The industrial applications in the cloud do not meet the requirements of low latency and reliability since variables must be continuously monitored. For this reason, industrial internet of things (IIoT) is a challenge for the current infrastructure because it generates a large amount of data making cloud computing reach the edge and become fog computing (FC). FC can be considered as a new component of Industry 4.0, which aims to solve the problem of big data, reduce energy consumption in industrial sensor networks, improve the security, processing and storage real-time data. It is a promising growing paradigm that offers new opportunities and challenges, beside the ones inherited from cloud computing, which requires a new heterogeneous architecture to improve the network capacity for delivering edge services, that is, providing computing resources closer to the end user. The purpose of this research is to show a systematic review of the most recent studies about the architecture, security, latency, and energy consumption that FC presents at industrial level and thus provide an overview of the current characteristics and challenges of this new technology.

The fourth industrial revolution has forced most companies to technologically evolve, applying new digital tools, so that their workers can have the necessary skills to face changing work environments. This article presents a scoping review of the literature on virtual reality-based training systems. The methodology consisted of four steps, which pose research questions, document search, paper selection, and data extraction. From a total of 350 peer-reviewed database articles, such as SpringerLink, IEEEXplore, MDPI, Scopus, and ACM, 44 were eventually chosen, mostly using the virtual reality haptic glasses and controls from Oculus Rift and HTC VIVE. It was concluded that, among the advantages of using this digital tool in the industry, is the commitment, speed, measurability, preservation of the integrity of the workers, customization, and cost reduction. Even though several research gaps were found, virtual reality is presented as a present and future alternative for the efficient training of human resources in the industrial field.

Teleoperation virtual platforms allow people to send their skills and capacities into machines located in either relative close (few meters away) or far (different continents) locations. With the use of lightweight protocols, people can remotely control the actions and movements of robots so they can avoid physical interaction with dangerous or risky places. Oil and gas well-pads stations are working zones considered hazardous due to the various chemical substances used in their daily processes. This characteristic makes these places the perfect candidates for the implementation of teleoperation solutions in order to reduce the direct interaction of humans with different chemicals and risky situations. The following investigation focuses on the development of a base teleoperation scheme to perform inspection and maintenance tasks in the inside one of these hydrocarbon facilities. The proposed system aims to generate an easily scalable teleoperation solution using distributed control schemes and a lightweight communication protocol to remotely manipulate a KUKA mobile manipulator. As the first stage of this investigation, the main result focuses on the development of the generic control and communication functions that allow the physical testing of the system using a KUKA YouBOT mobile manipulator and the help of a qualified operator of the station.