Smart city space simulation based on multidimensional sensing networks and green energy intelligent decision support
• sustainable development and the effective use of green energy have become key issues. • This study aims to explore a smart city spatial simulation method based on multi-dimensional sensing technology • the proposed system can significantly improve the utilization rate of green energy In the context of accelerating global urbanization, the construction of smart cities faces many challenges, among which sustainable development and the effective use of green energy have become key issues. This study aims to explore a smart city spatial simulation method based on multi-dimensional sensing technology and green energy intelligent decision support to improve urban operation efficiency and resource utilization. In this paper, multi-dimensional sensing technology is used to monitor the data of urban environment, energy consumption and traffic flow in real time, and through data fusion and analysis, urban dynamic model is established. Based on this model, a green energy intelligent decision support system is developed, which can evaluate the cost and benefit of various types of renewable energy in real time, and provide reliable information support for city managers. The results show that the proposed system can significantly improve the utilization rate of green energy, optimize energy allocation, and reduce urban carbon emissions. Through simulation analysis, the effect of decision support in different scenarios is verified, which provides an empirical basis for the planning and construction of smart cities. The combination of multi-dimensional sensing technology and intelligent decision support provides a new perspective and a new method for achieving green sustainable development goals.
Authors
- Yilin Lai
Institutions
- Guangdong University Of Finances and Economics (CN)
- Guangdong University of Finance (CN)
Publication Details
- Journal
- Results in Engineering
- Published
- 2025-06-09
- DOI
- https://doi.org/10.1016/j.rineng.2025.105674
- Citations
- 2
- Primary Topic
- Human Mobility and Location-Based Analysis
- Type
- article
- Field-Weighted Citation Impact
- 4.35