A collective awareness platform for energy efficient smart buildings

Building Energy Management Systems (BEMS) are mature computer-based systems that manage, control and monitor different building technical services (such as heating, lighting etc.) and the energy consumption of devices used by the building. In the recent years, significant efforts have been made towards the integration of sensor devices and embedded computing systems with the Internet, thus transforming BEMS into a new era of Internet Buildings. Smart buildings can learn and even anticipate the needs of a buildings' occupants, including their preferences for light, temperature and other services, resulting in energy savings through targeted supply. In this work we argue that in such future buildings, it will be simply infeasible to expect individuals to be aware of the full range of potentially relevant possibilities and be able to pull them together manually. We thus propose a system that proactively guides users' interactions based on their preferences and constraints. We develop a collective awareness platform where the control of the smart building is balanced between the people and machines. We present the basic design principles, the implementation details and our experimental findings after evaluating our system in a real-world testbed