A Study on the Location Selection Model for a Remote Image Dispenser Using Machine Learning

초록

One of the phenomena of regional medical disparity is the time gap during late night hours, holidays, and weekends when pharmacies are not operated, and the concentration of pharmacies or stores selling over-the-counter medicines in the metropolitan area. As a way to solve this problem, an image dispenser appeared. There is a restriction that the image dispenser should be installed only in front of a pharmacy. However, if the restrictions are followed, the temporal gap will be resolved, but the phenomenon of concentration in the metropolitan area still exists. Based on these points, this paper proposes and compares the location selection model for the image dispenser in the case where it is installed only in front of the pharmacy and the case where it is installed without being limited to the pharmacy to the policy proponent. Through thesis analysis, the elderly who use primary medical facilities and pharmacies the most were set as the target. As a result of comparing the two models using the number of the elderly population with access to medicines, it was found that the number of cases where the area where the image dispenser was installed was not restricted to a pharmacy was 573% more than the case where the country was restricted to the previous country. This shows that the case where the installation area is not limited to the pharmacy can solve the preceding problem more efficiently. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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