insights for resource allocation and infrastructure maintenance, while customers
benefit from personalized usage reports to promote water conservation.
3. User Interface Improvements: User feedback highlights minor suggestions, such
as larger print sizes on receipts and improved thermal paper quality. Future
updates should incorporate these enhancements, along with customizable
interface options to improve accessibility for diverse users, including those with
visual impairments or non-English speakers.

66
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Technology (IJERT), 9(5), 733-737. http://www.ijert.org/smart-water-meter-
monitoring-system
Suddia, A., & Suddia, A. (2024, October 23). What Are the Best Programming
Languages for Mobile App Development? IT Craft’s Quick Guide to
Language Evaluation. IT Craft. https://itechcraft.com/blog/best-
programming-languages-for-mobile-app-development/
SWM Editorial Team. (2024, May 23). What is Smart Water Metering? Smart
Water Magazine. https://smartwatermagazine.com/q-a/what-smart-water-
metering.

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Taggle Systems. (2024). Aqualus Water: Advanced smart metering for water
utilities. Taggle Systems. Retrieved from https://www.taggle.com
10 Things Wrong with Tenant Submetering (And How to Fix Them) | Enertiv. (2024,
December 7). https://tinyurl.com/35x9ttyp.
Tapanm-Msft. (2024, August 7). What is Power Apps? - Power Apps. Microsoft
Learn. https://learn.microsoft.com/en-us/power-apps/powerapps-overview
Teddlie, C., & Tashakkori, A. (2020). Foundations of mixed methods research:
Integrating quantitative and qualitative approaches in the social and
behavioral sciences (2nd ed.). SAGE Publications.
top printer thermal 58mm factory for store | Xprinter . (2025).
https://www.xprintertech.com/top-printer-thermal-58mm-factory-for-store

Traditional water meters. (2024, May 3). Watertech.
https://wtmeters.it/en/traditional-water-meters/.
University of Sussex. (2023). Measurement uncertainty. University of Sussex.
https://users.sussex.ac.uk[](https://www.ukas.com/training-and-
advisory/training/courses/measurement-uncertainty-practitioners/)
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72
Appendix A
Sample Questionnaire

73

74

75

76

77
Appendix B
Certificate of Research Instrument Validation

78
Appendix C
Summary of Questionnaire Response
Street Customer Employees Manager
Legaspi 10 0 1
Rizal 10 1 0
Balintawak 6 1 0
Gen. Luna 9 2 0
Manigbas 5 0 0
Total 40 4 1

79
4 – Strongly Agree; 3 – Agree; 2 – Disagree; 1 – Strongly Disagree
Characteristic 4 3 2 1
Functional Stability
● The system makes it easy to access accurate water
consumption data, whether through the device
interface (for employees) or billing statements (for
customers)
44 1
● The system produces clear and correct billing
information that is easy to understand and use for both
employees and customers.
39 6
● The system’s interface (for employees) and billing
outputs (for customers) are user-friendly and meet my
expectations for managing water usage data.
34 11
● The system efficiently handles tasks like data entry or
bill generation (for employees) and provides timely
billing information (for customers).
37 8
● The system supports smooth operations for adding
new customers, ensuring consistent service for both
employees and customers.
39 6
Weighted Mean 3.85

Reliability

80
● The system consistently provides accurate water
usage data without errors, whether for data entry
(employees) or billing (customers).
42 3
● The system performs reliably during busy periods,
ensuring no delays in data processing (for employees)
or billing delivery (for customers).
40 5
● The system maintains stable operation, preventing
disruptions in data collection (for employees) or service
delivery (for customers).
40 5
● The system ensures that water usage data is
dependable, reducing the need for corrections by
employees or disputes from customers.
39 6
● The system quickly recovers from any technical issues,
ensuring continuous access to data or services for both
employees and customers.
38 7
Weighted Mean 3.88

Security
● The system keeps water usage and billing data secure,
giving me confidence in its safety (for employees
handling data, for customers receiving bills).
41 4

81
● The system prevents unauthorized access to sensitive
information, ensuring privacy for both employees and
customers.
41 4
● The system securely records all transactions, providing
assurance that data is accurate and tamper-proof for
both employees and customers.
42 3
● The system uses reliable methods (e.g., encryption) to
protect data during transmission, ensuring trust in its
operations for both employees and customers.
44 1
● The system feels safe from cyber threats, protecting
the information I interact with as an employee or
customer.
44 1
Weighted Mean 3.94

