Data Visualization to Explore Improving Decision-Making within Hajj Services
Nemshan Alharthi and
Adnan Gutub
Scientific Modelling and Research, 2017, vol. 2, issue 1, 9-18
Abstract:
This paper proposes improving Hajj services gaining advantage from the development of the exploratory data visualization technology. We will illustrate the latest view on data visualization, its difference from the normal explanatory figures and how it is needed as a current effective exploration decision making solution from the massive amount of data (big data) gathered from all agencies serving Hajj. Using the data visualization approach to gain and share insight by presenting some real exploratory global experience examples. We apply the technique to visualize some real data from last year Hajj season representing the results of a study on what pilgrims mostly do in their camping in Mina (a 4-days Hajj living area) during the peak Hajj days and finding out what are the prevailing habits among these pilgrims based on their nationalities averaged for last three years. We also give a simplified theoretical example to illustrate the concept linking between the different nationalities of pilgrims and their residence in Makkah beside the grand mosque (Al-Masjid Al-Haram). We show another exploratory data visualization example relating a virtual map of Mina to improve civil defence system services providing the various civil defence stations with its specialized most probable needed equipments and number of employees.
Keywords: Data visualization; Big data; Optimization in Hajj; Big data in Hajj; Info-graphics. (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.onlinesciencepublishing.com/index.php/smr/article/view/450/707 (application/pdf)
https://www.onlinesciencepublishing.com/index.php/smr/article/view/450/1321 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:onl:scmare:v:2:y:2017:i:1:p:9-18:id:450
Access Statistics for this article
More articles in Scientific Modelling and Research from Online Science Publishing
Bibliographic data for series maintained by Pacharapa Naka ( this e-mail address is bad, please contact ).