Article ID Journal Published Year Pages File Type
5004602 ISA Transactions 2014 7 Pages PDF
Abstract

•Applied Viterbi algorithm to recognize activity sequences from sensors events.•Tested time and activity length size feature values of sensors events.•Evaluated activity sequences recognition performances of Viterbi algorithm.•Larger time and/or smaller activity length size feature values are better.

In this paper, Viterbi algorithm based on a hidden Markov model is applied to recognize activity sequences from observed sensors events. Alternative features selections of time feature values of sensors events and activity length size feature values are tested, respectively, and then the results of activity sequences recognition performances of Viterbi algorithm are evaluated. The results show that the selection of larger time feature values of sensor events and/or smaller activity length size feature values will generate relatively better results on the activity sequences recognition performances.

Related Topics
Physical Sciences and Engineering Engineering Control and Systems Engineering
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