Please use this identifier to cite or link to this item:
|Title:||Implementing IoT-adaptive fuzzy neural network model enabling service for supporting fashion retail|
|Authors:||Ir. Dr. CHAN Chi On |
Lau, H. C. W.
|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 . 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.|
|Appears in Collections:||Business Administration - Publication|
Find@HKSYU Show full item record
checked on Dec 2, 2022
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.