2011 · 189 citations · 15 references
EngineeringEmbedded SensingSmart CityGreen BuildingSmart EnvironmentBuilding TechnologySocial SciencesBuilt EnvironmentData ScienceGreen ItBuilding AutomationInternet Of ThingsImplicit SensingSmart BuildingNetwork InfrastructureIt InfrastructureUrban PlanningMobile ComputingComputer ScienceBuilding PerformanceMobile SensingUrban DesignConstruction Management
Green IT has traditionally focused on reducing the energy use of IT infrastructure, but additional savings can be achieved by leveraging that infrastructure to optimize building operations. The study proposes that building operations can be driven by information extracted from existing IT infrastructure to reduce energy consumption. Implicit occupancy sensing is implemented by monitoring MAC and IP addresses on routers and wireless access points, correlating them with building, zone, or room occupancy, and using the resulting data to control lighting, HVAC, and other functions; the approach was experimentally evaluated for feasibility and accuracy. Data from two facilities demonstrate that implicit sensing using existing IT infrastructure shows significant promise for occupancy detection and energy savings.
The primary focus of Green IT has been on reducing energy use of the IT infrastructure itself. Additional significant energy savings can be achieved by using the IT infrastructure to enable energy savings in both the IT and non-IT infrastructure. Our premise is that energy can be saved by driving building operation on information gleaned from existing IT infrastructure already installed for non-energy purposes. We call our idea implicit occupancy sensing where existing IT infrastructure can be used to replace and/or supplement traditional dedicated sensors to determine building occupancy. Our implicit sensing methods are largely based on monitoring MAC and IP addresses in routers and wireless access points, and then correlating these addresses to the occupancy of a building, zone, and/or room. Occupancy data can be used to control lighting, HVAC, and other building functions to improve building functionality and reduce energy use. We experimentally evaluate the feasibility of this dual-use of IT infrastructure and assess the accuracy of implicit sensing. Our findings, based on data collected from two facilities, show that there is significant promise in implicit sensing using the existing IT infrastructure present in most modern non-residential buildings.
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Building occupancy detection through sensor belief networks
Robert H. Dodier, Gregor P. Henze, Dale K. Tiller et al. · Energy and Buildings · 2006 · 273 citations
Occupancy based demand response HVAC control strategy
Varick L. Erickson, Alberto Cerpa · 2010 · 218 citations
Smart occupancy sensors to reduce energy consumption
Vishal Garg, N.K. Bansal · Energy and Buildings · 2000 · 212 citations