IoT data acquisition in fashion retail application: Fuzzy logic approach

Abstract

The fashion industry operates in a fast moving and dynamic environment which requires fashion designers to respond to market trends continuously. This paper investigates potential for application of Internet of Things (IoT) and the related state-of-the-art research efforts in fashion retail. Non-purchasing behaviors are seldom recorded in retail. What customers are interested in may not reflect totally in products they actually bought and are recorded in Point of Sales (POS). However, some of in-store behaviors may reflect their hidden preferences. These data were not easy to record in the past. This study is relevant to use of sensing devices that can capture in-store customer behaviors and transmit the same through wireless network to cloud. A data analytics model with fuzzy logic approach is developed to generate data of purchasing intentions. The paper fills the literature gap on the use of specific non-purchase data in retail stores. With the aid of fuzzy logic, behavioral intentions can be used by salespersons for recommending products to customers and guide supply chain planning. It also enriches the application of IoT in fashion retail environment. The findings from this research can be applied to other products in the retail industry.