A Contemporary Survey on Multisource Information Fusion for Smart Sustainable Cities: Emerging Trends and Persistent Challenges

IF 14.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Information Fusion Pub Date : 2024-09-04 DOI:10.1016/j.inffus.2024.102667
Houda Orchi , Abdoulaye Baniré Diallo , Halima Elbiaze , Essaid Sabir , Mohamed Sadik
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Abstract

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.

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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
智能可持续城市的出现揭示了丰富的数据源,每种数据源都为大量城市应用做出了贡献。管理这些大量数据的核心是多源信息融合(MSIF),这是一种复杂的方法,不仅能提高从传感器、卫星、社交媒体和市民生成的内容等各种来源收集的数据的质量,还能帮助生成对可持续城市管理至关重要的可操作见解。与简单的数据融合不同,MSIF 擅长协调不同的数据源,有效克服数据源的可变性、潜在冲突以及不完整数据集带来的挑战。这种能力对于确保信息的完整性和实用性至关重要,有助于全面了解城市系统和有效规划。本调查结合了分层和多维分类,研究 MSIF 如何整合和分析不同的数据集,从而提高城市环境的运行效率和智能化程度。通过考虑社会、经济和环境因素,MSIF 提供了一种多学科方法,对推进城市可持续发展至关重要。作为学术界和实践者的重要资源,本研究推动了 MSIF 创新的新浪潮,旨在提高智慧城市的凝聚力、效率和可持续性。
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来源期刊
Information Fusion
Information Fusion 工程技术-计算机:理论方法
CiteScore
33.20
自引率
4.30%
发文量
161
审稿时长
7.9 months
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.
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