Mist and Edge Computing Cyber-Physical Human-Centered Systems for Industry 5.0: A Cost-Effective IoT Thermal Imaging Safety System

Abstract

While many companies worldwide are still striving to adjust to Industry 4.0 principles, the transition to Industry 5.0 is already underway. Under such a paradigm, Cyber-Physical Human-centered Systems (CPHSs) have emerged to leverage operator capabilities in order to meet the goals of complex manufacturing systems towards human-centricity, resilience and sustainability. This article first describes the essential concepts for the development of Industry 5.0 CPHSs and then analyzes the latest CPHSs, identifying their main design requirements and key implementation components. Moreover, the major challenges for the development of such CPHSs are outlined. Next, to illustrate the previously described concepts, a real-world Industry 5.0 CPHS is presented. Such a CPHS enables increased operator safety and operation tracking in manufacturing processes that rely on collaborative robots and heavy machinery. Specifically, the proposed use case consists of a workshop where a smarter use of resources is required, and human proximity detection determines when machinery should be working or not in order to avoid incidents or accidents involving such machinery. The proposed CPHS makes use of a hybrid edge computing architecture with smart mist computing nodes that processes thermal images and reacts to prevent industrial safety issues. The performed experiments show that, in the selected real-world scenario, the developed CPHS algorithms are able to detect human presence with low-power devices (with a Raspberry Pi 3B) in a fast and accurate way (in less than 10 ms with a 97.04% accuracy), thus being an effective solution (e.g., a good trade-off between cost, accuracy, resilience and computational efficiency) that can be integrated into many Industry 5.0 applications. Finally, this article provides specific guidelines that will help future developers and managers to overcome the challenges that will arise when deploying the next generation of CPHSs for smart and sustainable manufacturing.

Towards a Human-Centric Digital Twin for Human–Machine Collaboration: A Review on Enabling Technologies and Methods

“…Paula Fraga-Lamas et al [96] proposed a mist/edge computing cyber-physical humancentred system (CPHS) that uses low-cost hardware to detect human proximity to avoid risky situations in industrial scenarios. The proposed system was evaluated in a real-world scenario, where the maximum latency was reduced and low computational complexity was preserved.…”

Digital Twins in Software Engineering—A Systematic Literature Review and Vision

“…In these systems, embedded computers with sensors, actuators, controllers, and software in robots, humans, and network connectivity are combined to monitor and control physical processes, usually with real-time feedback loops of sensing, decision making, and evaluations of network compatibility, as commented by Dafflon et al [11]. Currently, the CPS designs are supported by many technological platforms such as the IoT, Fog, Edge Cloud, or 5G [12]. Furthermore, human-robot cooperation (HRC), for instance, studies the interactions between humans and robots in critical scenarios in a factory where humans and robots must work together, applying dynamic planning and safe routes for autonomous robots, as in the study by Maruyama et al [13].…”

A Bibliometric Analysis of Digital Twin in the Supply Chain

“…There were more than 70 research areas on digital twin in the supply chain. The top 10 research areas were engineering (1681), computer science (847), automation control systems (345), operations research/management science (265), materials science (249), telecommunications (198), chemistry (189), science technology other topics (159), physics (145), and energy fuels (109). Table 3 shows the top 20 research areas on digital twin in the supply chain.…”

“…Digital twin as an enabler in Industry 5.0 consists of seven elements, namely, technologies, humans, management, organizations, scopes, tasks, and modelling, while the types of digital twin in the supply chain involve product, process, organization, supply chain, and network-ofnetworks [158]. In using digital twin for Industry 5.0, the cyber-physical manufacturing system has now been shifted to cyber-physical human-centered systems for smart and sustainable manufacturing [159,160].…”