Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult-to-access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

Recently, the world witnessed a significant increase in the number of used drones, with a global and continuous rise in the demand for their multi-purpose applications. The pervasive aspect of these drones is due to their ability to answer people’s needs. Drones are providing users with a bird’s eye that can be activated and used almost anywhere and at any time. However, recently, the malicious use of drones began to emerge among criminals and cyber-criminals alike. The probability and frequency of these attacks are both high and their impact can be very dangerous with devastating effects. Therefore, the need for detective, protective and preventive counter-measures is highly required. The aim of this survey is to investigate the emerging threats of using drones in cyber-attacks, along the countermeasures to thwart these attacks. The different uses of drones for malicious purposes are also reviewed, along the possible detection methods. As such, this paper analyzes the exploitation of drones vulnerabilities within communication links, as well as smart devices and hardware, including smart-phones and tablets. Moreover, this paper presents a detailed review on the drone/Unmanned Aerial Vehicle (UAV) usage in multiple domains (i.e civilian, military, terrorism, etc.) and for different purposes. A realistic attack scenario is also presented, which details how the authors performed a simulated attack on a given drone following the hacking cycle. This review would greatly help ethical hackers to understand the existing vulnerabilities of UAVs in both military and civilian domains. Moreover, it allows them to adopt and come up with new techniques and technologies for enhanced UAV attack detection and protection. As a result, various civilian and military anti-drones/UAVs (detective and preventive) countermeasures will be reviewed.

Security analysis of drones systems: Attacks, limitations, and recommendations

A survey on position-based routing protocols for Flying Ad hoc Networks (FANETs)

This paper considers a last-mile delivery system in which a delivery truck operates in coordination with a fleet of unmanned aerial vehicles (UAVs, or drones). Deploying UAVs from the truck enables customers located further from the depot to receive drone-based deliveries. The problem is first formulated as a mixed integer linear program (MILP). However, owing to the computational complexity of this problem, only trivially-sized problems may be solved directly via the MILP. Thus, a heuristic solution approach that consists of solving a sequence of three subproblems is proposed. Extensive numerical testing demonstrates that this approach effectively solves problems of practical size within reasonable runtimes. Additional analysis quantifies the potential time savings associated with employing multiple UAVs. The analysis also reveals that additional UAVs may have diminishing marginal returns. An analysis of five different endurance models demonstrates the effects of these models on UAV assignments. The model and heuristic also support anticipated future systems that feature automation for UAV launch and retrieval.

The multiple flying sidekicks traveling salesman problem: Parcel delivery with multiple drones

UAV assistance paradigm: State-of-the-art in applications and challenges

This paper addresses the drone-aided delivery and pickup planning of medication and test kits for patients with chronic diseases who are required to visit clinics for routine health examinations and/or refill medicine in rural areas. For routine healthcare services, the work proposes two models: the first model is to find the optimal number of drone center locations using the set covering approach, and the second model is the multi-depot vehicle routing problem with pickup and delivery requests minimizing the operating cost of drones in which drones deliver medicine to patients and pick up exam kits on the way back such as blood and urine samples. In order to improve computational performance of the proposed models, a preprocessing algorithm, a Partition method, and a Lagrangian Relaxation (LR) method are developed as solution approaches. A cost-benefit analysis method is developed as a tool to analyze the benefits of drone-aided healthcare service. The work is tested on a numerical example to show its applicability.

Drone-Aided Healthcare Services for Patients with Chronic Diseases in Rural Areas

This paper addresses the design of a parcel delivery system using drones, which includes the strategic planning of the system and operational planning for a given region. The amount of payload affects the battery consumption rate (BCR), which can cause a disruption in delivery of goods if the BCR was under-estimated in the planning stage or cause unnecessarily higher expenses if it was over-estimated. Hence, a reliable parcel delivery schedule using drones is proposed to consider the BCR as a function of payload in the operational planning optimization. A minimum set covering approach is used to model the strategic planning and a mixed integer linear programming problem (MILP) is used for operational planning. A variable preprocessing algorithm and primal and dual bound generation methods are developed to improve the computational time for solving the operational planning model. The optimal solution provides the least number of drones and their flight paths to deliver parcels while ensuring the safe return of the drones with respect to the battery charge level. Experimental data show that the BCR is a linear function of the payload amount. The results indicate the impact of including the BCR in drone scheduling, 3 out of 5 (60%) flight paths are not feasible if the BCR is not considered. The numerical results show that the sequence of visiting customers impacts the remaining charge.

Drone Delivery Scheduling Optimization Considering Payload-induced Battery Consumption Rates

This paper presents a two-phase mathematical framework for efficient power network damage assessment using unmanned aerial vehicle (UAV). In the first phase, a two-stage stochastic integer programming optimization model is presented for damage assessment in which the first stage determines the optimal UAV locations anticipating an arrival of an extreme weather event, and the second stage is to adjust the UAV locations, if necessary, when the arrival time of the predicted extreme weather becomes closer with updated information. UAV paths to scan the power network are generated in the second phase to minimize operating costs and final damage assessment completion time of the UAVs. Computational techniques are developed to help reduce the solution time. Numerical experiments show that the proposed stochastic model outperforms the deterministic counterpart in terms of the total UAV pre-positioning setup cost. Additionally, sensitivity analysis discovered the relations among damage assessment time, UAV pre-positioning setup cost, and operating cost.

Seon Jin Kim

Papers

Drone-Aided Healthcare Services for Patients with Chronic Diseases in Rural Areas

Drone Delivery Scheduling Optimization Considering Payload-induced Battery Consumption Rates

Multi-UAV Pre-Positioning and Routing for Power Network Damage Assessment

Drone flight scheduling under uncertainty on battery duration and air temperature

Safety and Security Management with Unmanned Aerial Vehicle (UAV) in Oil and Gas Industry