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This project aims to develop an Intelligent Energy Management System (IEMS) that leverages IoT and edge AI technologies to monitor and optimize energy consumption in real-time. The system reduces energy waste. It helps lower electricity bills for households. Key components include the Arduino UNO R4 WiFi. MAX78000FTHR development boards are used with sensors for measuring power consumption temperature and ambient light. Smart plugs and relays act as actuators for appliance control. A WiFi module ensures seamless data transmission.
The IEMS features real-time monitoring. It allows for immediate tracking of energy use. It achieves this via current sensors. Edge AI models predict usage patterns. This enables automated control of appliances. Consequently it results in optimal energy efficiency. A user-friendly mobile app provides real-time insights. It also sends alerts It offers remote control capabilities. This enhances user engagement. The system also automatically turns off lights and appliances in unoccupied rooms. Additionally, it notifies users of abnormal consumption.
Implementation involves setting up hardware connections. Developing software is required for data collection and AI training. Tests are conducted in controlled environments. Tests in real-world environments are also necessary. Final deployment aims to validate performance. It also gathers user feedback. Ultimately this IEMS project promotes energy conservation. It enhances the comfort and convenience of smart home living. Making it standout solution in IoT and Edge AI Project Challenge.