Smart Electricity Theft Detection System

An innovative **IoT-based solution** designed to detect unauthorized electricity usage and prevent energy theft. The system combines **Arduino sensors**, real-time monitoring, and **machine learning algorithms** to identify suspicious consumption patterns and alert authorities immediately.

🔋 Key Features

• **Real-time Monitoring**: Continuous monitoring of electricity consumption patterns using Arduino sensors
• **Theft Detection Algorithm**: Advanced algorithms to identify unauthorized usage and tampering
• **Web Dashboard**: Comprehensive dashboard built with **Next.js** for monitoring and analytics
• **Alert System**: Instant notifications via email and SMS when theft is detected
• **Data Analytics**: Historical data analysis and consumption pattern visualization
• **Mobile Responsive**: Access monitoring dashboard from any device
• **Scalable Architecture**: Support for multiple sensor nodes and locations

🛠️ Technical Implementation

The hardware component uses **Arduino microcontrollers** with current and voltage sensors to monitor electrical parameters. The **Flask backend** processes sensor data and applies machine learning algorithms to detect anomalies. The **Next.js frontend** provides a modern, responsive interface for system administrators.

System Architecture:

• **Edge computing capabilities** for real-time processing
• **Cloud integration** for data storage and analytics
• **Machine learning models** trained on historical consumption data
• **Distributed sensor network** with WiFi communication
• **Scalable deployment** across multiple locations

🌐 IoT Architecture

The IoT infrastructure consists of **distributed sensor nodes** communicating via WiFi to a central gateway. Each node monitors electrical parameters and transmits data to the Flask backend for processing. The system supports scalable deployment across multiple locations.

Hardware Components:

• **Arduino Uno/ESP32** microcontrollers
• **Current sensors** (ACS712/SCT-013)
• **Voltage sensors** for AC measurement
• **WiFi modules** for data transmission
• **Power supply units** for sensor nodes

💡 Challenges and Solutions

**Challenge**: Achieving accurate theft detection while minimizing false positives
**Solution**: Implemented ensemble machine learning models and statistical analysis to improve accuracy

**Challenge**: Ensuring reliable communication in remote areas
**Solution**: Mesh networking and offline data storage capabilities for robust operation