AI BASED SMART ENVIRONMENTAL MONITORING SYSTEM

Abstract

This project introduces an AI-based Smart Environmental Monitoring System that automatically detects and reports public safety issues in urban areas. It uses Artificial Intelligence (AI) and Internet of Things (IoT) technologies. The main goal of the system is to monitor environmental conditions and identify hazardous situations without the need for constant human supervision. The system addresses two common problems in public spaces: gatherings of stray dogs and open manholes. A camera module captures images of the environment, and a machine learning model analyses these images to detect dogs. When several dogs are identified in the same area, signaling a gathering, the system records the event and sends the information to a web-based complaint management system. Additionally, an ultrasonic sensor measures the distance between the sensor and the ground to check the condition of a manhole. If the distance suggests that the manhole is open, the system creates a complaint and sends it to the monitoring dashboard. There is also a web interface where administrators and officers can log in to view detected problems, check details like location, date, and time, and update the complaint status to resolved or pending. By combining sensor technology, machine learning, and web monitoring, this system improves the efficiency of detecting environmental hazards, reduces reliance on manual reporting, and allows for quicker responses from authorities. This approach supports smart city efforts by offering a practical solution for monitoring safety-related environmental conditions in urban areas.