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Communication Dans Un Congrès Année : 2020

Life Habits Modeling with Stochastic Timed Automata in Ambient Assisted Living

Résumé

Recent improvements in connected tools and learning algorithms allow new opportunities in the field of Ambient Assisted Living (AAL). However, smart home inhabitant's life habits are often required to obtain adequate results for energy management, security, Health at Home (HaH), and numerous other applications. In this paper, a model for life routines representation and algorithms for its generation is introduced. Study on the state of the art exposes that activity ordering and duration are key features of human behavior. Consequently, the presented approach focuses on a higher level of semantic by observing activities performed by the inhabitant rather than the sensor logs, which allow for better understanding of his comportment and universality of the model for multiple aims. Stochastic Time Automata (STA) is proposed as it adequately models activity ordering with probability associated to edges and activity duration through probability distribution associated to location delay. Presented approach does not require specific equipment besides sensors required for activity recognition and is versatile enough to be used in various applications. A case study highlights the relevancy of the chosen features and demonstrates that the proposed model is efficient to depict and understand inhabitants' life habits.
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Dates et versions

hal-03039270 , version 1 (03-12-2020)

Identifiants

  • HAL Id : hal-03039270 , version 1

Citer

Kevin Fouquet, Gregory Faraut, Jean-Jacques Lesage. Life Habits Modeling with Stochastic Timed Automata in Ambient Assisted Living. 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Oct 2020, Toronto, Canada. pp. 2740-2745. ⟨hal-03039270⟩
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