Multioccupant activity recognition in pervasive smart home environments
Authors: Benmansour, A., Bouchachia, A., Feham, M.
Journal: ACM Computing Surveys
Publication Date: 08/02/2016
Volume: 48
Issue: 3
eISSN: 1557-7341
ISSN: 0360-0300
DOI: 10.1145/2835372
Abstract:Human activity recognition in ambient intelligent environments like homes, offices, and classrooms has been the center of a lot of research for many years now. The aim is to recognize the sequence of actions by a specific person using sensor readings. Most of the research has been devoted to activity recognition of single occupants in the environment. However, living environments are usually inhabited by more than one person and possibly with pets. Hence, human activity recognition in the context of multioccupancy is more general, but also more challenging. The difficulty comes from mainly two aspects: Resident identification, known as data association, and diversity of human activities. The present survey article provides an overview of existing approaches and current practices for activity recognition in multioccupant smart homes. It presents the latest developments and highlights the open issues in this field.
https://eprints.bournemouth.ac.uk/23055/
Source: Scopus
Multioccupant Activity Recognition in Pervasive Smart Home Environments
Authors: Benmansour, A., Bouchachia, A., Feham, M.
Journal: ACM COMPUTING SURVEYS
Publication Date: 12/2015
Volume: 48
Issue: 3
eISSN: 1557-7341
ISSN: 0360-0300
DOI: 10.1145/2835372
https://eprints.bournemouth.ac.uk/23055/
Source: Web of Science
Multi-Occupant Activity Recognition in Pervasive Smart Home Environments
Authors: Benmansour, A., Bouchachia, A., Feham, M.
Journal: ACM Computing Surveys
Publication Date: 03/10/2016
Publisher: ACM
ISSN: 1557-7341
Abstract:been the center of lot of research for many years now. The aim is to recognize the sequence of actions by a specific person using sensor readings. Most of the research has been devoted to activity recognition of single occupants in the environment. However, living environments are usually inhabited by more than one person and possibly with pets. Hence, human activity recognition in the context of multi-occupancy is more general, but also more challenging. The difficulty comes from mainly two aspects: resident identification, known as data association, and diversity of human activities. The present survey paper provides an overview of existing approaches and current practices for activity recognition in multi-occupant smart homes. It presents the latest developments and highlights the open issues in this field.
https://eprints.bournemouth.ac.uk/23055/
Source: Manual