Maintainability
● The system is easy to update, ensuring it remains
effective for data management (for employees) and
billing services (for customers).
41 4
● The system’s maintenance does not cause significant
disruptions to my work (for employees) or service
experience (for customers).
43 2

82

● The system provides clear feedback or alerts about
issues, making it easier to keep it running smoothly for
both employees and customers.
42 3
● The system is designed to adapt to changes (e.g., new
billing rates), ensuring reliable performance for
employees and customers.
41 4
● The system’s upkeep is straightforward, supporting
consistent operations for employees and uninterrupted
services for customers.
43 2
Weighted Mean 3.93
Comments/ Suggestions
1.Make the prints bigger. Make bigger space between the total amount to be
paid for the billing period and the total amount to be paid after the due date to
avoid confusion.
2. Improve the size and quality of thermal paper.

83
Appendix D
CONSENT LETTER

84
Appendix E
Certificate of Implementation

85
Appendix F
Bill of Materials
Materials Cost (PHP)
POS Device 8,000
Software Program 0
Thermal Papers 200
TOTAL 8,200

86
Appendix F
User’s Manual

BMPC Water Meter App User Manual
April 13, 2025

87
Table of Contents
The BMPC Water Meter App connects to a Google Sheets backend to store and
retrieve customer data, including meter readings, usage, and billing information.
It supports both online and offline modes, allowing meter readers to work
seamlessly in areas with limited connectivity. Key features include:
● Customer verification
● Reading submission with automatic billing calculations
● Receipt printing
● Customer search and list views
● Notepad for notes
● History tracking
● Data backup to Google Sheets

1. Introduction
The BMPC Water Meter App is designed for the Bolo Multipurpose Cooperative
to manage water meter readings, generate bills, and maintain customer records
efficiently. This manual provides step-by-step instructions for using the app’s
features, including submitting readings, printing receipts, searching customers,
viewing history, and more.

2. Getting Started

2.1 Installation
- Device Requirements:
- Android device running Android 10 (API level 29) or higher.
- Internet connection for initial setup and data syncing (Wi-Fi or mobile data).
- Steps:

88
1. Download the APK file from the provided source (e.g., cooperative’s server or
email).
2. Enable “Install from Unknown Sources” in your device settings if prompted.
3. Install the app by opening the APK file and following the on-screen
instructions.
- Launch the App:
- Locate the “BWSC App” icon on your home screen or app drawer.
- Tap to open.

2.2 Permissions
The app requires the following permissions:
- Internet: To sync data with Google Sheets.
- Network State: To check connectivity status.
Grant these permissions when prompted during the first launch.

3. Main Interface
Upon launching, the main screen displays the following elements:
- Month Spinner: Select the billing month (January to December).
- Customer ID Field: Enter the customer’s ID.
- Verify Customer Button: Validates the entered ID.
- Customer Name Display: Shows the verified customer’s name.
- Previous Month Reading Display: Shows the last recorded reading (if available).
- Previous Reading Field: Optional field to override the previous reading.
- Present Reading Field: Enter the current meter reading.
- Street Spinner: Select the customer’s street (e.g., Rizal 1, Legaspi 2).

89
- Remarks Field: Add optional notes (e.g., meter issues).
- Submit Button: Submits the reading and generates a bill.
- Backup Button: Opens the Google Sheet in a browser for manual download.
- Print Button: Prints the last generated receipt (disabled until a reading is
submitted).
- Last Customer ID Display: Shows the most recently processed customer ID.
- Notepad Button: Opens a note-taking dialog.
- Search Button: Searches customers by name.
- List Button: Displays the customer list for the selected street.
- History Button: Shows the daily reading history.

4. Core Features

4.1 Selecting Street and Month
1. Choose a Street:
- Tap the Street Spinner.
- Select a street (e.g., “Rizal 1”, “Manigbas”).
- The app fetches customer IDs for the selected street (requires internet for the
first fetch).
2. Choose a Month:
- Tap the Month Spinner.
- Select the current billing month (e.g., “October”).
- The app adjusts the Google Sheet to show relevant columns for the selected
month and street.
3. Notes:
- Both selections are required before entering customer data.

