Authors : Rajesh Kumar K.; Nelapati Siyuktha; Varsha Narra; Vasa Ashwitha; Gantla Sai Smitha; Mantenwar Akshaya; Golkonda Pavani; M. Lakshmi Kausthubha

Volume/Issue : Volume 11 - 2026, Issue 3 - March

Google Scholar : https://tinyurl.com/4884f67z

Scribd : https://tinyurl.com/3zcpzjpc

DOI : https://doi.org/10.38124/ijisrt/26mar1620

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Rapid urbanization and industrial growth have significantly increased air and sound pollution levels, posing serious threats to environmental sustainability and public health. The primary objective of this work is to design and develop an Internet of Things (IoT) based air and sound pollution monitoring system capable of continuously measuring, analysing, and reporting pollution parameters in real time. The proposed system aims to provide accurate, low-cost, and scalable environmental monitoring that supports timely decision-making and effective pollution management. The novelty of this work lies in the integrated monitoring of both air quality and sound intensity within a single IoT framework, combined with localized data processing and real-time visualization. Unlike conventional monitoring stations that are expensive and sparsely distributed, the proposed system leverages low-cost sensors and networked embedded devices to enable dense deployment and improved spatial resolution of pollution data. The methodology involves interfacing air quality sensors for parameters such as particulate matter and harmful gases, along with sound sensors for noise level measurement, to an embedded controller. The collected data are processed and transmitted through a communication module to a monitoring platform, where they are visualized in real time and stored for further analysis. Threshold-based alert mechanisms are incorporated to notify users or authorities when pollution levels exceed permissible limits. Field testing is conducted under different environmental conditions to evaluate system performance in terms of accuracy, reliability, responsiveness, and scalability. The findings demonstrate that the proposed IoT-based monitoring system provides consistent and reliable measurements of air and sound pollution with minimal latency. The integrated approach enables simultaneous assessment of multiple environmental factors, offering a more comprehensive understanding of urban pollution patterns. Results also indicate that the system is cost-effective, energyefficient, and suitable for continuous long-term monitoring. Overall, this study confirms that IoT-enabled air and sound pollution monitoring systems can serve as an effective alternative to traditional monitoring methods, supporting smart city initiatives, environmental protection policies, and public awareness by delivering real-time, accessible, and actionable environmental data.

Keywords : Internet of Things (IoT), Air Pollution, Smart Control, Sound Pollution.

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