Citation

Tan, Ian Kim Teck and Yaik, Ooi Boon and Sheng, Ooi Boon (2016) Predicting Shopper Volume Using ARIMA on Public Wi-Fi Signals. Information, 19 (8(A)). pp. 3295-3300. ISSN 1343-4500

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Abstract

Shopping malls are being built at a rapid pace in many South East Asia 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.

Item Type:	Article
Uncontrolled Keywords:	Shopping mall, shopper volume, ARIMA, Wi-Fi, prediction
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	21 Nov 2017 09:21
Last Modified:	21 Nov 2017 09:21
URII:	http://shdl.mmu.edu.my/id/eprint/6504

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