Ubiquitous measurement methods of long‐term nursing bed resource allocation based on multi‐sensor social internet of things. Issue 1 (9th November 2020)

• Record Type: Journal Article
• Authors: Li, Xingjiang; Zhao, Xiaodong; Bai, Jie
• Is Part Of: Internet technology letters. Volume 6:Issue 1(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-11-09
• Subjects: data mining -- neural networks -- nursing bed -- measurement method -- resource allocation -- social internet of things; Internet -- Periodicals; 004.67805
• DOI: 10.1002/itl2.253
• Languages: English
• ISSNs: 2476-1508

Abstract

Abstract : This article starts from the service population of long‐term care beds and estimates the spatial distribution of long‐term care beds in the area. At the same time, combined with the spatial distribution of beds in the area, the supply of long‐term care beds is based on the division of service areas. Long‐term care institutions are facilities for the care and care of disabled elderly people. The beds are long‐term care beds, and the clients are mainly elderly people who cannot take care of themselves. The demand for long‐term care beds is mainly related to the number of elderly people. The elderly population in this article mainly refers to the resident population aged 60 and above. Based on the layout map of the resident population aged 60 and above, combined with the area of the administrative divisions of the village committees, the population density of each village committee is calculated to produce a schematic diagram. We use the data connection analysis model and the pattern finding algorithm to optimize the traditional methodologies.