DocumentCode
3057747
Title
Application of OpenStreetMap Data in Ambulance Location Problem
Author
Azizan, Mohd Hafiz ; Lim, Cheng Siong ; Hatta, W. A Lutfi W M ; Gan, Lian Chai
Author_Institution
Dept. of Mechatron. & Robot., Univ. Teknol. Malaysia, Johor Bahru, Malaysia
fYear
2012
fDate
24-26 July 2012
Firstpage
321
Lastpage
325
Abstract
Locating a group of ambulances to get optimum coverage can ensure the efficiency of emergency medical services (EMS) delivery. Maximal covering location problem (MCLP) is a static location model which has been proven as a cost-effective tool in the development of EMS system. Meanwhile, OpenStreetMap (OSM) has gained popularity among the researchers because of its open-source status. Due to the lack of study of its application in EMS, its presence is not much recognized and valued as it should be. In this paper, we present our solution of MCLP to locate a number of ambulances to maximize the coverage of local demands by using OSM geodata. We also discuss on the technique to integrate the local population data within the map. The results show that the ambulance location problem can be solved successfully by using OSM geodata.
Keywords
cartography; emergency services; facility location; medical information systems; public domain software; EMS delivery; EMS system; MCLP; OSM geodata; OpenStreetMap data; ambulance location problem; cost-effective tool; emergency medical service; local population data; maximal covering location problem; open-source status; optimum coverage; static location model; Data mining; Geographic information systems; Global Positioning System; Medical services; Roads; Standards; Subspace constraints; Ambulance Service; Location-allocation; Maximal Covering Location Problem (MCLP); OpenStreetMap;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence, Communication Systems and Networks (CICSyN), 2012 Fourth International Conference on
Conference_Location
Phuket
Print_ISBN
978-1-4673-2640-7
Type
conf
DOI
10.1109/CICSyN.2012.66
Filename
6274362
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