Low Cost Decentralized Smart Air Purification and Monitoring System

Abstract

Air pollution has become a serious threat to human health, especially in densely populated urban regions such as Delhi NCR. The increasing number of vehicles, industries, and construction activities has resulted in high levels of harmful gases and airborne particles. To overcome this challenge, this work presents a low- cost decentralized smart air purification and monitoring system based on Internet of Things (IoT) and blockchain technology. The proposed system uses DHT11, MQ-7, and MQ-135 sensors to continuously measure temperature, humidity, carbon monoxide, and overall air quality. The sensed data is transmitted to a cloud platform and securely recorded using blockchain to ensure data integrity and transparency. When pollution levels exceed safe limits, a low-cost air purification unit is automatically activated to reduce contaminants. The system is affordable, scalable, and suitable for deployment in smart city environments, providing both real-time monitoring and localized pollution control.

Introduction

The text discusses the growing problem of air pollution in urban areas like Delhi NCR, driven by transportation, industrial, and construction activities. Traditional air quality monitoring relies on expensive, centralized stations that cannot capture real-time, localized pollution exposure. Recent advances in IoT allow low-cost sensors and microcontrollers to continuously collect environmental data, but data security and reliability remain concerns. Blockchain technology can address this by providing tamper-proof, decentralized storage, while integrating automated air purification ensures timely pollution control.

The proposed solution is a low-cost, decentralized smart air purification and monitoring system combining IoT-based sensing, blockchain-secured data, and automatic purification. It is designed for indoor use in homes, offices, schools, and small public spaces. The system continuously monitors air quality with gas, temperature, and humidity sensors, processes data via an Arduino UNO microcontroller, displays readings on an LCD, and activates HEPA, activated carbon, and UV-C purification when pollution exceeds safe levels.

Key features include:

• Continuous real-time monitoring of harmful gases and particulates.
• Automated purification triggered by air quality thresholds.
• Cloud connectivity for remote monitoring and historical analysis.
• Low-cost, modular, and scalable design for broad adoption.
• Decentralized operation, allowing multiple units to contribute to a shared network.

The literature review highlights the effectiveness of low-cost sensor networks, IoT monitoring, and blockchain integration for secure environmental data. However, most existing systems either monitor without purification or lack affordable, decentralized, automated solutions.

Methodology includes sensor data acquisition, processing, threshold-based purification control, and cloud monitoring. System design emphasizes modularity, energy efficiency, calibration, noise reduction, and future expandability, with calculations for sensor signal conversion, gas concentration, and Air Quality Index (AQI) evaluation. A MATLAB/Simulink model simulates the system before hardware deployment to validate its operation under varying air quality conditions.

Overall, the proposed system aims to provide an affordable, intelligent, and secure solution for improving indoor air quality, combining monitoring, data reliability, and automatic purification for modern smart environments.

Conclusion

The IoT-based Smart Air Purification and Monitoring System presented in this work offers a practical and sustainable solution for maintaining healthy indoor air quality. By combining HEPA filtration, activated carbon adsorption, and UV-C disinfection, the system is capable of removing fine particles, toxic gases, and harmful microorganisms from the air. The use of environmental sensors together with an Arduino UNO controller enables continuous monitoring and automatic regulation of air quality within safe limits. The proposed design is economical, easy to maintain, and well suited for use in homes, offices, and small public spaces. Its modular structure allows future improvements such as cloud connectivity, artificial intelligence–based air quality forecasting, and enhanced filtration techniques. Simulation results obtained through MATLAB Simulink validate the accuracy. Overall, this project provides a compact, energy-efficient, and intelligent approach to indoor air purification, supporting healthier living environments and sustainable smart-technology applications.

References

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Copyright

Copyright © 2026 Ms. A. Preethi, Hema R R, Kanishka M, Ramasuganthi R, Vinothini G. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.