Indoor Air Sensing: A Study in Cost, Energy, Reliability and Fidelity in Sensing

• Published in: Sensing and imaging Vol. 24; no. 1
• Main Authors: Sharma, Praveen Kumar, Dalal, Bidyut, Mondal, Ananya, Sen, Argha, Banerjee, Amartya, Mondal, Sandip, De, Tanmay, Saha, Sujoy
• Format: Journal Article
• Language: English
• Published: New York Springer US 20.02.2023
• Subjects: Electrical Engineering; Engineering; Imaging; Microwaves; Original Paper; Radiology; RF and Optical Engineering; Air quality monitoring device; Energy aware system; Soft calibration; Hard calibration; Indoor air quality
• ISSN: 1557-2072; 1557-2072
• DOI: 10.1007/s11220-023-00412-x

The rise in environmental pollution and degradation of air quality worldwide has dragged researchers’ attention due to its direct societal impact. Studies reveal that the indoor environment is more polluted than the outdoors. In this paper, a framework for indoor air quality monitoring has been presented. We have developed a portable and cost-effective air quality monitoring device. The device generates fine-grained data for a combination of different pollutants and meteorological sensors (humidity and temperature). In this work, an energy-aware Environment Monitoring Device (EMD) has been developed with an adaptive sampling rate. Different aspects of the EMD have been presented with an analysis of their power consumption. The proposed technique has reduced more than 45% of energy consumption. A proposed energy reduction technique has discussed a trade-off between the cost-effectiveness of developed EMD and its reliability. We proposed the calibration of the sensor to ensure the reliability of the sensed data. A soft-calibration technique has been proposed considering the classrooms’ Spatio-temporal nature to ensure the sensed data’s reliability by mitigating the sensor errors due to spatial factors and achieved ≈ 6 % of error reduction compared to the baselines. Moreover, an energy-aware calibration technique has been proposed by providing a scheduling algorithm for re-calibration. The overall system significantly improves the lifetime and energy consumption of the sensors compared to that of normal conditions.