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Title: Spatio-temporal data analysis for human daily life activities
Authors: Saeed Ullah, Kashif Rizwan, Nasir Ayub, Nadeem Mahmood
Journal: ARPN Journal of Engineering and Applied Sciences
Publisher: Khyber Medical College, Peshawar
Country: Pakistan
Year: 2020
Volume: 15
Issue: 24
Language: English
Pakistan currently has the largest percentage of young people in its history that makes Pakistan one of the youngest country in the world and second in Asia Pacific region. To understand the macro level pattern of daily life activities for everyone can reveal significant information about people of a particular region. This information at the persons’ own end can be used to adapt a desirable, more healthy and smart options to plan further. On the other hand this information if used by mass planning and governments to promote and plan future strategies in wide range. This study entangles a case study for the daily life activities of Pakistani peoples. In Pakistan there is no such platform exists where people can understand the life pattern of their daily life activities with respect to time and location. We used dynamic flowing bubble graph technique (Force Directed Graph) and scatter plots to observe and analyse human daily life activities. We used 20 volunteers of age group between 19 to 29 years residents of Islamabad/ Rawalpindi. We modeled spatial and temporal features of data by catering 18 distinct daily life activities of each person. A dataset generated with 6 attributes having 709 daily life activity instances of volunteers. This comprises a web based application coupled with a mobile application to represent the human daily life activities using force-directed graph. Results shows the desired offline analysis of Pakistani peoples’ daily life activities.
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