Industry 5.0 is projected to be an exemplary improvement in digital transformation allowing for mass customization and production efficiencies using emerging technologies such as universal machines, autonomous and self-driving robots, self-healing networks, cloud data analytics, etc., to supersede the limitations of Industry 4.0. To successfully pave the way for acceptance of these technologies, we must be bound and adhere to ethical and regulatory standards. Presently, with ethical standards still under development, and each region following a different set of standards and policies, the complexity of being compliant increases. Having vague and inconsistent ethical guidelines leaves potential gray areas leading to privacy, ethical, and data breaches that must be resolved. This paper examines the ethical dimensions and dilemmas associated with emerging technologies and provides potential methods to mitigate their legal/regulatory issues.

This paper presents a review of inspection-class Remotely Operated Vehicles (ROVs). The review divides the classification of inspection-class ROVs; categorising the vehicles in order of size and capability. A state of the art technology review is undertaken, discussing various common subsystems of the ROV. Standard and novel ROV shapes and designs are reviewed, with emphasis on buoyancy, frame materials and hydrodynamics. Several power considerations and designs are discussed, accounting for battery fed and mains fed systems. ROV telemetry is split into a discussion on the various transmission hardware systems and the communication protocols that are most widely used in industry and research today. A range of thruster technologies is then introduced with consideration taken of the various thruster architectures available. Finally, the navigation and positioning sensors employed for ROV navigation and control are reviewed. The author has also created a number of comparison tables throughout the review; tables include comparison of wired data transmission technology, comparison of common ROV communication protocols and comparisons of various inertial navigation systems. By the end of the review the reader will have clearer understanding on the fundamentals of inspection-class ROV technologies and can use this as an introduction to further paper investigation.

Industrial IoT (IIoT) is a novel concept of a fully connected, transparent, automated, and intelligent factory setup improving manufacturing processes and efficiency. To achieve this, existing hierarchical models must transition to a fully connected vertical model. Since IIoT is a novel approach, the environment is susceptible to cyber threat vectors, standardization, and interoperability issues, bridging the gaps at the IT/OT ICS (industrial control systems) level. IIoT M2M communication relies on new communication models (5G, TSN ethernet, self-driving networks, etc.) and technologies which require challenging approaches to achieve the desired levels of data security. Currently there are no methods to assess the vulnerabilities/risk impact which may be exploited by malicious actors through system gaps left due to improper implementation of security standards. The authors are currently working on an Industry 4.0 cybersecurity project and the insights provided in this paper are derived from the project. This research enables an understanding of converged/hybrid cybersecurity standards, reviews the best practices, and provides a roadmap for identifying, aligning, mapping, converging, and implementing the right cybersecurity standards and strategies for securing M2M communications in the IIoT.

The rapid growth of the Internet and communications has resulted in a huge increase in transmitted data. These data are coveted by attackers and they continuously create novel attacks to steal or corrupt these data. The growth of these attacks is an issue for the security of our systems and represents one of the biggest challenges for intrusion detection. An intrusion detection system (IDS) is a tool that helps to detect intrusions by inspecting the network traffic. Although many researchers have studied and created new IDS solutions, IDS still needs improving in order to have good detection accuracy while reducing false alarm rates. In addition, many IDS struggle to detect zero-day attacks. Recently, machine learning algorithms have become popular with researchers to detect network intrusion in an efficient manner and with high accuracy. This paper presents the concept of IDS and provides a taxonomy of machine learning methods. The main metrics used to assess an IDS are presented and a review of recent IDS using machine learning is provided where the strengths and weaknesses of each solution is outlined. Then, details of the different datasets used in the studies are provided and the accuracy of the results from the reviewed work is discussed. Finally, observations, research challenges and future trends are discussed.

5G networks will change several industries, including manufacturing. 5G has the potential to become the future communication platform of choice for many industries and in particular the manufacturing sector, driving the future of Industry 4.0 and smart manufacturing. The vision of a “factory of the future” is now tangible for many industry sectors. The ability to cope with increased bandwidth, latency requirements, big-data generated from more connected equipment and the data processing required on the factory floor is a massive challenge for industry. This paper discusses how 5G can impact a manufacturing environment, the standards and technical requirements needed to meet the demands of utilizing 5G, and the security issues that need to be addressed if planning a 5G deployment.

In the past 10 years, wireless sensor networks have grown from a theoretical concept to a burgeoning modern technology. In this paper, we present a comparative review of several wireless sensor network motes. We analyze these WSN devices under a number of different parameters and criteria, including processing ability, expected lifetime and measurement capabilities. We compare and contrast the selected WSN motes under these different headings, highlighting the individual mote's performance under each category.