Sequential pattern-based activity recognition model for ambient computing. (17th February 2022)

• Record Type: Journal Article
• Authors: Gitanjali, J.; Ghalib, Muhammad Rukunuddin
• Is Part Of: International journal of advanced intelligence paradigms. Volume 21:Number 1/2(2022)
• Page Start: 41
• Page End: 52
• Publication Date: 2022-02-17
• Subjects: action -- activity -- sensor based data -- sequence patterns -- classifiers; Artificial intelligence -- Periodicals; Machine theory -- Periodicals; Fuzzy logic -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-0386

Abstract

In the recent years, the human activity recognition gain popularity in ambient computing. The human activity recognition is composed of identifying the daily activities of the users by observing their actions. Action identification is a more complex task than sensor data generated by each sensor. In this paper, sequential pattern-based activity recognition is proposed for identifying sequential patterns among actions on the given dataset. This support value is used as a parameter to validate the sequence. The experimental evaluation is performed on the real time dataset and it is observed that the sequential pattern approach is very beneficial in reducing the execution time and increasing the classification accuracy of the classifiers.