大型商场智慧购物系统研究

doi:10.16182/j.issn1004731x.joss.201612013

系统仿真学报 ›› 2016, Vol. 28 ›› Issue (12): 2966-2972.doi: 10.16182/j.issn1004731x.joss.201612013

大型商场智慧购物系统研究

陈立龙¹, 宋建文², 周伟², 张立国², 潘志庚³

1.三明学院海峡动漫学院,福建三明 365004;
2.中国美术学院互动艺术与技术研究所,浙江杭州 310024;
3.杭州师范大学DMI中心,浙江杭州 311121

收稿日期:2014-08-30 修回日期:2015-03-02 出版日期:2016-12-08 发布日期:2020-08-13
第一作者简介:陈立龙(1987-),男,福建尤溪,硕士,助教,研究方向为网络技术与应用;宋建文(1959-),福建福州,学士,副教授,研究方向为虚拟现实、色彩数字化及其应用。

Research of Smart Shopping System

Chen Lilong¹, Song Jianwen², Zhou Wei², Zhang Liguo², Pan Zhigeng³

1. Strait Animation Institute of Sanming University, Sanming 365004 China;
2. Institute of Interactive Art and Technology, China Academy of Art, Hangzhou 310024, China;
3. DMI Center, Hangzhou Normal University, Hangzhou 311121, China

Received:2014-08-30 Revised:2015-03-02 Online:2016-12-08 Published:2020-08-13

摘要/Abstract

摘要： 大型商场面积大、商品种类繁多,顾客需要花大量时间在寻找商品和排队结账上;而商店在商品的导购和收银等环节中需要投入大量的人力和财力,且效率不高,同时也缺少对每位顾客的消费习惯进行统计的手段。通过将信息化移动技术、自动识别技术(射频识别技术)以及网络、数据库等技术的结合,为商场构建一个以“智能购物车”为核心技术的智能购物系统,使顾客快速付账无需等待,提高商场效率和服务质量,对大型超市具有较强的实用价值。

关键词: 射频识别技术, 智能购物, 室内导航, 快捷支付, 购买习惯

Abstract: Hypermarket is quite large in area, and rich in many different kinds of goods, the customer needs to spend a lot of time looking for the products and waiting in check-out queues; And hypermarket not only needs to invest a lot of manpower and financial resources in links such as shopping guide and check-out, and the efficiency is not high, but also lack of statistical means in spending habits of each customer. It has an important significance in the hypermarket to create a smart shopping system by putting mobile information technology, automatic identification technology (RFID technology, for example), the network and database technology together, smart cart was the core element of the system, the system could save customers time, improve the efficiency of the market activities of each link and the quality of services to improve the user experience at the same time, the shop also could earn more profits.

Key words: RFID, smart shopping, indoor navigation, quick payment, buying habit

中图分类号:

TP391.9

陈立龙,宋建文,周伟等 . 大型商场智慧购物系统研究[J]. 系统仿真学报, 2016, 28(12): 2966-2972.

Chen Lilong,Song Jianwen,Zhou Wei,et al . Research of Smart Shopping System[J]. Journal of System Simulation, 2016, 28(12): 2966-2972.

参考文献

[1] Lionel M Ni, Yunhao Liu, Yiu Cho Lau, et al.LANDMARC: Indoor Location Sensing Using Active RFID[J]. Wireless Networks-WINET (S1022-0038), 2004, 10(6): 701-710.
[2] Wei Song, Mengli Li.Localization in Supermarket Based on RFID Technology[J]. Procedia Engineering (S1877-7058), 2012, 29: 3779-3782.
[3] Jing Chen, Gengmin Li, Xuejun Zhang, et al.An efficient algorithm for indoor location based on RFID[C]// Wireless Communications and Signal Processing (WCSP), 2011 International Conference on. New York, USA: IEEE, 2011: 1-4.
[4] M Mathankumar, T Kavitha.Design and Implementation of Smart Supermarket[J]. International Journal of Engineering and Technology (IJET)(S0975-4024), 2013, 5(1): 215-219.
[5] H Fernandesa, Vitor Filipea, Paulo Costac, et al. Location based Services for the Blind Supported by RFID Technology[J]. Procedia Computer Science (S1877-0509), 2014, 27: 78-80.
[6] Wei Dai, Shuo Zhou, Guangjun Luo, et al.Analyze on Mobile Payment Based on RFID[J]. Procedia Environmental Sciences (S1878-0296), 2011, 10(Part B): 950-955.
[7] Erik-Oliver Blass, Anil Kurmus, Refik Molva, et al.PSP: Private and secure payment with RFID[J]. Computer Communications (S0140-3664), 2013, 36(4): 468-480.
[8] Dong Yang, Qingxian Wang.The study on the application of RFID based mobile payment to the Internet of Things[C]// IEEE. International Conference on Multimedia Technology-ICMT. New York, USA: IEEE, 2011: 908-911.
[9] Takai Keiji, Yada Katsutoshi.Relation between stay-time and purchase probability based on RFID data in a Japanese supermarket[C]//Springer-Verlag. Proceedings of the 14th International Conference on Knowledge- based and Intelligent Information and Engineering Systems: Part III. Berlin, Heidelberg, Germany: Springer-Verlag, 2010: 254-263.
[10] 李雪, 陆百川, 李政. RFID系统多阅读器防碰撞问题研究[J]. 重庆交通大学学报(自然科学版), 2012, 31(3): 437-438, 442.(Li Xu, Lu Baichuan, Li Zheng. Study on Reader Anti-Collision Algorithm in RFID System [J]. Journal of Chongqing Jiaotong University (Natural Sciences), 2012, 31(3): 437-438, 442. DOI:10.3969/j.issn.1674-0696.2012.03.19.)

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大型商场智慧购物系统研究

Research of Smart Shopping System

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