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research-article

EPICGen: an experimental platform for indoor congestion generation and forecasting

Published: 01 July 2021 Publication History

Abstract

Effectively and accurately forecasting the congestion in indoor spaces has become particularly important during the pandemic in order to reduce the risk of exposure to airborne viruses. However, there is a lack of readily available indoor congestion data to train such models. Therefore, in this demo paper we propose EPICGen, an experimental platform for indoor congestion generation to support congestion forecasting in indoor spaces. EPICGen consists of two components: (i) Grid Overlayer, which models the floor plans of buildings; and (ii) Congestion Generator, a realistic indoor congestion generator. We demonstrate EPICGen through an intuitive map-based user interface that enables end-users to customize the parameters of the system and visualize generated datasets.

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Cited By

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  • (2023)Recommending the Least Congested Indoor-Outdoor Paths without Ignoring TimeProceedings of the 18th International Symposium on Spatial and Temporal Data10.1145/3609956.3609969(121-130)Online publication date: 23-Aug-2023

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      cover image Proceedings of the VLDB Endowment
      Proceedings of the VLDB Endowment  Volume 14, Issue 12
      July 2021
      587 pages
      ISSN:2150-8097
      Issue’s Table of Contents

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      VLDB Endowment

      Publication History

      Published: 01 July 2021
      Published in PVLDB Volume 14, Issue 12

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      • (2023)Recommending the Least Congested Indoor-Outdoor Paths without Ignoring TimeProceedings of the 18th International Symposium on Spatial and Temporal Data10.1145/3609956.3609969(121-130)Online publication date: 23-Aug-2023

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