90
- If offline, the app uses cached data if available.

4.2 Verifying Customer ID
1. Enter Customer ID:
- Input the customer’s ID (e.g., “123A”) in the Customer ID Field.
2. Verify:
- Tap Verify Customer.
- If online, the app checks the ID against the Google Sheet for the selected
street.
- If offline, it checks against cached IDs.
3. Result:
- Valid ID: Displays the customer’s name and previous month’s reading (if
available).
- Invalid ID: Shows “Customer Name: Not Found” and a toast message
prompting for a valid ID.
4. Auto-Fill Next ID:
- After submitting a reading, the app suggests the next ID based on the sorted
list for the street.

4.3 Entering Readings
1. Previous Reading:
- The Previous Month Reading Display shows the last recorded reading
(fetched from the Google Sheet).
- Optionally, enter a value in the Previous Reading Field to override it (e.g., for
corrections).
- If left empty, the app uses the fetched value or 0.0 if none exists.
2. Present Reading:

91
- Enter the current meter reading (in cubic meters) in the Present Reading
Field.
- Use decimal points for precision (e.g., “123.5”).
3. Remarks:
- Add optional notes in the Remarks Field (e.g., “Leaky pipe reported”).
4. Validation:
- The present reading must be greater than or equal to the previous reading.
- If invalid, a toast message appears (e.g., “Present reading cannot be less
than previous reading”).

4.4 Submitting Readings
1. Submit:
- Tap Submit Reading after entering all required fields (Customer ID, Present
Reading, Street, Month).
- The app calculates:
- Usage: Present Reading - Previous Reading.
- Bill:
- ≤ 5 m³: PHP 85
- 6–10 m³: PHP 85 + (extra units × PHP 18)
- 11–20 m³: PHP 175 + (extra units × PHP 19.5)
- > 20 m³: PHP 370 + (extra units × PHP 20)
- After Due: Bill + 15% penalty.
- Due Date: 25th of the next month.
2. Online Submission:
- Sends data to Google Sheets (Customer ID, Name, Readings, Usage, Bill,
Timestamp, Remarks).

92
- Clears input fields and auto-fills the next Customer ID.
- Enables the Print Button.
3. Offline Submission:
- Stores data locally in Pending Submissions.
- Syncs automatically when internet is restored.
4. Feedback:
- Success: “Data updated in Google Sheets”.
- Error: “Failed to send data. Will retry when online.”

4.5 Printing Receipts
1. Generate Receipt:
- After submitting a reading, the Print Button becomes active.
- Tap Print to generate a receipt with:
- Cooperative details (name, address, contact).
- Customer details (ID, Name, Street, Month, Remarks, Due Date).
- Reading details (Previous, Present, Usage).
- Billing details (Bill, After Due, Garbage Cost range).
2. Printer Setup:
- Ensure a compatible printer (e.g., thermal printer) is connected via USB,
Bluetooth, or Wi-Fi.
- The app formats the receipt for a 58mm paper width at 203 DPI.
3. Reprint:
- Use the Print Button to reprint the last receipt.
- Alternatively, use History or Search to reprint older receipts (see below).

93
4.6 Viewing Customer List
1. Access:
- Select a Street and Month.
- Tap List.
2. Display:
- Shows all customers for the selected street in a paginated dialog (15 entries
per page).
- Green text indicates customers with readings for the selected month.
- Red text indicates no readings.
- Sorted numerically and alphabetically (e.g., “1”, “2”, “12A”, “12B”).
3. Navigation:
- Use Next and Previous buttons to flip pages.
- Tap OK to close.
4. Notes:
- Requires internet to fetch the latest data.
- Shows a progress dialog while loading.

4.7 Searching Customers
1. Access:
- Select a Street and Month.
- Tap Search.
2. Search Dialog:
- Enter a customer’s name in the AutoCompleteTextView.
- Suggestions appear as you type (threshold: 1 character).
3. Result:

94
- If found, prints a receipt with the customer’s latest reading for the selected
month.
- If not found, shows “No customer found with name [name] in [street]”.
4. Notes:
- Case-insensitive search.
- Requires internet.

