Frontiers in Cyber-Physical-Social Data Fusion in Smart Cities

Dear colleagues,

The proliferation of low-cost sensors coupled with their widening deployment and citizen sensing is contributing to the deluge of data sources that can drive the smart cities phenomenon. Advances made in the Internet of Things and associated cyber-physical systems and other disruptive technological trends such as Big Data analytics and edge computing are widely accepted as the enabling solutions to the numerous challenges affecting smart city services. However, solutions need to address the diversity in data sources and resulting datasets, which includes multiple modalities, with different representations, distributions and scale of measure (ordinal or nominal scale). Potential sources of data include not only physical sensor, actuator deployments that generate mostly numerical data streams as continuous time series, but also social networks (e.g. Twitter, Foursquare) that provide data in both textual and numeric modalities. Knowledge derivation in such diverse and heterogeneous, though potentially connected datasets is a pressing research issue and calls for advanced data mining and machine learning-oriented techniques.
The goal of this Special Issue is to seek original articles examining the state-of-the-art, open challenging research issues, new research results, and solutions in Cyber-Physical Social Data Fusion. Articles can address both theoretical and practical aspects, either from a methodological or from an application perspective.

Topics of interest include but are not limited to the following:

• Techniques for spatio-temporal big data analysis of smart city datasets
• Intelligent data fusion techniques for multimodal data streams in smart cities
• Context-awareness for smart environments
• Environment-aware application, analytics and visualisation
• Large-scale smart city data fusion techniques with computational intelligence
• Pattern derivation through visualisation
• Correlation between physical and social data streams
• Applications based on heterogeneous data in smart city domains, such as eHealth, traffic, infrastructures, pollution, etc.
• Smart city frameworks for multimodal data

Dr. Suparna De
Dr. Zhipeng Cai
Dr. Wei Wang
Dr. Maria Bermudez Edo
Guest Editors

Manuscript Submission Information

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