Detection of indoor actions through probabilistic induction model

In the present work a system able to classify the indoor action is presented. The data are recorded with multiple kind of sensor collecting the position of the joints of the person in the room, the acceleration recorded on the person wrist and the presence or absence in a specific room. The latent semantic analysis, based on the principal component search, allows to estimate the probability of a given action according the sampled values.