Orchestrating urban footfall prediction: leveraging ai and batch-oriented workflow for smart city application

HIGHLIGHTS

  • What: The work demonstrates ease at which similar systems can be developed given sufficient volume of data and availability of compute power. To address these issues the primary objective of this study is to develop a realtime prediction system for footfall timeseries data collected by Newcastle Urban Observatory (P. 2022). In this work the focus is operationalising the forecasting solution by integrating machine learning with batch-oriented data processing framework.
  • Who: Tom, Komar and Philip, James from the th International Conference on Smart Data and Smart Cities (SDSC), June, Athens, Greece have published the research . . .

     

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