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Authors: Andrzej Szczurek ; Monika Maciejewska and Tomasz Pietrucha

Affiliation: Wroclaw University of Technology, Poland

Keyword(s): Indoor Air, Occupancy Detection, Gas Sensor, VOC, Carbon Dioxide.

Related Ontology Subjects/Areas/Topics: Applications and Uses ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Energy Efficiency ; Energy Efficiency and Green Manufacturing ; Environment Monitoring ; Gas Analysis and Sensing ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial and Structural Monitoring ; Industrial Engineering ; Informatics in Control, Automation and Robotics ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Obstacles ; Pattern Recognition ; Physiological Computing Systems ; Reasoning on Sensor Data ; Sensor Networks ; Soft Computing

Abstract: Room occupancy is an important variable in high performance building management. Presence of people is usually detected by dedicated sensing systems. The most popular ones exploit physical phenomena. Such sensing solutions include passive infrared motion detectors, magnetic reed switches, ultrasonic, microwave and audible sensors, video cameras and radio-frequency identification. However, in most cases either human movement is needed to succeed in detection or privacy issues are involved. In this work, we studied occupancy detection using chemical sensors. In this case, the basis for detecting human presence indoors is their influence of chemical composition of air. Movement of people is not needed to succeed and privacy of occupants is secured. The approach was reported effective when using carbon dioxide, which is one of major human metabolites. We focused on volatile organic compounds (VOCs). Their consideration is justified because numerous human effluents belong to this group. The analysis showed that VOCs’ sensors, such as semiconductor gas sensors, offer comparable occupancy detection accuracy (97.16 %) as nondispersive infrared sensor (NDIR) (97.36 %), which is considered as the benchmark. In view of our results, semiconductor gas sensors are interesting candidates for nodes of sensor nets dedicated to detection of human presence indoors. They are smaller, cheaper and consume less energy. (More)


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Paper citation in several formats:
Szczurek, A.; Maciejewska, M. and Pietrucha, T. (2017). Occupancy Detection using Gas Sensors. In Proceedings of the 6th International Conference on Sensor Networks - SENSORNETS; ISBN 978-989-758-211-0; ISSN 2184-4380, SciTePress, pages 99-107. DOI: 10.5220/0006207100990107

author={Andrzej Szczurek. and Monika Maciejewska. and Tomasz Pietrucha.},
title={Occupancy Detection using Gas Sensors},
booktitle={Proceedings of the 6th International Conference on Sensor Networks - SENSORNETS},


JO - Proceedings of the 6th International Conference on Sensor Networks - SENSORNETS
TI - Occupancy Detection using Gas Sensors
SN - 978-989-758-211-0
IS - 2184-4380
AU - Szczurek, A.
AU - Maciejewska, M.
AU - Pietrucha, T.
PY - 2017
SP - 99
EP - 107
DO - 10.5220/0006207100990107
PB - SciTePress