This work presents a detailed study, characterization, and measurement of video latency in a real‐time video streaming application. The target application consists of an automatic control system in the form of a control station and the mini Remotely Operated Vehicle (ROV) equipped with a camera, which is controllable over local area network (LAN) and the Internet. Control signal transmission and feedback measurements to the operator usually impose real‐time constraints on the network channel. Similarly, the video stream, which is required for the normal system control and maneuvering, imposes further strict requirements on the network in terms of bandwidth and latency. Based on these requirements, controlling the system in real time through a standard Internet connection is a challenging task. The measurement of important network parameters like availability, bandwidth, and latency has become mandatory for remotely controlling the system in real time. It is necessary to establish a methodology for the measurement of video and network latency to improve the real‐time controllability and safety of the system as such measurement is not possible using existing solutions due to the following reasons: insufficient accuracy, relying on the Internet resources such as generic Network Time Protocol (NTP) servers, inability to obtain one‐way delay measurement, and many solutions only having support for web cameras. Here, an efficient, reliable, and cost‐effective methodology for the measurement of latency of a video stream over a LAN and the Internet is proposed. A dedicated stratum‐1 NTP server is used and the necessary software needed for acquiring and measuring the latency of a video stream from a generic IP camera as well as integration into the existing ROV control software was developed. Here, by using the software and dedicated clock synchronization equipment (NTP server), it was found that normal video latencies in a LAN were in the range of 488ms – 850ms, while latencies over the Internet were measured to be in the range of 558ms – 1211ms. It is important to note that the values were obtained by using a generic (off‐the‐shelf) IP camera and they represent the actual latencies which might be experienced during control over long range and across international territory borders.

With the growth of the internet of things (IoT), many challenges like information security and privacy, interoperability/standard, and regulatory and legal issues are arising. This work focused on the information security issue, which is one of the primary challenges faced by connected systems that needs to be resolved without impairing system behaviour. Information, which is made available on the Internet by the things, varies from insensitive information (e.g., readings from outdoor temperature sensors) to extremely sensitive information (e.g., video stream from a camera) and needs to be secured over the Internet. Things which utilise cameras as a source of information pertain to a subclass of the IoT called IoVT (internet of video things). This paper presents secured and unsecured video latency measurement results over the Internet for a marine ROV (remotely operated vehicle). A LabVIEW field programmable gate arrays (FPGAs)-based bump-in-the-wire (BITW) secure core is used to provide an AES (advanced encryption standard)-enabled security feature on the video stream of an IoVT node (ROV equipped with a live-feed camera). The designed LabVIEW-based software architecture provides an option to enable/disable the AES encryption for the video transmission. The latency effects of embedding encryption on the stream with real-time constraints are measured and presented. It is found that the encryption mechanism used does not greatly influence the video feedback performance of the observed IoVT node, which is critical for real-time secure video communication for ROV remote control and piloting. The video latency measurement results are taken using 128, 256 and 512 bytes block lengths of AES for both H.264 and MJPEG encoding schemes transmitted over both TCP and UDP transmission protocols. The latency measurement is performed in two scenarios (i.e., with matching equipment and different equipment on either end of the transmission).

The overall control system for an open-frame Remotely Operated Vehicle (ROV) is typically built from three subsystems: guidance, navigation and control (GNC). The control allocation plays a vital role in the control subsystem. Typically, open-frame underwater vehicles have p actuators (thrusters) for the motion in the horizontal plane, and the control allocation problem, in this case, is very complex and hard to visualise, because the normalised constrained control subset is a p-dimensional unit cube. The aim of this paper is to give a clear picture and a geometric interpretation of the problem and to introduce a hybrid method, based on the integration of a weighted pseudoinverse and the fixed-point method. The main idea of the hybrid method is visualised, and the deep geometric insight is provided using a “virtual” ROV in low-dimensional control spaces, including visualisation of the attainable command set, solution lines, control energy spheres and the role of pseudoinverse and fixed-point iterations. The same concepts are then extended to higher-dimensional cases, for open-frame ROV with four X-shaped (vectored) horizontal thrusters, which is one of the most common thruster configurations for commercial ROVs. The proposed hybrid method has been developed, integrated into a generic fault-tolerant ROV control system and evaluated in virtual and real-world environments off the west coast of Ireland using observation-class ROV Latis and work-class ROV Étaín.