Capturing users' spatio-temporal context by recognizing their interests, locations, history and activities, and thereafter providing context-aware services is a challenging task. In this paper, we propose a spatio...
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Capturing users' spatio-temporal context by recognizing their interests, locations, history and activities, and thereafter providing context-aware services is a challenging task. In this paper, we propose a spatio-temporal zoning model that takes different context dimensions into account and try to recommend necessary services to users in a personalized way. First, we propose a generic zoning model with unrestricted set of contexts where both spatial and temporal dimensions are relaxed, followed by two semi-restricted zoning models in which either spatial or temporal dimension is relaxed, while the other one is restricted. Finally, we show the model requiring restricted spatio-temporal zoning that applies to the scenario where millions of users need to perform some activities that have to be performed in a certain location and at a certain temporal period. We use the above zoning model for Hajj and Umrah events to define pilgrim's spatio-temporal contexts by capturing their real-time and historic activities through their smartphones' sensory data. This allows to intelligently recommend a set of necessary services to the users. We present a few of the implementations introduced in our proposed system.
We propose a context aware framework that offers a set of cloud-based services to support a very large Hajj and Umrah crowd by capturing their contexts using smartphones. The proposed framework captures the individual...
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We propose a context aware framework that offers a set of cloud-based services to support a very large Hajj and Umrah crowd by capturing their contexts using smartphones. The proposed framework captures the individual's context, provides a set of adapted services, and allows being in touch with a subset of one's community of interest. We leverage the spatiotemporal sensory data captured by our framework to define users' contexts for optimized services. Our proposed framework is also envisioned to assist the Hajj and Umrah authorities to (1) improve Hajj & Umrah documentation, (2) improve Hajj organization through better understanding of pilgrims' (individual and crowd) spatial and temporal behavior and needs, and (3) protect pilgrims' environment through environmental monitoring. In particular, the developed methods, techniques, and algorithms will support the pilgrimage quality of experience. We have tested our system through end-user subjects and due to apply for the upcoming Hajj events. We present our implementation details and the general impression of end users about our system.
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