Real-time building occupancy sensing using neural-network based sensor network

IEEE International Conference on Digital Ecosystems and Technologies

Volumn , Issue , 2013, Pages 114-119

  Ekwevugbe, Tobore ^a   Brown, Neil ^a   Pakka, Vijay ^a   Fan, Denis ^b  

^a DE MONTFORT UNIVERSITY   (United Kingdom)

^b Department of Energy and Climate Change ^*  (United Kingdom)

Author keywords

Energy savings; Features; HVAC systems; Occupancy; Sensors

Indexed keywords

BUILDING OCCUPANCY; ENERGY EFFICIENCY IN BUILDINGS; FEATURES; HVAC SYSTEM; NON-INTRUSIVE SENSORS; OCCUPANCY; OCCUPANCY DETECTIONS; SENSING TECHNOLOGY;

AIR CONDITIONING; CARBON DIOXIDE; ECOSYSTEMS; EMBEDDED SYSTEMS; ENERGY CONSERVATION; ENERGY EFFICIENCY; OFFICE BUILDINGS; SENSOR NETWORKS; SENSORS; UNCERTAINTY ANALYSIS; VENTILATION;

ADAPTIVE CONTROL SYSTEMS;

EID: 84885757392     PISSN: 21504938     EISSN: 21504946     Source Type: Conference Proceeding    
DOI: 10.1109/DEST.2013.6611339     Document Type: Conference Paper

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