Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/6223
Title: Implementing IoT-adaptive fuzzy neural network model enabling service for supporting fashion retail
Authors: Ir. Dr. CHAN Chi On 
Lau, H. C. W. 
Fan, Youqing 
Issue Date: 2020
Source: Proceedings of the 4th International Conference on Machine Learning and Soft Computing, Jan. 2020, pp. 19-24.
Conference: 4th International Conference on Machine Learning and Soft Computing 
Abstract: The fashion industry operates in a fast moving and dynamic environment which requires fashion designers to respond to market trends continuously. This study investigates potential for application of Internet of Things (IoT) in fashion retail. Customer in-store behaviors may reflect their hidden preferences. This study is based on use of IoT as a framework of data collection tools to capture customer behaviors in-store. Artificial intelligence (AI) such Fuzzy logic and Adaptive Neuro-Fuzzy Inference System (ANFIS) are used to analyze customer purchasing intentions and simulation will be used to illustrate the model [1]. This study shows that IoT can obtain the required data of customer behaviors and use AI to analyze the preferences. It can be used in-store to help salespersons to respond to customer needs faster and accurately. The data obtained after analyzing can be used in supply chain planning.
Type: Conference Paper
URI: http://hdl.handle.net/20.500.11861/6223
DOI: 10.1145/3380688.3380692
Appears in Collections:Business Administration - Publication

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