Research on Improving Elderly Health Service System by Computer Artificial Intelligence Technology
- DOI
- 10.2991/978-94-6463-200-2_79How to use a DOI?
- Keywords
- computer; artificial intelligence; the elderly; health service system
- Abstract
This article first analyzes the needs of the elderly, their families, community health service personnel and volunteers. Then this paper innovatively uses computer artificial intelligence technology Microsoft NET platform, Visual Studio 2013 integrated development environment, C# language, MySQL 5.7 database and ASP NETMVC development framework to develop the elderly health service system. The platform designs the framework and system function modules of the elderly health service system based on intelligent mobile products. After the system is completed, it is deployed on the Alibaba Cloud server. Experiments show that the system can meet various information needs of elderly health services accurately, efficiently and timely with the help of computer artificial intelligence technology. The system has the characteristics of information authority and credibility, and content can be customized.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yan Zhang AU - Li Qi AU - Yi Qu AU - Weixin Zhang AU - Chunmiao Xu AU - Tian Song AU - Mengyao Wang PY - 2023 DA - 2023/07/26 TI - Research on Improving Elderly Health Service System by Computer Artificial Intelligence Technology BT - Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023) PB - Atlantis Press SP - 768 EP - 776 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6463-200-2_79 DO - 10.2991/978-94-6463-200-2_79 ID - Zhang2023 ER -