Towards a mobile and context-aware framework from crowdsourced data
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 tr...
| Main Authors: | , , , , , |
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| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
IEEE
2014
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| Online Access: | http://irep.iium.edu.my/58187/ http://irep.iium.edu.my/58187/1/58187-Towards%20a%20mobile%20and%20context-aware%20framework%20from%20crowdsourced%20data-edited.pdf http://irep.iium.edu.my/58187/2/58187-Towards%20a%20mobile%20and%20context-aware%20framework%20from%20crowdsourced%20data_SCOPUS.pdf |
| _version_ | 1848785066347462656 |
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| author | Ahmad, Akhlaq Rahman, Md Abdur Afyouni, Imad Rehman, Faizan Ur Sadiq, Bilal Wahiddin, Mohamed Ridza |
| author_facet | Ahmad, Akhlaq Rahman, Md Abdur Afyouni, Imad Rehman, Faizan Ur Sadiq, Bilal Wahiddin, Mohamed Ridza |
| author_sort | Ahmad, Akhlaq |
| building | IIUM Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T16:47:14Z |
| format | Proceeding Paper |
| id | iium-58187 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T16:47:14Z |
| publishDate | 2014 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-581872020-06-04T08:46:23Z http://irep.iium.edu.my/58187/ Towards a mobile and context-aware framework from crowdsourced data Ahmad, Akhlaq Rahman, Md Abdur Afyouni, Imad Rehman, Faizan Ur Sadiq, Bilal Wahiddin, Mohamed Ridza T Technology (General) 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. IEEE 2014 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/58187/1/58187-Towards%20a%20mobile%20and%20context-aware%20framework%20from%20crowdsourced%20data-edited.pdf application/pdf en http://irep.iium.edu.my/58187/2/58187-Towards%20a%20mobile%20and%20context-aware%20framework%20from%20crowdsourced%20data_SCOPUS.pdf Ahmad, Akhlaq and Rahman, Md Abdur and Afyouni, Imad and Rehman, Faizan Ur and Sadiq, Bilal and Wahiddin, Mohamed Ridza (2014) Towards a mobile and context-aware framework from crowdsourced data. In: 2014 The 5th International Conference on Information and Communication Technology for The Muslim World (ICT4M), 17th-18th November 2014, Kuching, Sarawak, Malaysia. http://ieeexplore.ieee.org/document/7020672/ 10.1109/ICT4M.2014.7020672 |
| spellingShingle | T Technology (General) Ahmad, Akhlaq Rahman, Md Abdur Afyouni, Imad Rehman, Faizan Ur Sadiq, Bilal Wahiddin, Mohamed Ridza Towards a mobile and context-aware framework from crowdsourced data |
| title | Towards a mobile and context-aware framework from crowdsourced data |
| title_full | Towards a mobile and context-aware framework from crowdsourced data |
| title_fullStr | Towards a mobile and context-aware framework from crowdsourced data |
| title_full_unstemmed | Towards a mobile and context-aware framework from crowdsourced data |
| title_short | Towards a mobile and context-aware framework from crowdsourced data |
| title_sort | towards a mobile and context-aware framework from crowdsourced data |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/58187/ http://irep.iium.edu.my/58187/ http://irep.iium.edu.my/58187/ http://irep.iium.edu.my/58187/1/58187-Towards%20a%20mobile%20and%20context-aware%20framework%20from%20crowdsourced%20data-edited.pdf http://irep.iium.edu.my/58187/2/58187-Towards%20a%20mobile%20and%20context-aware%20framework%20from%20crowdsourced%20data_SCOPUS.pdf |