4.8 Using Notepad
1. Access:
- Tap Notepad.
2. Features:
- Opens a multi-line text editor for notes (e.g., reminders, meter issues).
- Pre-filled with previously saved content.
3. Save:
- Edit the text and tap Save.
- Saved to local storage (persists across app restarts).
4. Cancel:
- Tap Cancel to discard changes.

4.9 Viewing History
1. Access:
- Tap History.
2. Display:
- Shows a list of customers processed today (Customer ID and Name).
- Stored locally and resets daily.

95
3. Reprint:
- Tap a customer’s entry to reprint their receipt for the selected street and
month.
4. Notes:
- Requires a selected Street and Month to fetch receipt data.
- If no readings exist for the day, displays “No readings today”.

4.10 Backing Up Data
1. Access:
- Tap Backup.
2. Action:
- Opens the Google Sheet in your default browser.
- Manually download the sheet as an Excel file or other format from Google
Sheets.
3. Notes:
- Requires internet.
- If the browser fails to open, a toast message shows the error.

5. Offline Mode
- Availability:
- The app works offline using cached customer IDs and pending submissions.
- Features:
- Verify Customer ID (checks cached IDs).
- Submit Readings (stores locally).
- View Notepad and History.

96
- Limitations:
- Cannot fetch new customer data or previous readings.
- Cannot view Customer List or Search.
- Backup requires internet.
- Syncing:
- When internet is restored, pending submissions sync automatically.
- Monitor toast messages for sync status (e.g., “Synced pending data to Google
Sheets”).

6. Troubleshooting

For persistent issues, contact the cooperative’s IT support with:
- Device model and Android version.

97
- Error messages or screenshots.
- Description of the problem.

7. Glossary
- Customer ID: Unique identifier for a customer (e.g., “123A”).
- Street: Customer’s location (e.g., “Rizal 1”).
- Previous Reading: Meter reading from the prior month (in cubic meters).
- Present Reading: Current meter reading (in cubic meters).
- Usage: Difference between Present and Previous Readings.
- Bill: Calculated cost based on usage tiers.
- After Due: Bill plus 15% penalty if paid after the due date.
- Remarks: Optional notes for meter issues or customer status.
- Google Sheets: Backend storage for all customer and reading data.
- Pending Submissions: Readings stored locally when offline, synced later.
- Cached Data: Locally stored customer IDs for offline verification.

98

BWSC Google Sheets Manual
April 13, 2025

99
1. Introduction
The BWSC Google Sheets backend stores and manages water meter data for
the Bolo Multipurpose Cooperative’s Water Meter App. As the Google Sheets
manager, your role is to maintain the spreadsheet, ensure data accuracy,
monitor app interactions, and troubleshoot issues. This manual explains the
sheet structure, Apps Script functionality, and best practices for managing the
backend.

2. Getting Started

2.1 Accessing the Spreadsheet
- URL: The primary spreadsheet is located at
https://docs.google.com/spreadsheets/d/1S9RLnZjK5POmS9x8l9YSrCZnHtYl5gr
A7lajNB7HCB0/edit?gid=0#gid=0.
- Permissions:
- Ensure you have “Editor” access. Contact the cooperative’s IT administrator if
you lack permission.
- The Apps Script (linked to the sheet) requires “Run” permissions for the app to
function.
- Steps:
1. Open the URL in a web browser.
2. Sign in with your Google account.
3. Verify access by editing a cell (e.g., type “Test” and delete it).

2.2 Understanding the Apps Script
- Location: Access the script via Extensions > Apps Script in Google Sheets.
- Purpose: The script handles data requests from the BWSC app, including
fetching customer IDs, retrieving readings, updating records, and hiding columns.

100
- Do Not Modify: Unless you’re trained in JavaScript/Google Apps Script, avoid
editing the script to prevent breaking app functionality.
- Deployment: The script is deployed as a web app at
NOTE: ONLY FOR DEVELOPERS OF APP
https://script.google.com/macros/s/AKfycbx1x-SxG-
vVPB4jEhcced5Gh0viGH_MS131STwZDkKFlWyf94IVg3Gmc60mC33GFHWX/e
xec.

