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

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Udgivet i:Algorithms vol. 18, no. 1 (2025), p. 30
Hovedforfatter: Liu, Binglin
Andre forfattere: Li, Qian, Zheng, Zhihua, Huang, Yanjia, Deng, Shuguang, Huang, Qiongxiu, Liu, Weijiang
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MDPI AG
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100 1 |a Liu, Binglin  |u 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 
245 1 |a A Review of Multi-Source Data Fusion and Analysis Algorithms in Smart City Construction: Facilitating Real Estate Management and Urban Optimization 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a 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. 
653 |a Smart cities 
653 |a Innovations 
653 |a Data analysis 
653 |a Real estate 
653 |a Spatial data 
653 |a Spatial analysis 
653 |a Urban planning 
653 |a Decision making 
653 |a Privacy 
653 |a Optimization 
653 |a Cities 
653 |a Algorithms 
653 |a Data integration 
653 |a Sustainable development 
653 |a Machine learning 
653 |a Real time 
653 |a Interdisciplinary studies 
653 |a Multisensor fusion 
700 1 |a Li, Qian  |u School of Computer and Information Engineering, Guangxi Vocational Normal University, Nanning 530007, China 
700 1 |a Zheng, Zhihua  |u Guangxi Natural Resources Information Center, Nanning 530021, China 
700 1 |a Huang, Yanjia  |u Guangxi City Survey Technology Co., Ltd., Nanning 530002, China 
700 1 |a Deng, Shuguang  |u 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 
700 1 |a Huang, Qiongxiu  |u Guangxi Chaotu Information Technology Co., Ltd., Nanning 530023, China 
700 1 |a Liu, Weijiang  |u College of Engineering, City University of Hong Kong, Hong Kong 999077, China; <email>lliuweiji2-c@my.cityu.edu.hk</email> 
773 0 |t Algorithms  |g vol. 18, no. 1 (2025), p. 30 
786 0 |d ProQuest  |t Engineering Database 
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856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3159222452/fulltext/embedded/75I98GEZK8WCJMPQ?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3159222452/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch