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Original Article

IOT Based Industrial Environmental Monitoring System

Kolli V JayaLakshmi1 Sesetti Kalyani2 Sambana Yaswitha3 Putta Vyshnavi4 Vommi Sai Vignesh5
1 Assistant Professor, Department of ECE, Dr. Lankapalli Bullayya College of Engineering, Visakhapatnam, Andhra Pradesh, India. 2 3 4 5 Department of ECE, Dr. Lankapalli Bullayya College of Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, India.

Published Online: May-June 2026

Pages: 177-180

Abstract

Industrial environments often involve hazardous operating conditions such as the presence of flammable or toxic gases, excessive temperature, smoke, fire risks, and poor air quality. These factors pose serious threats to worker safety, equipment reliability, and environmental health. Conventional monitoring systems largely depend on manual inspection or standalone safety devices, which are inefficient, prone to human error, and incapable of providing real-time remote monitoring. To overcome these limitations, this project proposes an IOT-Based Industrial Environmental Monitoring System using ESP32. The proposed system continuously monitors critical environmental parameters including gas concentration, temperature, humidity, smoke or flame presence, and air quality using multiple sensors such as MQ- series gas sensors, DHT11 temperature and humidity sensor, smoke/flame sensor, and MQ-135 air quality sensor. The ESP32 microcontroller acts as the central processing unit, acquiring sensor data, processing it in real time, and transmitting it wirelessly to an IoT cloud platform using built-in Wi-Fi functionality. The monitored data is visualized on a cloud dashboard, enabling real-time remote monitoring and historical data analysis. When any environmental parameter exceeds predefined safety thresholds, the system automatically generates alerts and notifications, allowing rapid response to hazardous conditions. The proposed system is cost-effective, scalable, and easy to deploy, making it suitable for applications in manufacturing industries, chemical plants, warehouses, power stations, and research laboratories. With further enhancements such as advanced analytics and mobile application integration, the system can be extended to support predictive safety and smart industrial monitoring in accordance with Industry 4.0 concepts.

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