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Unmanned aerial vehicles (UAV), colloquially called drones, are widely applied in many sectors of the economy, including the construction industry. They are used for building inspections, damage assessment, land measurements, safety inspections, monitoring the progress of works, and others.

The study notes that UAV pose new, and not yet present, risks in the construction industry. New threats arise, among others, from the development of new technologies, as well as from the continuous automation and robotization of the construction industry. Education regarding the safe use of UAV and the proper use of drones has a chance to improve the safety of work when using these devices.

The procedure (protocol) was developed for the correct and safe preparation and planning of an unmanned aerial vehicle flight during construction operations.

Based on the analysis of available sources, no such complete procedure has yet been developed for the correct, i.e. compliant with applicable legal regulations and occupational health and safety issues, preparation for flying UAV. The verification and validation of the developed flight protocol was performed on a sample of over 100 different flight operations.

To avoid this situation, the authors proposed an optimal artificial bee colony algorithm-based Unmanned Aerial Vehicle (UAV) routing algorithm for efficient data communication between doctors and patients. This proposed method worked in three stages.

In recent decades, wireless body area networks have played an important role in health care applications. It facilitates the transmission of the patients' health data analysis report to the appropriate doctors.

In the first phase, biological sensors are connected to the human body via a controller node and collected data is transmitted via Bluetooth to the Personal Device Assistant (PDA). In the second phase, collected data will be transmitted via the Internet of things using an artificial bee colony algorithm. The second aids in determining the best route. In the third phase, unmanned aerial vehicles will use the best path to send collected data to doctors, caregivers, ambulances and cloud storage servers.

The simulation results show that the network's performance is superior when compared to existing approaches. The proposed algorithm achieves a high throughput, a lower delay, a higher link rate and a higher delivery rate.

The purpose of this paper is to review the most recent AUVSI unmanned vehicle show, with emphasis on the new robot innovations and applications on display.

In‐depth interviews with exhibitors of unmanned vehicles.

Unmanned vehicles are being coming more autonomous and addressing an ever‐increase range of applications in military, law enforcement, and commercial applications such as agriculture, fishing and rescue operations.

Customers will have to begin thinking of unmanned vehicle robots and able body helpers in all kinds of applications.

The paper presents a review of the latest innovations that one might have seen if they had been on the exhibition floor at the Las Vegas unmanned show.

The purpose of this study is to provide the full-state mathematical model and devise a nonlinear controller for a balloon-supported unmanned aerial vehicle (BUAV).

Newtonian mechanics is used to establish the nonlinear mathematical model of the proposed vehicle assembly which incorporates the dynamics of both balloon and quadrotor UAV. A controllable form of the nine degrees of freedom model is derived. Backstepping control is designed for the proposed model and simulations are performed to assess the tracking performance of the proposed control.

The results show that the proposed methodology works well for smooth trajectories in presence of wind gusts. Moreover, the final mathematical model is affine and various nonlinear control techniques can be used in the future for improved system performance.

Multi-rotor unmanned aerial vehicles (MUAVs) are equipped with controllers but are constrained by smaller flight endurance and payload carrying capability. On the contrary, lighter than air (LTA) aerial vehicles have longer flight times but have poor control performance for outdoor operations. One of the solutions to achieve better flight endurance and payload carrying capability is to augment the LTA balloon to MUAV. The novelty of this research lies in full-order mathematical modeling along with transformation to controllable form for the BUAV assembly.

The purpose of this paper is to review the 2007 AUVSI Conference and Show held in Washington DC with emphasis on unmanned vehicles or service robots, their application on the ground, in the air and in the water.

In‐depth interviews with exhibitors of unmanned vehicles and the providers of the technologies which are fundamental to their design and deployment. Also, attendance at conference presentations.

The unmanned vehicle industry is largely driven by government requirements, both military and civilian. Unmanned service robots are also found in commercial applications such as pipeline surveillance, crop monitoring and fish school location at sea.

Developers will be challenged to meet the need for improvements in speed, payload, sensor capabilities, autonomous operation and command and control of fleets of unmanned vehicles.

The paper offers insights into trends and new products in the unmanned vehicle industry.

Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.

This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.

This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.

It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.

The objective of this research is to investigate various neural network (NN) observer techniques for sensors fault identification and diagnosis of nonlinear system in consideration of numerous faults, failures, uncertainties and disturbances. For the importunity of increasing the faults diagnosis and reconstruction preciseness, a new technique is used for modifying the weight parameters of NNs without enhancement of computational complexities.

Various techniques such as adaptive radial basis functions (ARBF), conventional radial basis functions, adaptive multi-layer perceptron, conventional multi-layer perceptron and extended state observer are presented. For increasing the fault detection preciseness, a new technique is used for updating the weight parameters of radial basis functions and multi-layer perceptron (MLP) without enhancement of computational complexities. Lyapunov stability theory and sliding-mode surface concepts are used for the weight-updating parameters. Based on the combination of these two concepts, the weight parameters of NNs are updated adaptively. The key purpose of utilization of adaptive weight is to enhance the detection of faults with high accuracy. Because of the online adaptation, the ARBF can detect various kinds of faults and failures such as simultaneous, incipient, intermittent and abrupt faults effectively. Results depict that the suggested algorithm (ARBF) demonstrates more confrontation to unknown disturbances, faults and system dynamics compared with other investigated techniques and techniques used in the literature. The proposed algorithms are investigated by the utilization of quadrotor unmanned aerial vehicle dynamics, which authenticate the efficiency of the suggested algorithm.

