Exhibition venues are the prerequisites and physical carriers in terms of infrastructure and technologies in MICE industry. As public places with high density of visitors flow, there always lurk such risks as traffic congestion in popular booths and crowd gathering in entrances and exits. The services for accurate positioning and navigation guidance are gradually in demand for exhibition venues. This paper firstly analyses the core technological bases of customer intelligent guidance APP, namely, face recognition, crowd density detection, as well as indoor positioning and navigation. Then, technical structures are dealt with, which include overall architecture and databases of visitors, exhibitors, organizers and electronic maps. 7 first-level modules are hence designed. The venue map is displayed on the website port. The system backstage is built on Spring Boot, and the local data are saved in the form of map with the implementation of Serializable. This App is thereby programmed with algorithms and tested with great results.

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Design of Customer Intelligent Guidance APP in Exhibition Venues

  • Xiao Liu,
  • Chen Wan’er Zhang,
  • Huiru Wang,
  • Xia Wang,
  • Xiaohua Yang

摘要

Exhibition venues are the prerequisites and physical carriers in terms of infrastructure and technologies in MICE industry. As public places with high density of visitors flow, there always lurk such risks as traffic congestion in popular booths and crowd gathering in entrances and exits. The services for accurate positioning and navigation guidance are gradually in demand for exhibition venues. This paper firstly analyses the core technological bases of customer intelligent guidance APP, namely, face recognition, crowd density detection, as well as indoor positioning and navigation. Then, technical structures are dealt with, which include overall architecture and databases of visitors, exhibitors, organizers and electronic maps. 7 first-level modules are hence designed. The venue map is displayed on the website port. The system backstage is built on Spring Boot, and the local data are saved in the form of map with the implementation of Serializable. This App is thereby programmed with algorithms and tested with great results.