Indoor occupancy estimation using the LTE-CommSense system

Sardar, Santu and Mishra, Amit K. and Khan, Mohammed Zafar Ali (2020) Indoor occupancy estimation using the LTE-CommSense system. International Journal of Remote Sensing, 41 (14). pp. 5609-5619. ISSN 0143-1161

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Abstract

Indoor occupancy estimation is necessary for the efficient operation of smart buildings. The development of an efficient algorithm to estimate indoor occupancy will allow better control and optimization of the heating, ventilation, and air conditioning (HVAC) methods of the whole building. Various methods are proposed in the open literature, which depends on environmental sensor data, image or video data, smartphone data, and radio frequency (RF) signals. This work proposes a unique non-intrusive, low cost, passive indoor occupancy estimation solution using our novel instrumentation scheme. We call it Long-Term Evolution (LTE) communication infrastructure-based environment sensing or LTE-CommSense. It requires no signal transmission and uses LTE communication radiation using passive radar principle. Therefore, the system is less complex, has a low footprint and consumes low power requiring no regulations related to radar signal transmissions. This system uses practical data to first determine whether the indoor environment is empty or not. If not, it estimates the number of people occupying the room. Performance evaluation with practical data confirms the feasibility of this proposed approach. Consistency of this approach is verified by using data captured at different dates and times with a different set of people.

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IITH Creators:
IITH CreatorsORCiD
Sardar, SantuUNSPECIFIED
Mishra, Amit K.UNSPECIFIED
Khan, Mohammed Zafar AliUNSPECIFIED
Item Type: Article
Uncontrolled Keywords: Communication infrastructure; Communication radiations; Control and optimization; Environmental sensor; Indoor environment; Number of peoples; Radiofrequency signals; Signal transmission
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 15 Jul 2021 07:49
Last Modified: 15 Jul 2021 07:49
URI: http://raiith.iith.ac.in/id/eprint/8339
Publisher URL: http://doi.org/10.1080/2150704X.2020.1734246
OA policy: https://v2.sherpa.ac.uk/id/publication/5433
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