Key points are not available for this paper at this time.
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.
Orchi et al. (Wed,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: