Journal
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
Volume 75, Issue -, Pages 158-171Publisher
ELSEVIER
DOI: 10.1016/j.future.2016.09.006
Keywords
Cloud computing; Activity monitoring; Wearable sensors; Programming framework; Software as a service
Categories
Funding
- European Union [687283]
- Italy project Smart Personal Mobility Systems for Human Disabilities in Future Smart Cities [CN13MO7]
- LOCUBIRehab Project (Polo della Salute, Regione Calabria) [CUP J24E07000400005]
- China project Smart Personal Mobility Systems for Human Disabilities in Future Smart Cities [2015DFG12210]
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This paper proposes Activity as a Service (Activity-aaService), a full-fledged cyber-physical framework to support community, on-line and off-line human activity recognition and monitoring in mobility. Activity-aaService is able to address the current lack of Cloud-Assisted Body Area Networks platforms and applications supporting monitoring and analysis of human activity for single individuals and communities. Activity-aaService is built atop the BodyCloud platform so enabling efficient BSN-based sensor data collection and local processing (Body-side), high performance computing of collected sensor data and data storing on the Cloud (Cloud-side), workflow-based programming of data analysis (Analyst-side), and advanced visualization of results (Viewer-side). Specifically, it provides specific, powerful and flexible programming abstractions for the rapid prototyping of efficient human activity-oriented applications. The effectiveness of the proposed framework has been demonstrated through the development of several prototypes related to physical activity monitoring, step counting, physical energy estimation, automatic fall detection, and smart wheelchair support. Finally, performance evaluation of the proposed framework at the Body-side of the activity classification has been carried out by analyzing processing load, data transmission time, CPU usage, memory footprint, and battery consumption using four heterogeneous mobile devices representing low, medium and high performance mobile platforms. (C) 2016 Elsevier B.V. All rights reserved.
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