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Sensors 2011, 11(12), 11581-11604; doi:10.3390/s111211581
Article

Towards Smart Homes Using Low Level Sensory Data

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Received: 26 October 2011; in revised form: 28 November 2011 / Accepted: 7 December 2011 / Published: 12 December 2011
(This article belongs to the Section Physical Sensors)
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Abstract: Ubiquitous Life Care (u-Life care) is receiving attention because it provides high quality and low cost care services. To provide spontaneous and robust healthcare services, knowledge of a patient’s real-time daily life activities is required. Context information with real-time daily life activities can help to provide better services and to improve healthcare delivery. The performance and accuracy of existing life care systems is not reliable, even with a limited number of services. This paper presents a Human Activity Recognition Engine (HARE) that monitors human health as well as activities using heterogeneous sensor technology and processes these activities intelligently on a Cloud platform for providing improved care at low cost. We focus on activity recognition using video-based, wearable sensor-based, and location-based activity recognition engines and then use intelligent processing to analyze the context of the activities performed. The experimental results of all the components showed good accuracy against existing techniques. The system is deployed on Cloud for Alzheimer’s disease patients (as a case study) with four activity recognition engines to identify low level activity from the raw data captured by sensors. These are then manipulated using ontology to infer higher level activities and make decisions about a patient’s activity using patient profile information and customized rules.
Keywords: accelerometer; location sensor; video sensor; u-healthcare; activity recognition accelerometer; location sensor; video sensor; u-healthcare; activity recognition
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Khattak, A.M.; Truc, P.T.H.; Hung, L.X.; Vinh, L.T.; Dang, V.-H.; Guan, D.; Pervez, Z.; Han, M.; Lee, S.; Lee, Y.-K. Towards Smart Homes Using Low Level Sensory Data. Sensors 2011, 11, 11581-11604.

AMA Style

Khattak AM, Truc PTH, Hung LX, Vinh LT, Dang V-H, Guan D, Pervez Z, Han M, Lee S, Lee Y-K. Towards Smart Homes Using Low Level Sensory Data. Sensors. 2011; 11(12):11581-11604.

Chicago/Turabian Style

Khattak, Asad Masood; Truc, Phan Tran Ho; Hung, Le Xuan; Vinh, La The; Dang, Viet-Hung; Guan, Donghai; Pervez, Zeeshan; Han, Manhyung; Lee, Sungyoung; Lee, Young-Koo. 2011. "Towards Smart Homes Using Low Level Sensory Data." Sensors 11, no. 12: 11581-11604.



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