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1. IoT-Based Smart Energy Meter – Monitor Electricity Usage and Detect   Energy   Thef Subject Coordinator Dr. Arpita Bhargava Assistance pro. IT department INTERNET OF THINGS– IT 322 Represented Group:- 22U03006- Yogesh jadhav 22U03005- Ankit Godbole 22U03070- Sujeet Rawat DEPRATMENT OF INFORMATION TECHNOLOGY

2. Introduction Smart energy meters are a modern alternative to traditional meters, capable of real-time data collection and remote monitoring. These meters offer enhanced accuracy, automated billing, and efficient energy management. One of the major issues with traditional energy meters is energy theft, which leads to significant financial losses for power companies. With IoT integration, smart energy meters can detect power theft by analyzing consumption patterns and detecting unusual activities. This project aims to design and implement a smart energy meter that leverages IoT technology to monitor power consumption and alert authorities about potential theft. Subject Coordinator: Dr. Arpita Bhargava Subject Name & Code: IT-322 Semester: 6th

3. Objectives The primary objective of this project is to develop an advanced smart energy meter capable of real-time monitoring and detecting unauthorized electricity consumption. The key goals include: Developing a real-time monitoring system that provides consumers with live data on energy usage. Detecting energy theft and tampering through anomaly detection and pattern analysis. Enabling remote access for consumers and power authorities to track electricity consumption. Improving energy efficiency by providing data insights that help consumers reduce unnecessary usage. Implementing an automated billing system to ensure accurate and transparent electricity billing. Subject Coordinator: Dr. Arpita Bhargava Subject Name & Code: IT-322 Semester: 6th

4. System Architecture The IoT-based smart energy meter consists of multiple hardware and software components that work together to monitor electricity consumption and detect anomalies. Hardware Components: Microcontroller (ESP32/Arduino/Raspberry Pi) – Acts as the central processing unit. Current and Voltage Sensors (ACS712, PZEM-004T) – Measure power consumption. Wi-Fi/GSM Module – Enables communication with the cloud. Relay Module – Allows remote power control. Subject Coordinator: Dr. Arpita Bhargava Subject Name & Code: IT-322 Semester: 6th

5. Working Mechanism: Data Collection: Voltage and current sensors measure energy consumption. Data Processing: The microcontroller calculates power usage in real-time. Data Transmission: The processed data is sent to the cloud via Wi-Fi or GSM. User Interface: The data is displayed on a mobile app or web dashboard. Theft Detection: The system identifies abnormal consumption patterns and alerts the authorities. Subject Coordinator: Dr. Arpita Bhargava Subject Name & Code: IT-322 Semester: 6th

6. Hardware Components The Hardware components used in this project play a crucial role in ensuring the accuracy and efficiency of the smart energy meter. ESP32/Arduino Microcontroller: Serves as the main processing unit that controls the entire system. ACS712 Current Sensor & PZEM-004T Energy Meter: Measure the current, voltage, and power consumption of the connected load. Wi-Fi (ESP8266) and GSM (SIM800L) Modules: Enable remote data transmission to the cloud. Relay Module: Allows remote switching of the power supply in case of emergency or unauthorized access. LCD Display & LED Indicators: Provide real-time status updates locally. Subject Coordinator: Dr. Arpita Bhargava Subject Name & Code: IT-322 Semester: 6th

7. Software Components The software system consists of embedded programming, cloud integration, and user interface development. Embedded Programming: The microcontroller is programmed using C and Python to control the sensors and communication modules. Cloud Database: Data is stored in Firebase, AWS IoT, or a MySQL database for real-time access. User Interface: A web dashboard (React.js, Node.js) and a mobile app (Flutter/React Native) allow users to monitor their electricity usage remotely. Machine Learning Integration: AI algorithms analyze data to detect energy theft and unusual power usage patterns. Subject Coordinator: Dr. Arpita Bhargava Subject Name & Code: IT-322 Semester: 6th

8. Working Principle The smart energy meter operates by continuously monitoring the electrical parameters such as voltage, current, and power. Data Acquisition: Sensors measure voltage and current. Data Processing: The microcontroller computes the power consumed. Data Transmission: The readings are sent to the cloud for storage and analysis. User Access: Consumers and authorities can monitor the data via a web interface. Theft Detection: AI-based anomaly detection algorithms identify irregularities. Alerts and Actions: If energy theft is detected, an alert is sent, and power may be disconnected remotely. Subject Coordinator: Dr. Arpita Bhargava Subject Name & Code: IT-322 Semester: 6th

9. Real-Time Monitoring Features The proposed smart energy meter offers multiple real-time monitoring features: Live Data Updates: Consumers can track their electricity usage in real-time. Usage History: Historical data visualization through charts and graphs. Notifications & Alerts: Instant alerts for unusual consumption or possible theft. Remote Power Control: Users can remotely turn on/off their electricity supply. Billing & Cost Analysis: Automatic bill calculation based on actual energy usage. Subject Coordinator: Dr. Arpita Bhargava Subject Name & Code: IT-322 Semester: 6th

10. Energy Theft Detection Mechanism Energy theft occurs through various methods, such as direct hooking, meter bypassing, or tampering with meter readings. The smart energy meter employs multiple strategies to detect and prevent unauthorized electricity usage. Real-Time Power Analysis: Compares expected and actual consumption patterns. AI-Based Anomaly Detection: Identifies sudden spikes or drops in usage. Tamper Detection Sensors: Detect physical tampering attempts. Remote Alert System: Sends notifications to authorities if theft is detected. Once theft is identified, the system can either notify the authorities or trigger automatic disconnection of power. Subject Coordinator: Dr. Arpita Bhargava Subject Name & Code: IT-322 Semester: 6th

11. Advantages & Benefits Smart energy meters offer several advantages over traditional electricity meters: For Consumers: Real-time energy tracking Cost savings by reducing unnecessary consumption Improved transparency in billing For Utility Companies: Reduces losses due to theft Automates billing processes Enhances power grid efficiency For the Environment: Encourages energy conservation Reduces wastage and promotes sustainable energy use Subject Coordinator: Subject Name & Code: Semester:

12. Challenges & Future Enhancements Challenges: Despite the benefits, implementing smart energy meters comes with challenges: Accuracy of Theft Detection: AI-based detection models need constant training. Internet Connectivity Issues: Real-time monitoring requires stable network connections. Cybersecurity Risks: IoT devices are vulnerable to hacking attempts. Future Enhancements: AI & Machine Learning Improvements: More accurate theft detection models. Blockchain for Secure Transactions: Enhancing security and transparency. Integration with Smart Homes: Automated energy-saving suggestions. Subject Coordinator: Subject Name & Code: Semester:

13. Conclusion The IoT-based smart energy meter is a revolutionary advancement in power monitoring and theft detection. By leveraging real-time data collection, cloud computing, and AI-based analysis, this system ensures efficient power distribution while minimizing losses due to theft. Future enhancements will further improve its accuracy, security, and integration with smart grids, making electricity usage more sustainable and cost-effective. Subject Coordinator: Subject Name & Code: Semester: