Abstract
Ubiquitous computing has been defined as “machines that fit the human environment instead of forcing humans to enter theirs.” An example of this type of approach is “Smart Sensory Furniture” (SSF) Project. SSF is an ambient assisted living system that allows inferring a potential dangerous action of an elderly person living alone at home. This inference is obtained by a specific sensory layer with sensor nodes fixed into furniture and a reasoning layer embedded in a PC that learns from the users’ behavioral patterns and advices when the system detects unusual patterns. This paper aims to explain the SSF sensory layer, which is a distributed signal processing system in a network of sensing objects massively distributed, physically coupled, wirelessly networked, and energy limited. A complete set of experimental test has been carried out. The results show the level of accuracy for each type of sensors and potential use. Finally, the power consumption was experimentally measured and the results show the low maintenance requirements of this solution. The complete system design is described and discussed, including the node mesh details, as well as the type of sensors and actuators and other aspects, such as integration issues and solutions.
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