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)