Forecasting Crowd Counts with Wi-Fi Systems: Univariate, Non-Seasonal Models

Recently, event organizers and researchers have advocated the development of novel technologies supporting crowd control, notably for public events. This paper presents a crowd monitoring system based on probe requests (PRs), which are Wi-Fi packets smartphones send periodically. By estimating the global rate at which nearby smartphones send PRs, Wi-Fi sensors can estimate crowd counts. The core contribution of this paper is a computationally tractable method that forecasts crowd counts up to thirty minutes in the future, with forecasts becoming available as soon as two hours of data are available. The forecasting method relies on autoregressive integrated moving average (ARIMA) models. Contributions also include two methods that compute prediction intervals associated with the forecasts, one of which is based upon generalized autoregressive conditional heteroskedasticity (GARCH) models. Recent real-world data from Winter Wonders 2018/2019 (an event that took place in Brussels, Belgium) notably demonstrate that the proposed forecasting method outperforms its immediate variations as well as baseline models (i.e., random walk models).

• Record URL:
  http://dx.doi.org/10.1109/TITS.2020.2992101
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Supplemental Notes:
  • Copyright © 2021, IEEE.
• Authors:
  • Determe, J F
  • Singh, U
  • Horlin, F
  • De Doncker, P
• Publication Date: 2021-10

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 6407-6419
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 22
  • Issue Number: 10
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1524-9050
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979

Subject/Index Terms

• TRT Terms: Crowds; Crowdsourcing; Pedestrian counts; Traffic counting; Traffic forecasting
• Geographic Terms: Brussels (Belgium)
• Subject Areas: Pedestrians and Bicyclists; Safety and Human Factors; Security and Emergencies;

Filing Info

• Accession Number: 01785091
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 21 2021 11:12AM