A Review of Multi-Source Data Fusion and Analysis Algorithms in Smart City Construction: Facilitating Real Estate Management and Urban Optimization

作     者：Liu, Binglin Li, Qian Zheng, Zhihua Huang, Yanjia Deng, Shuguang Huang, Qiongxiu Liu, Weijiang 

作者机构：Nanning Normal Univ Sch Geog & Planning Nanning 530001 Peoples R China Nanning Normal Univ Key Lab Environm Change & Resources Use Beibu Gulf Minist Educ Nanning 530001 Peoples R China Guangxi Vocat Normal Univ Sch Comp & Informat Engn Nanning 530007 Peoples R China Guangxi Nat Resources Informat Ctr Nanning 530021 Peoples R China Guangxi City Survey Technol Co Ltd Nanning 530002 Peoples R China Guangxi Chaotu Informat Technol Co Ltd Nanning 530023 Peoples R China City Univ Hong Kong Coll Engn Hong Kong 999077 Peoples R China 

出 版 物：《ALGORITHMS》 (Algorithms)

年 卷 期：2025年第18卷第1期

页      面：30-30页

核心收录：

基　　金：Guangxi Key R&D Project "Research and Application of Key Technologies for Natural Resources Knowledge Graph Construction"  Guangxi Natural Science Foundation Project "Research on Collaborative Services of Distributed Spatial Information Systems for Group Intelligence" [2024GXNSFAA010341] Nanning Normal University Demonstration Modern Industrial College Nanning Normal University Characteristic Undergraduate College Construction and College Teaching Quality and Reform Engineering Project-Undergraduate Education and Teaching Key Project Nanning Normal University Doctoral Research Startup Project Guike AB24010057 

主　　题：smart city construction multi-source data fusion data analysis algorithm real estate management urban optimization 

摘      要：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.