3. Spreadsheet Structure

3.1 Overview
The spreadsheet contains one sheet per street, with data organized by customer
and month. Below is the structure for each sheet:

Column Description
A Customer ID (unique, e.g., “123A”)
B Customer Name (e.g., “Juan Dela
Cruz”)
C Meter Number (optional, unique
identifier for the meter)
D onwards Month-specific data (6 columns per
month: Previous Reading, Present
Reading, Usage, Bill, Timestamp,
Remarks)

3.2 Sheets
- Sheets (one per street): Rizal 1, Rizal 2, Manigbas, Legaspi 1, Legaspi 2, Gen
Luna 1, Gen Luna 2, Balintawak.
- Rows: Each row after the header represents a customer.

101
- Columns: Fixed columns (A–C), followed by 6 columns per month (January to
December).

3.3 Month Columns
Each month occupies 6 columns, starting from column D:
- Example for January (columns D–I):
- D: Previous Reading (m³)
- E: Present Reading (m³)
- F: Usage (m³, calculated as Present - Previous)
- G: Bill (PHP, based on usage tiers)
- H: Timestamp (e.g., “2025-04-13 14:30:00”)
- I: Remarks (e.g., “Meter replaced”)
- Subsequent months follow (e.g., February: J–O, March: P–U).

3.4 Data Validation
- Customer ID: Must be unique within a street.
- Readings: Numeric, non-negative. Present Reading ≥ Previous Reading.
- Bill: Calculated by the app (see Section 4.3).
- Timestamp: Auto-generated by the app in “YYYY-MM-DD HH:MM:SS” format.
- Remarks: Optional text.

4. Managing Data

4.1 Adding Customers
1. Open the relevant street’s sheet (e.g., “Rizal 1”).

102
2. Add a new row at the bottom:
- Column A: Enter a unique Customer ID.
- Column B: Enter the customer’s full name.
- Column C: Enter the meter number (optional).
3. Leave month-specific columns blank until readings are submitted via the app.
4. Save changes (Google Sheets auto-saves).

4.2 Editing Customer Data
1. Locate the customer’s row using the Customer ID or Name.
2. Update fields as needed:
- Customer ID or Name: Ensure no duplicates.
- Meter Number: Update if the meter changes.
- Readings: Only edit if correcting app-submitted data (e.g., typo in Present
Reading).
3. Avoid editing Timestamp or Bill unless correcting errors, as these are app-
generated.

4.3 Verifying App Submissions
- The app submits:
- Previous Reading, Present Reading, Usage, Bill, Timestamp, Remarks.
- Bill calculation:
- ≤ 5 m³: PHP 85
- 6–10 m³: PHP 85 + (extra units × PHP 18)
- 11–20 m³: PHP 175 + (extra units × PHP 19.5)
- > 20 m³: PHP 370 + (extra units × PHP 20)
- Check for:

103
- Usage: Present Reading - Previous Reading.
- Bill: Matches the tiered calculation.
- Timestamp: Recent and correctly formatted.
- Remarks: Relevant and clear (e.g., “Leaky pipe”).
- Correct errors manually if needed (e.g., adjust Present Reading if misentered).

4.4 Hiding Columns
- Purpose: The app hides irrelevant month columns to simplify data entry (e.g.,
shows only October’s columns when October is selected).
- How It Works:
- The Apps Script automatically hides all columns after C and shows only the 6
columns for the selected month.
- Example: For October in “Rizal 1”, columns D–AN are hidden, and columns
AO–AT (October’s columns) are visible.
- Manual Adjustment:
- If columns are incorrectly hidden/shown, go to View > Hidden columns > Show
all.
- To hide manually, right-click column headers > Hide column.
- Note: The app triggers this via the hideColumnsForMonth function when a
street and month are selected.

4.5 Backing Up Data
1. Download a copy:
- File > Download > Microsoft Excel (.xlsx) or CSV.
- Save to a secure location (e.g., cooperative’s server or external drive).
2. Schedule regular backups (e.g., monthly) to prevent data loss.
3. Share backups with authorized personnel only.

104

4.6 Deleting Data
- Caution: Avoid deleting rows or columns unless absolutely necessary, as it may
disrupt app functionality.
- To delete a customer:
1. Verify the customer is no longer active.
2. Copy their row to a backup sheet (e.g., “Archived Customers”).
3. Delete the row from the street’s sheet.
- To clear old readings:
1. Back up the sheet.
2. Select the month’s columns (e.g., D–I for January).
3. Right-click > Clear content.

