The high energy required by home appliances (like white goods, audio/video devices, and communication equipments) and air conditioning systems (heating and cooling), makes our homes one of the most critical areas for the impact of energy consumption on natural environment. In this paper we present a work in progress within the European project AIM for the design of a system that can minimize energy waste in home environments efficiently managing devices operation modes. In our architecture we use a wireless sensor network to monitor physical parameters (like light and temperature) as well as the presence of users at home and in each of its rooms. With gathered data our system creates profiles of the behavior of house inhabitants and through a prediction algorithm is able to automatically set system parameters in order to optimize energy consumption and cost while guaranteeing the required comfort level. When users change their habits due to unpredictable events, the system is able to detect wrong predictions analyzing in real time information from wireless sensors and to modify system behavior accordingly. By the automatic control of energy management system it is possible to avoid complex manual settings of system parameters that would prevent the introduction of home automation systems for energy saving into the mass market.
Home Energy Saving through a User Profiling System based on Wireless Sensors
BARBATO, ANTIMO;CAPONE, ANTONIO;
2009-01-01
Abstract
The high energy required by home appliances (like white goods, audio/video devices, and communication equipments) and air conditioning systems (heating and cooling), makes our homes one of the most critical areas for the impact of energy consumption on natural environment. In this paper we present a work in progress within the European project AIM for the design of a system that can minimize energy waste in home environments efficiently managing devices operation modes. In our architecture we use a wireless sensor network to monitor physical parameters (like light and temperature) as well as the presence of users at home and in each of its rooms. With gathered data our system creates profiles of the behavior of house inhabitants and through a prediction algorithm is able to automatically set system parameters in order to optimize energy consumption and cost while guaranteeing the required comfort level. When users change their habits due to unpredictable events, the system is able to detect wrong predictions analyzing in real time information from wireless sensors and to modify system behavior accordingly. By the automatic control of energy management system it is possible to avoid complex manual settings of system parameters that would prevent the introduction of home automation systems for energy saving into the mass market.File | Dimensione | Formato | |
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