Authors :
Tarun Badiwal; Nitin Sharma; Utkarash Sahai Saxsena; Suresh Chand Meena
Volume/Issue :
Volume 10 - 2025, Issue 12 - December
Google Scholar :
https://tinyurl.com/yef7wjz6
Scribd :
https://tinyurl.com/yeynwvp7
DOI :
https://doi.org/10.38124/ijisrt/25dec672
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Noise pollution has become a serious environmental challenge, especially in rapidly growing urban regions. Excessive
noise levels contribute to psychological stress, hypertension, sleep disturbance, reduced productivity, and long-term hearing
damage. Traditional monitoring approaches rely on manual measurements that are time-consuming, expensive, and incapable
of real-time reporting.
This paper presents a low-cost IoT-based noise pollution monitoring system using the ESP32 microcontroller and an analog
sound sensor. The system measures ambient noise levels, converts them into decibel (dB) values, and uploads them to a cloud
dashboard using Wi-Fi. Users can monitor live data, historical trends, and receive alerts when predefined thresholds are crossed.
Experimental evaluation shows an accuracy of 90–95% compared to a standard sound-level meter, making the system suitable
for smart city, school, hospital, and industrial applications.
References :
- A. Sharma et al., IoT-Based Sound Monitoring System, IEEE Sensors Journal, 2024.
- K.Patel, Smart Noise Measurement Using ESP Modules, IJSER, 2023
- WHO Environmental Noise Guidelines, 2022.
- ESP32 and Sound Sensor Datasheets.
Noise pollution has become a serious environmental challenge, especially in rapidly growing urban regions. Excessive
noise levels contribute to psychological stress, hypertension, sleep disturbance, reduced productivity, and long-term hearing
damage. Traditional monitoring approaches rely on manual measurements that are time-consuming, expensive, and incapable
of real-time reporting.
This paper presents a low-cost IoT-based noise pollution monitoring system using the ESP32 microcontroller and an analog
sound sensor. The system measures ambient noise levels, converts them into decibel (dB) values, and uploads them to a cloud
dashboard using Wi-Fi. Users can monitor live data, historical trends, and receive alerts when predefined thresholds are crossed.
Experimental evaluation shows an accuracy of 90–95% compared to a standard sound-level meter, making the system suitable
for smart city, school, hospital, and industrial applications.
