{"title":"多源信息融合促进智能可持续城市的当代调查:新趋势与长期挑战","authors":"Houda Orchi , Abdoulaye Baniré Diallo , Halima Elbiaze , Essaid Sabir , Mohamed Sadik","doi":"10.1016/j.inffus.2024.102667","DOIUrl":null,"url":null,"abstract":"<div><p>The emergence of smart sustainable cities has unveiled a wealth of data sources, each contributing to a vast array of urban applications. At the heart of managing this plethora of data is multisource information fusion (MSIF), a sophisticated approach that not only improves the quality of data collected from myriad sources, including sensors, satellites, social media, and citizen-generated content, but also aids in generating actionable insights crucial for sustainable urban management. Unlike simple data fusion, MSIF excels in harmonizing disparate data sources, effectively navigating through their variability, potential conflicts, and the challenges posed by incomplete datasets. This capability is essential for ensuring the integrity and utility of information, which supports comprehensive insights into urban systems and effective planning. This survey combines hierarchical and multi-dimensional classification to examine how MSIF integrates and analyses diverse datasets, enhancing the operational efficiency and intelligence of urban environments. It highlights the most significant challenges and opportunities presented by MSIF in smart sustainable cities, particularly how it overcomes the limitations of existing approaches in scope and coverage.</p><p>By considering social, economic, and environmental factors, MSIF offers a multidisciplinary approach that is pivotal for advancing sustainable urban development. Recognized as an essential resource for academics and practitioners, this study promotes a new wave of MSIF innovations aimed at improving the cohesion, efficiency, and sustainability of smart cities.</p></div>","PeriodicalId":50367,"journal":{"name":"Information Fusion","volume":"114 ","pages":"Article 102667"},"PeriodicalIF":14.7000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Contemporary Survey on Multisource Information Fusion for Smart Sustainable Cities: Emerging Trends and Persistent Challenges\",\"authors\":\"Houda Orchi , Abdoulaye Baniré Diallo , Halima Elbiaze , Essaid Sabir , Mohamed Sadik\",\"doi\":\"10.1016/j.inffus.2024.102667\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The emergence of smart sustainable cities has unveiled a wealth of data sources, each contributing to a vast array of urban applications. At the heart of managing this plethora of data is multisource information fusion (MSIF), a sophisticated approach that not only improves the quality of data collected from myriad sources, including sensors, satellites, social media, and citizen-generated content, but also aids in generating actionable insights crucial for sustainable urban management. Unlike simple data fusion, MSIF excels in harmonizing disparate data sources, effectively navigating through their variability, potential conflicts, and the challenges posed by incomplete datasets. This capability is essential for ensuring the integrity and utility of information, which supports comprehensive insights into urban systems and effective planning. This survey combines hierarchical and multi-dimensional classification to examine how MSIF integrates and analyses diverse datasets, enhancing the operational efficiency and intelligence of urban environments. It highlights the most significant challenges and opportunities presented by MSIF in smart sustainable cities, particularly how it overcomes the limitations of existing approaches in scope and coverage.</p><p>By considering social, economic, and environmental factors, MSIF offers a multidisciplinary approach that is pivotal for advancing sustainable urban development. Recognized as an essential resource for academics and practitioners, this study promotes a new wave of MSIF innovations aimed at improving the cohesion, efficiency, and sustainability of smart cities.</p></div>\",\"PeriodicalId\":50367,\"journal\":{\"name\":\"Information Fusion\",\"volume\":\"114 \",\"pages\":\"Article 102667\"},\"PeriodicalIF\":14.7000,\"publicationDate\":\"2024-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Fusion\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1566253524004457\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Fusion","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1566253524004457","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
A Contemporary Survey on Multisource Information Fusion for Smart Sustainable Cities: Emerging Trends and Persistent Challenges
The emergence of smart sustainable cities has unveiled a wealth of data sources, each contributing to a vast array of urban applications. At the heart of managing this plethora of data is multisource information fusion (MSIF), a sophisticated approach that not only improves the quality of data collected from myriad sources, including sensors, satellites, social media, and citizen-generated content, but also aids in generating actionable insights crucial for sustainable urban management. Unlike simple data fusion, MSIF excels in harmonizing disparate data sources, effectively navigating through their variability, potential conflicts, and the challenges posed by incomplete datasets. This capability is essential for ensuring the integrity and utility of information, which supports comprehensive insights into urban systems and effective planning. This survey combines hierarchical and multi-dimensional classification to examine how MSIF integrates and analyses diverse datasets, enhancing the operational efficiency and intelligence of urban environments. It highlights the most significant challenges and opportunities presented by MSIF in smart sustainable cities, particularly how it overcomes the limitations of existing approaches in scope and coverage.
By considering social, economic, and environmental factors, MSIF offers a multidisciplinary approach that is pivotal for advancing sustainable urban development. Recognized as an essential resource for academics and practitioners, this study promotes a new wave of MSIF innovations aimed at improving the cohesion, efficiency, and sustainability of smart cities.
期刊介绍:
Information Fusion serves as a central platform for showcasing advancements in multi-sensor, multi-source, multi-process information fusion, fostering collaboration among diverse disciplines driving its progress. It is the leading outlet for sharing research and development in this field, focusing on architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome.