Issue |
E3S Web Conf.
Volume 634, 2025
2025 3rd International Forum on Clean Energy Engineering (FCEE2025)
|
|
---|---|---|
Article Number | 03002 | |
Number of page(s) | 12 | |
Section | Environmental Sensing and Monitoring Systems | |
DOI | https://doi.org/10.1051/e3sconf/202563403002 | |
Published online | 20 June 2025 |
A study on a low-cost real time MEMS based modular Indoor Environmental Quality monitor sensor
1 School of Civil Engineering and Surveying, Faculty of Technology, University of Portsmouth, Portsmouth, UK
2 School of Electrical and Mechanical Engineering, Faculty of Technology, University of Portsmouth, Portsmouth, UK
* Corresponding author: nikos.nanos@port.ac.uk
Indoor air quality (IAQ) is crucial for human well-being, particularly in urban environments where individuals spend most of their time indoors. Poor IAQ, influenced by pollutants like CO2, particulate matter (PM), and volatile organic compounds (VOCs), necessitates real-time monitoring for effective mitigation. Traditional IAQ monitoring systems, while precise, are often costly and cumbersome, limiting accessibility. This study explores the feasibility of integrating low-cost micro-electromechanical systems (MEMS) sensors with Arduino platforms to develop an affordable, portable IAQ monitoring solution. A prototype IAQ monitoring system was developed using MEMS sensors, including the BME680 for temperature, humidity, and VOCs; LM358 for sound levels; BH1750 for light intensity; GP2Y10x and SPS30 for PM detection. The system was integrated with an Arduino MKR1010, enabling real-time data logging and wireless transmission. Calibration against commercial sensors ensured data validity. The prototype sensor package underwent preliminary deployments in controlled and dynamic environments, including an indoor laboratory and a concrete lab. Results demonstrated the system’s ability to capture variations in IAQ parameters accurately. Despite minor limitations, the system proved viable for continuous IAQ monitoring at a significantly reduced cost compared to traditional systems. Future work will focus on refining sensor calibration, improving data processing through advanced analytics, and establishing standardized evaluation criteria to enhance sensor reliability and potential use framework.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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