IOT Enhanced Pollution Management System For Vehicles Using Predictive Machine Learning Models

The project seeks to solve the important issue of urban air pollution caused by vehicle emissions. This project aims to create a real-time monitoring and control system for vehicle pollution by combining Machine Learning (ML) and Internet of Things (IoT) technology. IoT sensors will be installed on vehicles and in strategic metropolitan areas to collect real-time data on pollutants including NOx, CO, and PM. Advanced machine learning algorithms will be used to analyze this data, find patterns, estimate pollution levels, and offer active emission reduction strategies. The research will also include engine model and fuel quality data to enable a thorough examination of emissions and traffic-related pollutants. The projected conclusion is an intelligent, data-driven system that can provide timely insights and solutions, resulting in cleaner air and healthier urban settings. This strategy improves pollution monitoring and management while also promoting sustainable urban design and public health activities.