Abstract-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 nonresidential buildings.

Buildings are a major consumer of energy. We believe that energy can be saved with the notion of implicit occupancy sensing where existing IT infrastructure can be used to replace and/or supplement explicit dedicated sensors to determine building occupancy and drive building operation. Implicit sensing has the promise to be both lower in cost than explicit sensing based on PIR and ultrasound sensors and to offer additional useful data about the occupants of a building. Our implicit sensing methods are largely based on monitoring IP and MAC addresses in Wi-Fi access points and in routers, and then correlating these addresses to the occupancy of a floor, area, or room of a building. We experimentally evaluate the feasibility of this dual-use of IT infrastructure. We demonstrate an application of implicit sensing to sense the pending occupancy of a user workspace and automatically control the plugged-in devices in the workspace.