IOT-ENABLED WEATHER ANALYSIS USING ML ALGORITHMS

Abstract

This project presents about IoT-based Weather Monitoring and Forecasting System designed by using ESP32 microcontroller integrated with a 16x2 LCD display (non-I2C) which is suited for environmental sensors. This system of model includes a DHT11 sensor for predicting temperature and humidity, MQ-7 and MQ-135 sensors detecting carbon monoxide (CO) and carbon dioxide (CO₂) levels respectively, the sensor LDR measure the ambient light intensity, and a rain sensor is to detect precipitation. The sensors which predict the real time data analysis and displayed on the LCD display. Then it will be uploaded to the remote monitoring cloud platform i.e. Think speak. A Machine Learning (ML) module is implemented on a local computer, the module of this sensor receives a real time data from the ESP32 via serial communication, through a pre-trained ML model the data will be processed, and also predicts the current weather condition like (e.g., Sunny, Cloudy, Rainy) along with a rain forecast. The results will rapidly share to the user via a Telegram bot channel, providing timely weather forecast updates.