Research on Grid Management Mode of Super-Large Cities Under Digital Background
Analysis Based on the Operation and Management of “Sui Zhi Guan”
- DOI
- 10.2991/978-94-6463-016-9_19How to use a DOI?
- Keywords
- digital management; Super-large cities; Grid; Urban management; Sui Zhi guan
- Abstract
The wave of digitization represented by technologies such as artificial intelligence, the Internet of Things, and big data is sweeping the world, profoundly affecting urban management and development. The Guangzhou Municipal Government took the initiative to adapt to the new situation and began to fully invest in the construction of the “Suizhiguan” urban operation and management center, dividing the entire urban area into nearly 20,000 data “grids”, in order to solve the large-scale, multi-agent super-large city Management issues. This article will start from the technical analysis premise of digital empowerment of city management, and use the “one network and four platforms” smart management model constructed by “Suizhiguan” as the core of the research. Finally, it provides decision support for the current deficiencies in the digital grid management of super large cities.
- 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 - Anqi Xu AU - Aikeda Adili AU - Liuyun Chen PY - 2022 DA - 2022/12/07 TI - Research on Grid Management Mode of Super-Large Cities Under Digital Background BT - Proceedings of the 2022 2nd International Conference on Public Management and Intelligent Society (PMIS 2022) PB - Atlantis Press SP - 152 EP - 159 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-016-9_19 DO - 10.2991/978-94-6463-016-9_19 ID - Xu2022 ER -