Proposal_DUSENGIMANA_Claude_2305000936.pptx

PPt presentation for smart baby incubation using IOT

1. SMART BABY CARE INCUBATOR USING IoT MONITORING “ A CASE STUDY OF MUHIMA HOSPITAL ”  By Claude DUSENGIMANA Reg no: 2305000936

2. CONTENTS I. General Introduction II. problem statement III. General Objective IV. Specific Objectives V. Research Questions VI. Location of the study VII. Conceptual Framework VIII. Research Methodology IX. Target population X. EXISTING PROTOTYPE MODEL XI. PROPOSED PROTOTYPE MODEL xII. Conclusion

3. I. GENERAL INTRODUCTION The Smart Baby Care Incubator with IoT Monitoring project marks a significant advancement in newborn care. This new solution combines Internet of Things (IoT) technologies with traditional incubator operations to provide comprehensive newborn care. It constantly checks vital signs, automatically modifies the incubators the environment, and provides intelligent care reminders. Real-time vital sign tracking, automated environmental control, remote access for doctors and nurses, an easy-to-use interface, and a portable design are among its key features.

4. Imagined picture of a baby in an incubator with a GSM module and IoT.

5. II. PROBLEM STATEMENT Current incubators have severe limitations in providing the best treatment to vulnerable babies. -They frequently lack real-time monitoring capabilities, causing potential delays in recognizing significant changes in an infant's condition. -Manually adjusting the temperature and humidity takes time and is prone to error. -The absence of automatic warnings and reminders can lead to missed care treatments. - Limited remote monitoring might cause delays in specialist interventions, burden healthcare professionals, and have a poor influence on baby outcomes, particularly in limited resources situations.    

6. III. GENERAL OBJECTIVE -To create a smart baby care incubator that utilizes Internet of Things (IoT) technologies to improve newborn care and monitoring. - This system intends to provide real-time health tracking, automate incubator updates, and make important data easily accessible to both medical professionals and parents, thereby improving the quality and consistency of newborn care.

7. IV. SPECIFIC OBJECTIVES I. To create an IoT-enabled incubator system that includes sensors for vital sign monitoring . ii. Implement environmental control methods to precisely regulate temperature, humidity, and air quality . iii. To create real-time data collection and visualization tools for monitoring newborn status. iv. To set up monitoring and to notify the mother when it is time to breastfeed the baby, and when is crying out. Additionally, to notify when to change the baby’s diapers.

8. V. RESEARCH QUESTIONS I. What hardware components (sensors, microcontrollers, actuators) and software systems are required to enable the smart incubator system with IoT monitoring capabilities? ii. How to maintaining environment conditions in the incubator automatically? iii. How to monitor vital signs using IoT ? iv. How can real-time data collecting, analysis, and visualization be used to give healthcare providers with current information on the baby's condition and follow patterns over time ? V. How does a system alert a woman to breastfeed a baby, change the baby's diaper, and when the newborn cries?

9. VI. LOCATION OF THE STUDY This research report's case study will be located in Muhima Hospital, and consist of a mother, a doctor, an infant baby, and a nurse.

10. VII. CONCEPTUAL FRAMEWORK

11. VIII. RESEARCH METHODOLOGY ♦ The current study will use a descriptive and correlational research approach to describe the Smart Baby Care Incubator with IoT Monitoring system and investigate its impact on newborn care services. This method will allow the researcher to assess the success of the IoT-enabled incubator in enhancing infant health outcomes and assisting healthcare providers . ♦ Qualitative investigation Outcomes in statistics containing words, testimonies, observations, and files that show the issues and subject of the take a look. ♦ The study focuses on neonatologists, nurses, and NICU parents (about 300 people). It assesses their perspectives on the Smart Baby Care Incubator and IoT Monitoring's impact on neonatal care results.

12. IX. TARGET POPULATION AND SAMPLE SIZE Categories Population Sample size Sampling Techniques Doctors 40 36 Random sampling Nurses 110 86 Random sampling Mothers 1100 293 Random sampling Total 1250 303  

13. Sample size ♦ This study utilized it in the following ways: n = N / (1+Ne 2 ) whereas:  n = no. of samples N = total population e = error margin / margin of error ♦ A confidence level of 95% was assumed which resulted in a margin of error equal to 5%. In order to obtain a fair and representative sample size, the sample size will be drawn proportionate to the population size.

14. Sample size(Con’t) ♦ The sample size of 400 respondents will be drawn from the target population. The population will be proportionally divided into different category which include the Doctors and the Nurses where the Doctors= 40, Nurses =110 and 1100 mothers from Muhima Hospitals. Thus, n=1250/ (1+(1250*0.05 2 )) = 303

15. x. existing PROTOTYPE MODEL

16. XI. PROPOSED PROTOTYPE MODEL

17. XII. CONCLUSION The Smart Baby Care Incubator with IoT Monitoring combines advanced technology with important neonatal care. Its goal is to improve newborn health outcomes and support care by offering real-time monitoring, automated changes, and simple access to critical information.  

18. P.O Box 2611 Kigali [email protected] www.uok.ac.rw