A Survey of Data Fusion in Smart City Applications
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Abstract (arXiv)
The advancement of various research sectors such as Internet of Things (IoT), Machine Learning, Data Mining, Big Data, and Communication Technology has shed some light in transforming an urban city integrating the aforementioned techniques to a commonly known term - Smart City. With the emergence of smart city, plethora of data sources have been made available for wide variety of applications. The common technique for handling multiple data sources is data fusion, where it improves data output quality or extracts knowledge from the raw data. In order to cater evergrowing highly complicated applications, studies in smart city have to utilize data from various sources and evaluate their performance based on multiple aspects. To this end, we introduce a multi-perspectives classification of the data fusion to evaluate the smart city applications. Moreover, we applied the proposed multi-perspectives classification to evaluate selected applications in each domain of the smart city. We conclude the paper by discussing potential future direction and challenges of data fusion integration.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 May 2019.
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Citing papers per year: 2021: 2; 2022: 3; 2023: 2; 2024: 2; 2025: 0; 2026: 1.
10 papers.
- 2022Context-aware multi-head self-attentional neural network model for next location predictioncited by 20
- 2022Explainable Artificial Intelligence: Precepts, Methods, and Opportunities for Research in Constructioncited by 4
- 2023Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunitiescited by 4
- 2021ECO: Enabling Energy-Neutral IoT Devices through Runtime Allocation of Harvested Energycited by 3
- 2024Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Sensor Fusioncited by 2
- 2021WiFi Fingerprint Clustering for Urban Mobility Analysiscited by 1
- 2022tinyMAN: Lightweight Energy Manager using Reinforcement Learning for Energy Harvesting Wearable IoT Devicescited by 1
- 2023A survey on deep learning approaches for data integration in autonomous driving systemcited by 1
- 2024A Data-Driven Review of Remote Sensing-Based Data Fusion in Precision Agriculture from Foundational to Transformer-Based Techniquescited by 0
- 2026Heterogeneous Graph Alignment for Joint Reasoning and Interpretabilitycited by 0
- 2026Heterogeneous Graph Alignment for Joint Reasoning and Interpretability30 Jan 2026
- 2024Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Sensor Fusion11 Nov 2024
- 2024A Data-Driven Review of Remote Sensing-Based Data Fusion in Precision Agriculture from Foundational to Transformer-Based Techniques24 Oct 2024
- 2023Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunities13 Jul 2023
- 2023A survey on deep learning approaches for data integration in autonomous driving system17 Jun 2023
- 2022Context-aware multi-head self-attentional neural network model for next location prediction4 Dec 2022
- 2022Explainable Artificial Intelligence: Precepts, Methods, and Opportunities for Research in Construction12 Nov 2022
- 2022tinyMAN: Lightweight Energy Manager using Reinforcement Learning for Energy Harvesting Wearable IoT Devices18 Feb 2022
- 2021WiFi Fingerprint Clustering for Urban Mobility Analysis4 May 2021
- 2021ECO: Enabling Energy-Neutral IoT Devices through Runtime Allocation of Harvested Energy26 Feb 2021