Content area
In the context of the booming construction of smart cities, multi-source data fusion and analysis algorithms play a key role in optimizing real estate management and improving urban efficiency. In this review, we comprehensively and systematically review the relevant algorithms, covering the types, characteristics, fusion techniques, analysis algorithms, and their synergies of multi-source data. We found that multi-source data, including sensors, social media, citizen feedback, and GIS data, face challenges such as data quality and privacy security when being fused. Data fusion algorithms are diverse and have their own advantages and disadvantages. Data analysis algorithms help urban management in areas such as spatial analysis and deep learning. Algorithm collaboration can improve decision-making accuracy and efficiency and promote the rational allocation of urban resources. In the future, algorithm development will focus on data quality, real-time, deep mining, interdisciplinary research, privacy protection, and collaborative application expansion, providing strong support for the sustainable development of smart cities.
Details
; Li, Qian 2 ; Zheng, Zhihua 3 ; Huang, Yanjia 4 ; Deng, Shuguang 1 ; Huang, Qiongxiu 5 ; Liu, Weijiang 6
1 School of Geography and Planning, Nanning Normal University, Nanning 530001, China; Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning 530001, China
2 School of Computer and Information Engineering, Guangxi Vocational Normal University, Nanning 530007, China
3 Guangxi Natural Resources Information Center, Nanning 530021, China
4 Guangxi City Survey Technology Co., Ltd., Nanning 530002, China
5 Guangxi Chaotu Information Technology Co., Ltd., Nanning 530023, China
6 College of Engineering, City University of Hong Kong, Hong Kong 999077, China;