AI-Powered Environments or Industrial Monitoring and Surveillance Alert System

Abstract

This project presents to designed to improve safety, environmental monitoring, and real-time supervision in Environments or industrial. The system is developed using an ESP32-CAM module, which captures live images to provide continuous visual surveillance of the industrial workspace. Environmental parameters such as temperature and humidity gas leakage and fire detection are continuously monitored to ensure both workplace safety and environmental protection. In addition, current and voltage sensors are used to track electrical parameters and detect abnormal power conditions. The ESP32 microcontroller acts as the central controller, collecting sensor data and analysing it to identify hazardous or abnormal situations. When conditions such as fire, gas leakage, abnormal temperature, environmental hazards, or electrical faults are detected, the system immediately activates a buzzer alert and AI technology based supervised machine learning are used to send alert abnormal condition to bot app displays warning messages on an LCD for rapid response. The ESP32-CAM also provides real-time video monitoring, enhancing industrial surveillance and operational awareness. This integrated system offers a low-cost, scalable, and energy-efficient solution for industrial and environmental monitoring. By combining safety sensors, electrical monitoring, and visual surveillance, the proposed system helps reduce industrial accidents, protect the environment, and improve overall workplace safety and operational efficiency.