Title

Lightweight context-aware activity recognition

Source of Publication

Lecture Notes in Electrical Engineering

Abstract

© Springer-Verlag Berlin Heidelberg 2016. In ubiquitous environments, it is important to recognize the situation and deliver services accordingly. In addition, it is equally important to have a fast response time. The existing context-aware activity recognition engines have good recognition rates; however, they consume lots of time to produce feasible results. Our focus in this research is to reduce the time required by eliminating the need for ontology matching (in context-aware activity manipulation engine) and extend the rules. In addition, we incorporate the sliding time window concept to retain activities for a longer duration and maintain their relevance using ontological data for a better accuracy. The proposed scheme has increased the overall accuracy against the existing system by 12.6 % for individual activities relevance and 6 % for high level activities.

Document Type

Conference Proceeding

ISBN

['9783662478943']

First Page

367

Last Page

373

Publication Date

1-1-2016

DOI

10.1007/978-3-662-47895-0_44

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