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International Research Journal of Engineering and Technology (IRJET)

e-ISSN: 2395-0056

Volume: 12 Issue: 10 | Oct 2025

p-ISSN: 2395-0072

www.irjet.net

IOT-BASED AIR POLLUTION MONITORING AND PURIFICATION SYSTEM Supriya Rajput 1 Alfiya Mulla2, Rabiya Kazi3, Suzain Bargir4, Tasbiya Chikkodi5 1Assistant Professor, Maratha Mandal’s Engineering College, Belagavi, Karnataka, India 2Student, Maratha Mandal’s Engineering College, Belagavi, Karnataka, India 3Student, Maratha Mandal’s Engineering College, Belagavi, Karnataka, India 4Student, Maratha Mandal’s Engineering College, Belagavi, Karnataka, India 5Student, Maratha Mandal’s Engineering College, Belagavi, Karnataka, India ---------------------------------------------------------------------***----------------------------------------------------------------------

Abstract - This research presents the development of an

Things architectures has created new possibilities for distributed, cost-effective air quality assessment systems. By integrating sensor networks with cloud-based data analytics and mobile interfaces, these systems empower individuals to track and manage their immediate breathing environment with unprecedented precision [3].

intelligent air quality management system that leverages Internet of Things technology to monitor and improve indoor atmospheric conditions. The proposed solution addresses growing concerns about airborne pollutants in enclosed spaces by implementing real-time detection and automated purification. At the core of the system is an ESP32 microcontroller that processes data from multiple environmental sensors, including a GP2Y1010 particulate matter detector and an MQ135 multi-gas sensor. These components work in tandem to identify harmful substances such as dust particles, carbon dioxide, carbon monoxide, and benzene derivatives. The architecture incorporates dual-mode operation, allowing either manual control through a mobile application or automatic adjustment of purification intensity based on contaminant concentration. Experimental validation demonstrates the system's capability to maintain air quality within safe parameters by dynamically modulating fan velocity in response to pollutant levels. This approach represents a significant step toward creating healthier indoor environments through accessible smart technology.

This investigation addresses the identified gap through the development of a comprehensive air quality management platform that combines real-time monitoring with responsive purification. Unlike conventional air purifiers that operate on fixed schedules or manual controls, the implemented system establishes a closed-loop control mechanism where purification intensity directly correlates with detected pollutant levels. The integration of multiple sensor modalities enables the detection of diverse contaminant types, while the IoT connectivity facilitates remote monitoring and control through consumer mobile devices. The subsequent sections of this paper detail the system architecture, component selection criteria, operational methodology, and performance evaluation. Particular emphasis is placed on the sensor calibration procedures, control algorithm development, and validation under realistic usage scenarios.

Keywords: IoT, Blynk, real-time monitoring, air purification, indoor air quality

1. INTRODUCTION

1.1 Research Objectives

The degradation of atmospheric quality in urban environments has emerged as a critical public health challenge, with scientific studies establishing clear correlations between pollutant exposure and respiratory complications [1]. While substantial attention has been directed toward outdoor air quality, the indoor environments where individuals spend approximately 90% of their time frequently harbor contaminant concentrations two to five times higher than external settings [2]. This paradox creates an urgent need for accessible monitoring technologies that can provide immediate awareness and intervention capabilities.

The primary objectives of this investigation include: designing a multi-sensor air quality monitoring platform, developing an intuitive user interface for local and remote interaction, implementing an adaptive control algorithm for automatic purification, and validating system performance under controlled environmental conditions.

1.2 Operational Modes A significant feature of this system is its dual-mode operation. In Manual Mode, the user has direct control over the fan speed via a slider in the Blynk app. In Automatic Mode, the system intelligently calculates the required fan speed based on the highest demand from either the dust or gas sensor readings, ensuring a dynamic and responsive purification process.

Traditional air quality assessment typically relies on expensive laboratory equipment or sparse government monitoring stations, offering limited utility for personalized environmental management. The emergence of Internet of

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