Industrial Humanless Monitoring System over 5G Networks in the Shipyard Environment

As the development of hardware technology and the application of AI technology become popular, efforts to apply image-based services to real industrial sites are increasing. In particular, the development of image-based worker recognition technology is a field in which various studies are being conducted as a base technology that can be widely used in many industrial fields, such as industrial health, safety monitoring, work process management, and collaboration between humans and robots. However, opposition from labor unions due to workers' privacy protection issues and outdated on-site network facilities are acting as obstacles to the application of video-based application services in actual industrial sites. To solve this privacy problem, we introduced a technology that recognizes a worker at the end device where an image sensor is installed and replaces the recognized worker with an existing background image. In this paper, we introduce the previously proposed worker deletion technology [1] and analyze the problems that occurred in field experiments. In addition, the structure linked with the 5G network is additionally presented, and advanced performance improvement techniques are presented. The performance of the implemented algorithm is applied to various hardware platforms to find out its performance and applicability.