A Mobile Unit for Weather Monitoring and Prediction Using IoT and Machine Learning

This project focuses on developing a mobile weather monitoring unit integrating IoT and machine learning. Built on a 4-wheel drive platform with components like the Arduino UNO R3, SEN50 DHT11 sensor, L298 Motor Driver Module, and a 12V lithium battery, the system collects temperature and humidity data every 5 seconds. A machine learning model processes this data to predict temperature trends and detect environmental changes. The goal is to automate temperature monitoring and control, particularly in environments like greenhouses, labs, and storage units. By minimizing human intervention, the system reduces labour while ensuring timely adjustments based on real-time data, enhancing environmental management and control efficiency.