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The idea of remote controlling ships for operational and commercial uses has developed beyond concepts. Controlling and monitoring vessels from a distant location requires updating the concept and requirements of shore control centers (SCCs), where human operators control the fleet via cameras, GPS, and many other types of sensors. While remote ship operation promises to reduce operational and maintenance costs, while increasing loading capacity and safety, it also brings significant uncertainty related to both the human-machine and human-human interactions which will affect operations. Achieving safe, reliable, and efficient remote ship operations requires consideration of both technological, cultural, social and human factor aspects of the system. Indeed, operators will act as captain and crew remotely, from the SCC, introducing new types of hardware and software interactions. This paper provides an overview of human factor issues that may affect human-machine and human-human interactions in the course of remote ship operations. In doing so, the literature related to remote operations in the domains of shipping, aerial vehicles, cranes, train transportation, automobiles, and mining is reviewed. Findings revealed that human factor issues are likely to fall into 13 distinct groups based on the type of human interactions that take place in SCCs.

Internet of Things (IoT) is an emerging technology that expands wireless and mobile networks into heterogeneous network of connected devices. Trustable remote monitoring and management systems are required to establish a controlled environment for new services and devices in order to (i) improve the quality of existing services and (ii) enable novel services. However, monitoring and remote management can cause security and privacy concerns and thus affect the trust formation between customer and service provider. This paper introduces a trust model considering institutions as mediators to assess trustability of remote monitoring and management systems. The proposed model considers governance as an approach to audit remote monitoring and management systems and accordingly provides institutional assurance in form of certificate or labels in order to facilitate trust decision making and motivate trustworthy behaviors. The proposed model utilized the multi-metric method to measure governance criteria objectively and represent level of trustworthiness with A-F labels. Representing governance criteria with labels accompanied by color coding facilitates trust decision making based on application context or requirements for everyone regardless of level of expertise. Meanwhile, issuing trustworthiness certificate or A-F labels will encourage service providers to improve trustability of their remote monitoring and management approaches, which improve acceptability and efficiency of managed services.

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