5. Monitoring Apps Script

5.1 Accessing Logs
1. Go to Extensions > Apps Script.
2. Click View > Logs.
3. Review entries for errors or actions (e.g., “Customer 123A not found”, “Data
updated successfully”).
4. Common logs:
- doGet: Handles app requests (e.g., fetch customer IDs).
- doPost: Handles data submissions (e.g., new readings).
- hideColumnsForMonth: Adjusts column visibility.

105
5.2 Checking Deployments
1. In Apps Script, click Deploy > Manage Deployments.
2. Verify the web app is active with the correct URL (matches the app’s sheetUrl).
3. If outdated, redeploy (Deploy > New Deployment > Web app > Execute as
“Me” > Access “Anyone”).

5.3 Handling Errors
- Common errors:
- “Sheet not found”: Ensure the street name matches exactly (e.g., “Rizal 1”, not
“rizal 1”).
- “Invalid month”: Month must be “January” to “December” (case-sensitive).
- “Customer not found”: Check the Customer ID in the sheet.
- Fix: Correct sheet names, month values, or customer data as needed.
- Notify IT if errors persist.

6. Best Practices
- Consistency: Use standardized formats for Customer IDs (e.g., “123A”) and
names (e.g., “Lastname, Firstname”).
- Validation: Double-check new entries for duplicates or typos.
- Access Control: Limit Editor access to trusted personnel. Use “Viewer” access
for others.
- Backup: Maintain weekly backups to avoid data loss.
- Communication: Coordinate with app users (meter readers) to resolve data
discrepancies.
- Documentation: Keep a log of manual changes (e.g., “Corrected reading for ID
123A on 2025-04-13”).

106
7. Troubleshooting

Issue Solution
“App cannot fetch customer IDs” Check sheet names (must match
“Rizal 1”, etc.). Verify Editor access for
the script’s Google account. Redeploy
the script if needed.
“Readings not appearing” Confirm the app’s month matches the
sheet’s month columns. Check Apps
Script logs for “doPost” errors. Ensure
internet connectivity on the app device.
“Columns not hiding correctly” Manually show all columns (View >
Hidden columns). Trigger hiding via the
app or run hideColumnsForMonth in
Apps Script with correct parameters.
“Duplicate customer IDs” Merge or delete duplicates. Update the
app’s cached IDs by clearing
SharedPreferences (advanced users).
“Incorrect bills” Verify Usage (Present - Previous) and
recalculate Bill per the tiered formula.
Correct manually if needed.
“Script timeout” Large datasets may cause delays. Split
sheets if exceeding Google Sheets
limits (e.g., 5 million cells). Contact IT
for optimization.
“Access denied” Ensure your account has Editor
access. Check Apps Script’s “Execute
as” setting (must be a valid Editor).

For persistent issues, contact the cooperative’s IT support with:
- Screenshot of the error or sheet.
- Apps Script logs (if applicable).
- Description of the issue and steps taken.

107
8. Glossary
- Customer ID: Unique identifier for a customer (e.g., “123A”).
- Street: Customer’s location (e.g., “Rizal 1”).
- Previous Reading: Meter reading from the prior month (m³).
- Present Reading: Current meter reading (m³).
- Usage: Present Reading - Previous Reading (m³).
- Bill: Calculated cost based on usage tiers (PHP).
- Timestamp: Date and time of submission (e.g., “2025-04-13 14:30:00”).
- Remarks: Notes about the meter or customer (e.g., “Leaky pipe”).
- Apps Script: Backend code handling app-sheet communication.
- Hidden Columns: Month columns not relevant to the app’s current selection.

108
Researcher’s Contact Information:
Caballero, Christian Villena
[email protected]
09957725946

Cusi, Jewelles Dannies Panganiban
[email protected]
09984868060

Dimacuha, Von Chester Cueto
[email protected]
09945674143

Dimaunahan, Yokimura
[email protected]
09955158438

Raca, Aleli Rose Magpantay
[email protected]
09109808922

Pesigan, Andrei Christopher Lubrico
[email protected]
09935002603

Design and Implementation of Wireless Water Meter Reading at Bolo Multipurpose Cooperative

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