Collision Avoidance on Unmanned Aerial Vehicles Using Neural Network Pipelines and Flow Clustering Techniques

Unmanned Autonomous Vehicles (UAV), while not a recent invention, have recently acquired a prominent position in many industries, and they are increasingly used not only by avid customers, but also in high-demand technical use-cases, and will have a significant societal effect in the coming years. However, the use of UAVs is fraught with significant safety threats, such as collisions with dynamic obstacles (other UAVs, birds, or randomly thrown objects). This research focuses on a safety problem that is often overlooked due to a lack of technology and solutions to address it: collisions with non-stationary objects. A novel approach is described that employs deep learning techniques to solve the computationally intensive problem of real-time collision avoidance with dynamic objects using off-the-shelf commercial vision sensors. The suggested approach’s viability was corroborated by multiple experiments, firstly in simulation, and afterward in a concrete real-world case, that consists of dodging a thrown ball. A novel video dataset was created and made available for this purpose, and transfer learning was also tested, with positive results.

Tactile Internet and the Remote Surgeon

The delivery of healthcare in remote rural areas is a global phenomenon. Using digital governance, a discretized cluster of node relaying time-sensitive, and reliable data, life-critical health services can be ensured. Here tactile internet-based internet of things (IoT) and its variant internet of medical things (IoMT), as well as tactile internet, is introduced. Its relationship with 5G is explored. A model for e-health implementation using unmanned autonomous vehicles (UAVs) in the backhaul is presented. The link is analyzed over fiber optics, satellite, and 5G network in terms of latency and reliability: the crucial metrics for robotic surgery. It is also shown that 5G implemented in Italy, Zimbabwe, and Cooks Island have supported mobile hospitals in rural regions. Hence, induction of 5G networks is a feasible approach. Finally, a critical review of expected future technologies including telematics is presented. Hence, tactile internet-based robotic surgery can reduce the digital divide.

Investigating the Impact of Energy Source Level on the Self-Guided Vehicle System Performances, in the Industry 4.0 Context

Automated industrial vehicles are taking an imposing place by transforming the industrial operations, and contributing to an efficient in-house transportation of goods. They are expected to bring a variety of benefits towards the Industry 4.0 transition. However, Self-Guided Vehicles (SGVs) are battery-powered, unmanned autonomous vehicles. While the operating durability depends on self-path design, planning energy-efficient paths become crucial. Thus, this paper has no concrete contribution but highlights the lack of energy consideration of SGV-system design in literature by presenting a review of energy-constrained global path planning. Then, an experimental investigation explores the long-term effect of battery level on navigation performance of a single vehicle. This experiment was conducted for several hours, a deviation between the global trajectory and the ground-true path executed by the SGV was observed as the battery depleted. The results show that the mean square error (MSE) increases significantly as the battery’s state-of-charge decreases below a certain value.

Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques

In this article, we propose a new mobility model, called Attractor Based Inter-Swarm collaborationS (ABISS), for improving the surveillance of restricted areas performed by unmanned autonomous vehicles. This approach uses different types of vehicles which explore an area of interest following unpredictable trajectories based on chaotic solutions of dynamic systems. Collaborations between vehicles are meant to cover some regions of the area which are unreachable by members of one swarm, e.g., unmanned ground vehicles on water surface, by using members of another swarm, e.g., unmanned aerial vehicles. Experimental results demonstrate that collaboration is not only possible but also emerges as part of the configurations calculated by a specially designed and parameterised evolutionary algorithm. Experiments were conducted on 12 different case studies including 30 scenarios each, observing an improvement in the total covered area up to 11%, when comparing ABISS with a non-collaborative approach.

Tactile Internet and the Remote Surgeon

The delivery of healthcare in remote rural areas is a global phenomenon. Using digital governance, a discretized cluster of node relaying time-sensitive, and reliable data, life-critical health services can be ensured. Here tactile internet-based internet of things (IoT) and its variant internet of medical things (IoMT), as well as tactile internet, is introduced. Its relationship with 5G is explored. A model for e-health implementation using unmanned autonomous vehicles (UAVs) in the backhaul is presented. The link is analyzed over fiber optics, satellite, and 5G network in terms of latency and reliability: the crucial metrics for robotic surgery. It is also shown that 5G implemented in Italy, Zimbabwe, and Cooks Island have supported mobile hospitals in rural regions. Hence, induction of 5G networks is a feasible approach. Finally, a critical review of expected future technologies including telematics is presented. Hence, tactile internet-based robotic surgery can reduce the digital divide.

Voice Controlled Wiper for Smart Helmets

Intelligent transportation system is one of the major focus in today’s era. Several sensor integrated devices and unmanned autonomous vehicles, not only enhance the comfort of drivers but also help in safe driving. Specifically, for motorcyclists, helmets embedded with sensors are lifesaving gadgets. Researchers have focused on developing low power low cost smart helmets to prevent road accidents. However, the existing smart helmets are not season friendly. This paper proposes an extension for smart helmets that can assist riders to ride the motorcycle with great ease during heavy rains. The hardware unit consists of wiper integrated to helmet which turns ON and OFF based on the voice commands issued by the motorcyclists.

Recent advances in remote sensing technologies for hydrocarbon exploration and environmental evaluation

Remote sensing detects and monitors the physical and spatial characteristics of the earth's oceans, surface, and atmosphere by measuring the reflected or scattered downwelling or emitted upwelling electromagnetic radiation or acoustic signal using passive or active sensors at a distance. It plays an important role in today's energy and environmental sustainability efforts. Remote sensing from spaceborne, airborne, terrestrial, and marine platforms has long been used in hydrocarbon exploration to map surface geology, topography, and hydrocarbon seepages, as well as to evaluate environments that relate to petroleum industry activities. Since the mid-2000s, remote sensing technologies have undergone substantial advances in data acquisition, processing, and interpretation. In the last decade, rapid advances in satellite systems, unmanned autonomous vehicles (UAVs), sensors, and scale of surveys have further expanded applications.