Industrial safety inspections, particularly in the mining sector and the industrial Internet of Things (IoT), increasingly rely on multi-robot systems to perform safety inspections and mapping in remote, confined, and hazardous areas inaccessible to humans. However, conventional multi-robot systems often depend on a central robot for data management, leading to vulnerabilities in fault tolerance and data replication during inspections. This centralized approach to inspection data management can result in single points of failure and potential trust disputes among stakeholders, including government agencies, industry representatives, and local communities. To address these challenges, this work proposes a system that combines blockchain technology with a Proof-of-Authority (PoA) consensus mechanism to improve the reliability and performance of multi-robot inspections. By leveraging blockchain’s inherent properties of fault tolerance, data replication, transparency, and immutability, our system mitigates the risks associated with centralized control in multi-robot operations in all safety inspection pipelines. We implemented and evaluated our proposed system using CoppeliaSIM, a widely used robot simulator, to validate its feasibility. The evaluation included multiple scenarios: normal operation, node failure, network latency simulations, and a comparison with a centralized system. The results show that our solution enhances fault tolerance and ensures data integrity in multi-robot systems. While the decentralized system has a higher average transaction latency (approximately 1.9 seconds) compared to the centralized system (1.42 milliseconds), it avoids the vulnerabilities linked to single points of failure. This approach not only enhances the reliability of industrial safety inspections but also provides secure data sharing among diverse stakeholders in the industrial safety ecosystem.
Garcia et al. (Mon,) studied this question.