Implementing IoT-adaptive fuzzy neural network model enabling service for supporting fashion retail

Chi On Chan; H. C. W. Lau; Youqing Fan

doi:10.1145/3380688.3380692

Implementing IoT-adaptive fuzzy neural network model enabling service for supporting fashion retail

Chi On Chan, H. C. W. Lau, Youqing Fan

Western Sydney University

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

6 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the 4th International Conference on Machine Learning and Soft Computing (ICMLSC 2020), Haiphong City, Vietnam, 17-19 January 2020
Publisher	Association for Computing Machinery
Pages	19-24
Number of pages	6
ISBN (Print)	9781450376310
DOIs	https://doi.org/10.1145/3380688.3380692
Publication status	Published - 2020
Event	International Conference on Machine Learning and Soft Computing - Duration: 17 Jan 2020 → …

Conference

Conference	International Conference on Machine Learning and Soft Computing
Period	17/01/20 → …

Keywords

Internet of things
artificial intelligence
consumer behavior
fashion merchandising
fuzzy logic
machine learning

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1145/3380688.3380692

Cite this

Chan, C. O., Lau, H. C. W., & Fan, Y. (2020). Implementing IoT-adaptive fuzzy neural network model enabling service for supporting fashion retail. In Proceedings of the 4th International Conference on Machine Learning and Soft Computing (ICMLSC 2020), Haiphong City, Vietnam, 17-19 January 2020 (pp. 19-24). Association for Computing Machinery. https://doi.org/10.1145/3380688.3380692

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title = "Implementing IoT-adaptive fuzzy neural network model enabling service for supporting fashion retail",

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.",

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author = "Chan, {Chi On} and Lau, {H. C. W.} and Youqing Fan",

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booktitle = "Proceedings of the 4th International Conference on Machine Learning and Soft Computing (ICMLSC 2020), Haiphong City, Vietnam, 17-19 January 2020",

publisher = "Association for Computing Machinery",

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Chan, CO, Lau, HCW & Fan, Y 2020, Implementing IoT-adaptive fuzzy neural network model enabling service for supporting fashion retail. in Proceedings of the 4th International Conference on Machine Learning and Soft Computing (ICMLSC 2020), Haiphong City, Vietnam, 17-19 January 2020. Association for Computing Machinery, pp. 19-24, International Conference on Machine Learning and Soft Computing, 17/01/20. https://doi.org/10.1145/3380688.3380692

Implementing IoT-adaptive fuzzy neural network model enabling service for supporting fashion retail. / Chan, Chi On; Lau, H. C. W.; Fan, Youqing.
Proceedings of the 4th International Conference on Machine Learning and Soft Computing (ICMLSC 2020), Haiphong City, Vietnam, 17-19 January 2020. Association for Computing Machinery, 2020. p. 19-24.

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

TY - GEN

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AU - Chan, Chi On

AU - Lau, H. C. W.

AU - Fan, Youqing

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N2 - 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.

AB - 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.

KW - Internet of things

KW - artificial intelligence

KW - consumer behavior

KW - fashion merchandising

KW - fuzzy logic

KW - machine learning

UR - http://hdl.handle.net/1959.7/uws:56361

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PB - Association for Computing Machinery

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ER -

Implementing IoT-adaptive fuzzy neural network model enabling service for supporting fashion retail

Abstract

Conference

Keywords

UN SDGs

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