This post is an excerpt from the journal ISA Transactions. All ISA Transactions articles are free to ISA members, or can be purchased from Elsevier Press.
Abstract: 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.
Free Bonus! To read the full article on influence of time and length size feature selections, click here.
Enjoy this technical resource article? Join ISA and get free access to all ISA Transactions articles as well as a wealth of other technical content, plus professional networking and discounts on technical training, books, conferences, and professional certification.
Click here to join ... learn, advance, succeed!
2006-2018 Elsevier Science Ltd. All rights reserved.
