Istituto di Scienza e Tecnologie dell'Informazione     
Bacciu D., Chessa S., Gallicchio C., Gallicchio C., Micheli A., Barsocchi P. An experimental evaluation of reservoir computation for ambient assisted living. Bruno Apolloni, Simone Bassis, Anna Esposito, Francesco Carlo Morabito (eds.). (Smart Innovation, Systems and Technologies, vol. 19). Berlin-Heidelberg: Springer, 2013.
In this paper we investigate the introduction of Reservoir Computing (RC) neural network models in the context of AAL (Ambient Assisted Living) and self-learning robot ecologies, with a focus on the computational constraints related to the implementation over a network of sensors. Specifically, we experimentally study the relationship between architectural parameters influencing the computational cost of the models and the performance on a task of user movements prediction from sensors signal streams. The RC shows favorable scaling properties results for the analyzed AAL task.
URL: http://link.springer.com/chapter/10.1007%2F978-3-642-35467-0_5
DOI: 10.1007/978-3-642-35467-0_5
Subject Ambient Assisted Living
C.2.2 Network Protocols

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