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A Study on the Automated Payment System for Artificial Intelligence-Based Product Recognition in the Age of Contactless Services

  • Kim, Heeyoung (Department of Immersive Content Convergence, General graduate school, Kwangwoon University) ;
  • Hong, Hotak (AI R&D Center, JLK, Inc.) ;
  • Ryu, Gihwan (Department of Tourism Industry, Graduate school of smart convergence, Kwangwoon University) ;
  • Kim, Dongmin (JLK, Inc.)
  • Received : 2021.04.27
  • Accepted : 2021.05.30
  • Published : 2021.06.30

Abstract

Contactless service is rapidly emerging as a new growth strategy due to consumers who are reluctant to the face-to-face situation in the global pandemic of coronavirus disease 2019 (COVID-19), and various technologies are being developed to support the fast-growing contactless service market. In particular, the restaurant industry is one of the most desperate industrial fields requiring technologies for contactless service, and the representative technical case should be a kiosk, which has the advantage of reducing labor costs for the restaurant owners and provides psychological relaxation and satisfaction to the customer. In this paper, we propose a solution to the restaurant's store operation through the unmanned kiosk using a state-of-the-art artificial intelligence (AI) technology of image recognition. Especially, for the products that do not have barcodes in bakeries, fresh foods (fruits, vegetables, etc.), and autonomous restaurants on highways, which cause increased labor costs and many hassles, our proposed system should be very useful. The proposed system recognizes products without barcodes on the ground of image-based AI algorithm technology and makes automatic payments. To test the proposed system feasibility, we established an AI vision system using a commercial camera and conducted an image recognition test by training object detection AI models using donut images. The proposed system has a self-learning system with mismatched information in operation. The self-learning AI technology allows us to upgrade the recognition performance continuously. We proposed a fully automated payment system with AI vision technology and showed system feasibility by the performance test. The system realizes contactless service for self-checkout in the restaurant business area and improves the cost-saving in managing human resources.

Keywords

References

  1. S.H. June, J.H. Kim, "Theoretical Background and Prospects for the Untact Industry", Journal of New Industry and Business (emr), Vol.38. Vol. 1, pp. 96-116, June 2020. DOI:10/30753/emr.2020.38.1.005 https://doi.org/10.30753/EMR.2020.38.1.005
  2. S.J. Jun, H.I. Kim, "The effect of untact service experience value on customer satisfaction and reuse intention as the development of food tech", Journal of Hospitality & Tourism Studies, Vol. 22, No. 4, pp. 141-155, December 2020. DOI:10.31667/jhts.2020.12.85.141
  3. M.L. Meuter, A. L. Ostrom, R.I. Roundtree and M.J. Bitner, "Self- service technologies: understanding customer satisfaction with technology-based service encounters", Journal of Marketing, Vol. 64 No. 3, pp. 50-64, July 2000. DOI: 10.1509/jmkg.64.3.50.18024
  4. H.C. Song, "New Normal Age, Untact Solutions and the Need for BCP", The Magazine of the IEEE, Vol. 47, No. 6, pp. 37-41, June 2020.
  5. S.S. Cha, S.Y. Park, "The Influence of Perceived Service Quality on Satisfaction and Revisit Intention in Restaurant Using Kiosk", Journal of Foodservice Management Society of Korea, Vol. 22, No. 4, pp. 27-50, August 2019.
  6. J.Y. An, C.C. Lee, D.E. Bae, and S.H. Lee, "A Study on Use of Untact Service: Based on Kiosk Case", The Journal of Internet Electronic Commerce Resarch, Vol. 20, No. 4, pp. 49-73, August 2020. DOI:10.37272/JIECR.2020.08.20.4.49
  7. S.M. Lee, D.H. Lee, "Untact": a new customer service strategy in the digital age, Service Business, Vol. 14, pp. 1-22, March 2020. DOI: 10.1007/s11628-019-00408-2
  8. J.W. Park, H.R. Lee, "The Effect of Fast Food Restaurant Customers' Kiosk Use on Acceptance Intention and Continuous Use Intention: Applying UTAUT2 Model and Moderating Effect of Familiarity", International Journal of Tourism Sciences, Vol. 44, No. 2, pp. 207-228, March 2020. DOI:10.17086/JTS.2020.44.2.207.228
  9. H.S. IM, D.J. Ryu, and D.H. Park, "Economic Analysis of the Kiosk Industry", Korea Business Review, Vol. 24, No. 1, pp. 21-48, February 2020. DOI: 10.17287/kbr.2020.24.1.21
  10. R. Katarzyna, M. Pawel, "A Vision-Based Method Utilizing Deep Convolutional Neural Networks for Fruit Variety Classification in Uncertainty Conditions of Retail Sales", Applied Sciences, Vol. 9, No. 19, pp. 2076-3417, September 2019. DOI: 10.3390/app9193971
  11. M. Chen, Y. Hao, K. Lin, Z. Yuan, and L. Hu, "Label-less learning for traffic control in an edge network", IEEE Network, Vol. 32, No. 6, pp. 8-14, November 2018. DOI: 10.1109/MNET.2018.1800110