Predicting shopper volume using ARIMA on public Wi-Fi signals

Ian K. T. Tan*, Ooi Boon Yaik, Ooi Boon Sheng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Shopping malls are being built at a rapid pace in many South East Asian countries and it has become competitive to attract and maintain shoppers. Being able to know the volume of shoppers and predicting the volume will greatly benefit mall management. In this paper, we present shopper volume monitoring using Wi-Fi signal detectors and use the data obtained from it to derive an Auto-Regressive Integrated Moving Average (ARIMA) model for shopper volume prediction.

Original languageEnglish
Pages (from-to)3295-3300
Number of pages6
JournalInformation - An International Interdisciplinary Journal in English, Japanese and Chinese
Issue number18A
Publication statusPublished - Aug 2016


  • Arima
  • Prediction
  • Shopper volume
  • Shopping mall
  • Wi-fi

ASJC Scopus subject areas

  • Information Systems


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