An auction based smart service robot implemented on a Fog Computing node

Maria B. Safianowska, Yi Chieh Peter Chang, Te Jen Wang, Chih Wei Huang, Ching-Yao Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Adopting AR/VR technology on smart retail services is gaining more momentum with the progress in indoor map scanning technology and the research on AI deep learning algorithms. In this paper we propose the use of a Fog computing node to generate an AR/VR view of the real store on a web page. The customers can then use the service robot to view the merchandise in the real store via the web and make purchases. Since the service robot is a precious resource on the AR/VR business model, we develop an auction method to optimize the customer satisfaction and the owner satisfaction in terms of customer waiting time and the average number of transactions that are assisted by the service robot respectively. We demonstrate that the auction method is a critical part in the AR/VR smart business services when the number of service robots is much less than the number of active customers from the web and that it performs better than the standard preemptive method.

Original languageEnglish
Title of host publication2017 IEEE Fog World Congress, FWC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781538636664
DOIs
StatePublished - 29 May 2018
Event2017 IEEE Fog World Congress, FWC 2017 - Santa Clara, United States
Duration: 30 Oct 20171 Nov 2017

Publication series

Name2017 IEEE Fog World Congress, FWC 2017

Conference

Conference2017 IEEE Fog World Congress, FWC 2017
CountryUnited States
CitySanta Clara
Period30/10/171/11/17

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