期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2021
卷号：12
期号：3
页码：626-635
DOI：10.14569/IJACSA.2021.0120374
出版社：Science and Information Society (SAI)
摘要：Everywhere, centers, laboratories, hospital and pharmacy have faced many challenges to delivery quality of health service due to constraints related to limited availability of resources such as drugs, places, equipments and specialists, often in health deficit with increasing number of patients, for instance during COVID-19 pandemic. Late information on these constraints from health service centers will play negatively on service quality because of time delayed between requesting service on place and the response to delivery safe service. All these problems don’t strengthen prevention or fighting against diseases in a region. This paper proposes a data research framework in a NoSQL database based on GIS data, containing an abstract table that could be inherited or specialized to any adopted GIS solution leading to a central data management instead of installing several database sites. The central database accepts data updated in back office by data owner and allows data research based on meshing Techniques and the map-reduce algorithm in front office. Variant meshing techniques have been presented to clustering GIS data with associated definitions of the content of map-reduce in order to improve processing time. In application in health service, the experimental results reveal that this system contributes to improve drug management in pharmacies and could be also used in others fields such as Finance, Education and Shopping through agencies spread over the territory, to strengthen national information systems and harmonised data.
关键词：Map-reduce; big data; digital health; classification; Geographic Information System (GIS); COVID-19; Spark; Mon-goDb; NewSQL;NoSQL