The proposed Lyapunov function theory and sliding-mode surface-based strategy are studied, which shows more efficiency to unknown faults, failures, uncertainties and disturbances compared with conventional approaches as well as techniques used in the literature.

For improvement of the system safety and for avoiding failure and damage, the rapid fault detection and isolation has a great significance; the proposed approaches in this research work guarantee the detection and reconstruction of unknown faults, which has a great significance for practical life.

In this research, two strategies such Lyapunov function theory and sliding-mode surface concept are used in combination for tuning the weight parameters of NNs adaptively. The main purpose of these strategies is the fault diagnosis and reconstruction with high accuracy in terms of shape as well as the magnitude of unknown faults. Results depict that the proposed strategy is more effective compared with techniques used in the literature.

For the crews and assets of the European Union’s (EU’s) Joint Operations available today, but a vast area in the Mediterranean Sea to monitor, detection of small boats and rafts in distress can take up to several days or even fail at all. This study aims to outline how an energy-autonomous swarm of Unmanned Aerial System can help to increase the monitored sea area while minimizing human resource demand.

A concept for an unattended swarm of solar powered, unmanned hydroplanes is proposed. A swarm operations concept, vehicle conceptual design and an initial vehicle sizing method is derived. A microscopic, multi-agent-based simulation model is developed. System characteristics and surveillance performance is investigated in this delimited environment number of vehicles scale. Parameter variations in insolation, overcast and system design are used to predict system characteristics. The results are finally used for a scale-up study on a macroscopic level.

Miniaturization of subsystems is found to be essential for energy balance, whereas power consumption of subsystems is identified to define minimum vehicle size. Seasonal variations of solar insolation are observed to dominate the available energy budget. Thus, swarm density and activity adaption to solar energy supply is found to be a key element to maintain continuous aerial surveillance.

This research was conducted extra-occupationally. Resources were limited to the available range of literature, computational power number and time budget.

A proposal for a probable concept of operations, as well as vehicle preliminary design for an unmanned energy-autonomous, multi-vehicle system for maritime surveillance tasks, are presented and discussed. Indications on path planning, communication link and vehicle interaction scheme selection are given. Vehicle design drivers are identified and optimization of parameters with significant impact on the swarm system is shown.

The proposed system can help to accelerate the detection of ships in distress, increasing the effectiveness of life-saving rescue missions.

For continuous surveillance of expanded mission theatres by small-sized vehicles of limited endurance, a novel, collaborative swarming approach applying in situ resource utilization is explored.

This paper aims to deal with the numerical investigation of laminar separation bubble (LSB) characteristics (length and height of the bubble) of SS007 airfoil at the chord Reynolds number of Re_c = 0.68 × 10⁵ to 10.28 × 10⁵.

The numerical simulations of the flow around SS007 airfoil were carried out by using the commercial fluid dynamics (CFD) software, ANalysis system (ANSYS) 15. To solve the governing equations of the flow, a cell-centred control volume space discretisation approach is used. Wind tunnel experiments were conducted at the chord-based Reynolds number of Re_c = 1.6 × 10⁵ to validate the aerodynamic characteristics over SS007 airfoil.

The numerical results revealed that the LSB characteristics of a SS007 airfoil, and the aerodynamic performances are validated with experimental results. The lift and drag coefficients for both numerical and experimental results show very good correlation at Reynolds number 1.6 × 10⁵. The lift coefficient linearly increases with the increasing angle of attack (AOA) is relatively small. The corresponding drag coefficient was found to be very small. After the formation of LSB which leads to burst to cause airfoil stall, the lift coefficient decreases and increases the drag coefficient.

Low Reynolds number and LSB characteristics concept in aerodynamics is predominant for both civilian and military applications. These include high altitude devices, wind turbines, human powered vehicles, remotely piloted vehicles, sailplanes, unmanned aerial vehicle and micro aerial vehicle. In this paper, the micro aerial vehicle flight conditions considered and investigated the LSB characteristics for different Reynolds number. To have better aerodynamic performances, it is strongly recommended to micro aerial vehicle (MAV) design engineers that the MAV is to fly at 12 m/s (cruise speed).

MAVs and unmanned aerial vehicles seem to give some of the technical challenges of nature conservation monitoring and law enforcement a versatile, reliable and inexpensive solution.

The SS007 airfoil delays the flow separation and improves the aerodynamic efficiency by increasing the lift and decreasing the drag. The maximum increase in aerodynamic efficiency is 12.5% at stall angle of attack compared to the reference airfoil at Re = 2 × 10⁵. The results are encouraging and this airfoil could have better aerodynamic performance for the development of MAV.