Recognition of Human Activities using the User’s Context and the Activity Theory for Risk Prediction
Alfredo Del Fabro Neto, Bruno Romero de Azevedo, Rafael Boufleuer, João Carlos Damasceno Lima, Alencar Machado, Iara Augustin, Márcia Pasin · 2016
Some of the activities performed daily by people may harm them physically. The performance of such activities in an inadequate manner or in an adverse environment can increase the risk of accidents. The development of context-aware systems capable of predicting these risks is important for human damage prevention. In this sense, we are developing an approach based on the Activity Theory and the Skill, Rule and Knowledge model for risk prediction of human activities in a context-aware middleware. To predict the risk in the activities, we identify the probability for the next actions and compare the current physiological context with its future state. In order to concept proving the proposed model, we developed a prototype and tested it with a public and a private dataset. The results show that the proposed model can assign an appropriate risk factor to the tested activities.