CrowdIM: Crowd-Inspired Intelligent Manufacturing Space Design

Bin Guo, Jiaqi Liu, Sicong Liu, Jiayao Wang, Mengyuan Li, Chen Wang, Zhiwen Yu

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Crowd-inspired intelligent manufacturing space (CrowdIM) aims to leverage the aggregated power of heterogeneous human-machine-things (HMT) agents for improving the efficiency of intelligent manufacturing. A significant scientific problem in CrowdIM is how to improve individual skills and crowd intelligence through cooperation, complementation, competition, and confrontation among HMT agents. The emergence mechanism of biological crowd intelligence provides an inspiration to address this challenge. This article explores the mapping mechanisms between natural crowd intelligence and CrowdIM, from the aspects, such as collective dynamics, self-adaptive mechanism, crowd intelligence optimization, graph structure mapping model, evolutionary game dynamics, multiagent learning, and so on. We further propose a general model of CrowdIM and expound it through a typical case study.

Original languageEnglish
Pages (from-to)19387-19397
Number of pages11
JournalIEEE Internet of Things Journal
Volume9
Issue number19
DOIs
StatePublished - 1 Oct 2022

Keywords

  • Crowd intelligence
  • human-machine-things (HMT)
  • intelligent manufacturing (IM)
  • multiagent learning
  • self-adaption

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