• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 춘계학술대회
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• pp.390-392
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• 2018

우리는 가끔 물건을 보관한 위치를 잊고 나서 찾는데 많은 시간을 보내는 경우가 발생한다. 본 논문에서는 물건을 보관하고 위치를 알려주며 쉽게 찾을 수 있게 하는 물건관리 시스템을 설계하고 개발한다. 물건을 정리하는 방식은 사람이 로봇 위에 물건을 올려놓고 스마트폰에 설치된 로봇제어 애플리케이션을 통해 물건의 이름을 선택하면 비어있는 보관 장소를 확인한 후 이동하여 보관한 뒤 보관 위치를 스마트폰으로 위치정보 데이터를 전송하는 방식이다. 본 논문을 통하여 우리가 집에서 관리하는 물건을 잊지 않고 쉽게 찾을 수 있는 가능성을 확인하였으며 무인 창고관리 기술의 발전에 기여할 것으로 기대된다.

• International Journal of Advanced Culture Technology
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• 제9권2호
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• pp.100-105
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• 2021

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.