Green, Pervasive, and Cloud Computing – GPC 2020 Workshops

Urban data can make cities and transport systems more responsive—but collecting, analyzing, and sharing it raises demanding questions about privacy, prediction, and reliability. These proceedings bring together research on those challenges, with focused studies spanning urban computing, intelligent transportation, and social computing.

Research across connected systems

Drawn from the workshops of GPC 2020, the volume gathers eight peer-reviewed papers selected from conference submissions. Rather than following one continuous argument, it offers distinct investigations into the technologies and methods shaping data-rich urban environments.

Privacy, mobility, and urban data

Topics include differential privacy for mobile crowdsensing, visualization for logistics customer maintenance, and machine-learning approaches to short-term traffic-speed prediction. The privacy-focused work examines how spatial data can be released with protection while retaining usefulness for counting queries.

Intelligent transportation in practice

The transportation papers consider privacy-preserving data collection in vehicular networks, dedicated-lane strategies for connected and automated vehicles, traffic-volume forecasting, and recovery of missing traffic-velocity data. A further study explores how text length affects text-classification models. Together, these contributions show the range of analytical problems that arise when computing meets transport infrastructure.

For readers following applied computing research

Researchers, graduate students, and practitioners in urban computing, transportation systems, data privacy, and machine learning will find concise, topic-specific studies to consult and compare. The proceedings are particularly relevant to readers looking for research examples that connect computational methods with real-world mobility and city-data questions.