Intelligent Wearable Elderly Service Platform Design Based on Big Data
Authors
Yuntong Zhong1, *, Kehong Chen2, Jiaqi Chen3
1Department of Accounting, Guangdong University of Technology, Guangzhou, Guangdong, China
2Department of Computing, Guangdong University of Technology, Guangzhou, Guangdong, China
3Department of Business Administration, Guangdong University of Technology, Guangzhou, Guangdong, China
*Corresponding author.
Email: zyt173649887@163.com
Corresponding Author
Yuntong Zhong
Available Online 23 December 2022.
- DOI
- 10.2991/978-94-6463-034-3_102How to use a DOI?
- Keywords
- Big Data; Smart Wearable Devices; Smart Aging; Aging; Aging Services
- Abstract
China has now entered the stage of rapid aging and urgently needs to develop a new model of senior care. Smart wearable senior care platform not only can effectively solve the current aging problem in China, but also can make full use of big data and other technologies to innovate the mode of traditional senior care, which is the trend of future development. By analyzing the demand of smart senior care, this paper specifies the operation mode of the smart wearable senior care platform under big data, and provides a new development direction for the senior care industry under big data.
- 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 - Yuntong Zhong AU - Kehong Chen AU - Jiaqi Chen PY - 2022 DA - 2022/12/23 TI - Intelligent Wearable Elderly Service Platform Design Based on Big Data BT - Proceedings of the 2022 3rd International Conference on Big Data and Informatization Education (ICBDIE 2022) PB - Atlantis Press SP - 994 EP - 1002 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-034-3_102 DO - 10.2991/978-94-6463-034-3_102 ID - Zhong2022 ER -