Towards a mobile and context-aware framework from crowdsourced data

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...

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Main Authors: Ahmad, Akhlaq, Rahman, Md Abdur, Afyouni, Imad, Rehman, Faizan Ur, Sadiq, Bilal, Wahiddin, Mohamed Ridza
Format: Conference or Workshop Item
Language:English
English
Published: IEEE 2014
Subjects:
T Technology (General)
Online Access: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
id iium-58187
recordtype eprints
spelling iium-581872017-09-20T04:22:36Z 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 Conference or Workshop Item 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
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
English
topic T Technology (General)
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
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.
format Conference or Workshop Item
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
title Towards a mobile and context-aware framework from crowdsourced data
title_short 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_sort towards a mobile and context-aware framework from crowdsourced data
publisher IEEE
publishDate 2014
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
first_indexed 2023-09-18T21:22:15Z
last_indexed 2023-09-18T21:22:15Z
_version_ 1777411959995498496

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