The increasingly large availability of sensors in modern houses, due to the establishment of home assistants, allow to think in terms of smart houses where behaviours can be automatized based on user habits. Common tasks required to this aim include activity prediction, i.e., the task of forecasting what is the next activity a human is going to perform in the smart space based on past sensor logs. In this discussion paper1, we outline a novel activity prediction method for smart houses based on the seminal probabilistic method named Marked Temporal Point Process Prediction.

Activity daily living prediction with marked temporal point processes

Fortino G.;Guzzo A.;Ianni M.;Mecella M.
2021

Abstract

The increasingly large availability of sensors in modern houses, due to the establishment of home assistants, allow to think in terms of smart houses where behaviours can be automatized based on user habits. Common tasks required to this aim include activity prediction, i.e., the task of forecasting what is the next activity a human is going to perform in the smart space based on past sensor logs. In this discussion paper1, we outline a novel activity prediction method for smart houses based on the seminal probabilistic method named Marked Temporal Point Process Prediction.
Activity prediction
Human habits
Smart houses
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/328602
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