Lightweight context-aware activity recognition

Document Type

Conference Proceeding

Source of Publication

Lecture Notes in Electrical Engineering

Publication Date

1-1-2016

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.

ISBN

9783662478943

ISSN

1876-1100

Publisher

Springer Verlag

Volume

354

First Page

367

Last Page

373

Disciplines

Computer Sciences

Keywords

Activity recognition, Knowledgebase, Ontology

Scopus ID

84947246965

Indexed in Scopus

yes

Open Access

no

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