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Optimization RFID-enabled Retail Store Management with Complex Event Processing

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Abstract

Radio frequency identification (RFID) enabled retail store management needs workflow optimization to facilitate real-time decision making. In this paper, complex event processing (CEP) based RFID-enabled retail store management is studied, particularly focusing on automated shelf replenishment decisions. We define different types of event queries to describe retailer store workflow action over the RFID data streams on multiple tagging levels (e.g., item level and container level). Non-deterministic finite automata (NFA) based evaluation models are used to detect event patterns. To manage pattern match results in the process of event detection, optimization algorithm is applied in the event model to share event detection results. A simulated RFID-enabled retail store is used to verify the effectiveness of the method, experiment results show that the algorithm is effective and could optimize retail store management workflow.

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Acknowledgements

This work was supported by National Social Science Fund (No. 16CTQ013), the Application Fundamental Research Foundation of Sichuan Province, China (No. 2017JY0011), and the Key Project of Sichuan Provincial Department of Education, China (No. 2017GZ0333).

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Authors and Affiliations

  1. College of Computer Science and Technology, Chengdu University of Information Technology, Chengdu, 610225, China

    Shang-Lian Peng, Jia He & Fan Li

  2. The Southwest Jiaotong University (SWJTU)-Leeds Joint School, Southwest Jiaotong University, Chengdu, 610041, China

    Ci-Jian Liu

  3. School of Computer Science and Network Security, Dongguan University of Technology, Dongguan, 523808, China

    Hong-Nian Yu

  4. Faculty of Science and Technology, Bournemouth University, Poole, BH125BB, UK

    Hong-Nian Yu

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  1. Shang-Lian Peng
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  5. Fan Li
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Correspondence to Shang-Lian Peng.

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Recommended by Associate Editor Jie Zhang

Shang-Lian Peng received the B. Sc. degree in information and computing science from China West Normal University, Chine in 2004, the M. Sc. degrees in computer science from Wuyi University, China in 2007, and the Ph. D. degree in computer science from Northwestern Polytechnic University, China in 2012. Since 2012, he is a faculty member at Chengdu University of Information Technology, China. He has published about 15 refereed journal and conference papers. He is a member of China Computer Federation (CCF), Association for Computing Machinery (ACM) and IEEE.

His research interests include data management, database, RFID, internet of things, and cloud computing.

Ci-Jian Liu is a undergraduate in computer science at the SWJTU-Leeds Joint School, Southwest Jiaotong University, China. He has contributed in the design and implementation of the event processing system.

His research interests including clouding computing and event detection.

Jia He received the B. Sc. degree in computer science from Southwest University, China in 1989, and the Ph. D. degree in computer science from University of Electronic Science and Technology of China, China in 2012. She is a professor in Chengdu University of Information Technology, China. She is a member of CCF, ACM and IEEE.

Her research interests include cloud computing, intelligent computing and artificial intelligence.

Hong-Nian Yu received the B. Eng. degree in electrical and electronic engineering from Harbin Institute of Technology, China in 1982, the the M. Sc. degree in control engineering from Northeast Heavy Machinery Institute, China in 1984, and the Ph. D. degree in robotics in King′s College London, UK in 1994. He is a professor in Bournemouth University, UK. He has held academic positions at the Universities of Sussex, Liverpool John Moor, Exeter, Bradford, Staffordshire and Bournemouth in UK. He is currently a professor in computing at Bournemouth University, UK. He has extensive research experience in mobile computing, modelling, scheduling, planning, and simulations of large discrete event dynamic systems with applications to manufacturing systems, supply chains, transportation networks, computer networks and RFID applications, modelling and control of robots and mechatronics, and neural networks. He has published over 200 journal and conference research papers. He is a member of the Engineering and Physical Sciences Research Council (EPSRC) Peer Review College. He is senior member of IEEE.

His research interests include mobile computing, modelling, scheduling, planning and simulations of large discrete event dynamic systems.

Fan Li received the B. Sc. and M. Sc. degrees in computer science from University of Electronic Science and Technology of China (UESTC), China in 2003 and 2006, respectively. He is a lecturer in Chengdu University of Information Technology, China. He is a member of CCF. He has extensive research experience in cloud computing, virtualization, modelling.

His research interests include cloud computing and distributed computing.

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Peng, SL., Liu, CJ., He, J. et al. Optimization RFID-enabled Retail Store Management with Complex Event Processing. Int. J. Autom. Comput. 16, 52–64 (2019). https://doi.org/10.1007/s11633-018-1164-5

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