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Development of an IoT-Enabled Real-Time Noise Pollution Monitoring and Alerting System Using Arduino
¹ Head of the Department, Department of Information Technology, PSV College of Engineering and Technology, Krishnagiri,Tamil Nadu, India. ² ³ ⁴ UG Scholars, Department of Information Technology, P.S.V. College of Engineering and Technology, Krishnagiri, Tamil Nadu, India.
Published Online: January-April 2026
Pages: 364-369
Noise pollution has emerged as one of the most critical environmental challenges in rapidly urbanizing and industrializing regions. Continuous exposure to elevated noise levels can lead to severe health issues such as hearing impairment, hypertension, stress disorders, sleep disturbances, and reduced productivity. Conventional noise monitoring techniques rely on manual measurements or standalone devices, which lack real-time data processing, remote accessibility, and automated alert mechanisms. These limitations make them inefficient for continuous environmental monitoring and rapid response. To overcome these challenges, this project presents the design and development of an IoT-enabled real-time noise pollution monitoring and alerting system using Arduino. The proposed system integrates a sound detection sensor with an Arduino microcontroller to continuously measure ambient noise levels in decibels (dB). The collected data is processed in real time and displayed locally on an LCD screen for immediate observation. Furthermore, the system incorporates an IoT communication module such as the ESP8266 Wi-Fi module, enabling seamless transmission of noise data to cloud-based platforms for remote monitoring and analysis. This allows users, authorities, and environmental agencies to access real-time noise data from anywhere, facilitating better decision-making and control. A key feature of the system is its intelligent alert mechanism. When the detected noise level exceeds a predefined threshold, the system automatically triggers alerts through a buzzer and visual indicators, ensuring immediate awareness. This proactive alerting approach helps in preventing prolonged exposure to harmful noise levels and supports timely corrective actions. The system is designed to be cost-effective, energy-efficient, and easily deployable in various environments such as residential areas, schools, hospitals, industrial zones, and traffic intersections. Its modular architecture allows scalability and integration with smart city infrastructures. Overall, this project demonstrates a reliable and efficient solution for continuous noise monitoring by combining embedded systems with IoT technology. It not only enhances environmental awareness but also contributes to sustainable urban development by providing a practical tool for noise pollution control and management.
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