Found 12 results
Opinion
22 August 2024Medical Drones for Public Health Emergency Preparedness, Response, and Resilience: Delivering Health for All
Amid a global metacrisis of health, environmental and economic challenges, medical delivery drones (or uncrewed aerial vehicles) offer a promising method to prepare for, and rapidly respond, to future emergencies. This opinion article summarizes the current medical delivery drone landscape, evidence base, and policy implications in the context of public health emergencies, such as pandemics, natural disasters, and humanitarian crises, with a particular emphasis on the region of sub-Saharan Africa. Using a multilateral, international health policy perspective, key challenges and opportunities, such as the development of sustainable funding mechanisms, robust regulatory frameworks, and capacity building, are identified.
Article
15 August 2024Hazardous Gas Monitoring with IoT Enabled Drone in Underground Tunnels and Cavities
Considering the healthiness of the atmosphere in mining activities (e.g., tunnelling), two of the most important parameters to be monitored are the concentration of oxygen and the presence of harmful gases such as CO2. Traditional methods for their measurement are fixed platforms and portable gas detectors carried by miners; they are incapable of recognizing sudden or short-term pollution events or correctly accounting for the spatial scarcity of gases. A UAV (Unmanned Aerial Vehicle) device capable of guaranteeing the measurement and continuous monitoring of concentrations has been designed. By using innovative technologies, it promotes digitization in the mining sector. This approach replaces current methods that, while effective at detecting and measuring environmental parameters, are slow, routine, and heavily reliant on human input. It saves productive expenses in the sector since it reduces costs compared to hiring a field technician for activities such as analysis of environmental conditions. This saving is about 110 euros daily, representing a 32% saving per working day for each mining technical responsible for environmental control. It also obtains a 3D spatial distribution of contaminants, a high sample resolution and a high sample resolution.. It reduces inspection time in mining works and the data collection time by more than 50%. The ECODRONE project constitutes a contribution to the MINE THE GAP challenge is a project financed with European funds whose line of desire aims to combine the innovation and development of SMEs or business groups from different regions of the mining, raw materials and materials sector. This program is aimed at strengthening the existing value chains and developing new industrial ones while designing new procedures, automated technologies, information and communication flows, which increase efficiency in the consumption of resources. All of the above implies integration with a circular economy and respect for European and global efficiency policies aimed at sustainability, industrial modernization, human health and the environment.
Review
06 August 2024Considerations for Unmanned Aerial System (UAS) Beyond Visual Line of Sight (BVLOS) Operations
This paper, intended for expert and non-expert audiences, evaluates the technical and regulatory requirements for Unmanned Aerial Systems (UAS) to operate beyond visual line of sight (BVLOS) services. UAS BVLOS operations have the potential to unlock value for the industry. However, the regulatory requirements and process can be complex and challenging for UAS operators. The work explored the BVLOS regulatory regime in the UK, Europe and the US and found similarities in process and requirements covering themes like Detect and Avoid (DAA), Remote identification and Reliable Connectivity. A unifying goal across these jurisdictions is to operate BVLOS safely and securely in non-segregated airspace. However, operating BVLOS in segregated airspace as the default or routine mode could accelerate approval and adoption. The paper reviewed existing challenges, highlighting Coverage, Capacity and Redundancy as critical for UAS BVLOS Operations. The work also highlighted the crucial role of Non-terrestrial Network (NTN) assets like Satellites and HAPS (High Altitude Platform Station) since terrestrial networks (not optimised for aerial platform coverage) may not be reliable for BVLOS connectivity.
Review
02 August 2024A Promising and Forward-Looking Advancement Using Drones: Perspectives from Indian Sericulture
Drone integration in sericulture marks a promising advancement within the sector, leveraging recent technological strides in unmanned aerial vehicles (UAVs) across various industries like agriculture and healthcare. While the adoption of drones in sericulture remains nascent, their potential benefits, particularly in chemical spraying tailored to sericulture’s unique environmental conditions, are increasingly recognized. This paper explores the efficacy of drone-based pesticide spraying and smart fertilization methods optimized for sericulture settings. The rapid deployment capabilities of drones facilitate enhanced network connectivity, potentially catalyzing rural development and economic prosperity within the sericulture community. However, ethical and operational concerns persist regarding drone use across industries, necessitating robust regulatory frameworks and ethical guidelines. Furthermore, advancements in artificial intelligence augment drone capabilities, enabling automated inspections and improved performance across diverse applications. This paper underscores the need for further research and the development of standardized operating protocols to harness the transformative potential of drone technology in sericulture. Key focus areas include optimizing pesticide delivery, ensuring environmental sustainability, and addressing ethical considerations surrounding drone utilization. By leveraging UAVs for precision spraying and smart fertilization, sericulture stands poised to enhance productivity, bolster economic development, and navigate emerging challenges in agricultural production.
Article
24 June 2024An Integer Programming Approach to Multi-Trip Routing of Delivery Drones at Load-Dependent Flight Speed
In recent years, there has been a growing interest in utilizing drones for parcel delivery among companies, aiming to address logistical challenges. However, effective optimization of delivery routes is essential. A theoretical framework termed the Flight Speed-aware Vehicle Routing Problem (FSVRP) has emerged to address the variability in drone flight speed based on payload weight. Several approximate methods have been proposed to solve the FSVRP. Our research endeavors to optimize parcel delivery efficiency and reduce delivery times by introducing a novel delivery problem. This problem accounts for multiple deliveries while considering the variability in flight speed due to diverse payloads. Through experimentation, we evaluate the efficacy of our proposed method compared to existing approaches. Specifically, we assess total flight distance and flight time. Our findings indicate that even in cases where the payload exceeds maximum capacity, all parcels can be delivered through multiple trips. Furthermore, employing a multi-trip FSVRP approach results in an average reduction of 10% in total flight time, even when payload capacities are not exceeded.
Article
12 June 2024Optimized Real Time Single-Drone Path Planning for Harvesting Information from a Wireless Sensor Network
We consider a remote sensing system in which fixed sensors are placed in a region, and a single drone flies over the region to collect information from cluster heads. We assume that the drone has a fixed maximum range and that the energy consumption for information transmission from the cluster heads increases with distance according to a power law. Given these assumptions, we derive local optimum conditions for a drone path that either minimizes the total or maximum energy required by the cluster heads to transmit information to the drone. We show how a homotopy approach can produce a family of solutions for different drone path lengths so that a locally optimal solution can be found for any drone range. We implement the homotopy solution in Python and demonstrate the tradeoff between drone range and cluster head power consumption for several geometries. Execution time is sufficiently rapid for the computation to be performed in real time so that the drone path can be recalculated on the fly. The solution is shown to be globally optimal for sufficiently long drone path lengths. A proof of concept implementation in Python is available on GitHub. For future work, we indicate how the solution can be modified to accommodate moving sensors.
Article
08 May 2024Assessing Drone Return-to-Home Landing Accuracy in a Woodland Landscape
While aerial photography continues to play an integral role in forest management, its data acquisition can now be obtained through an unmanned aerial vehicle (UAV), commonly referred as a drone, instead of conventional manned aircraft. With its feasibility, a drone can be programed to take off, fly over an area following predefined paths and take images, then return to the home spot automatically. When flying over forests, it requires that there is an open space for a vertical takeoff drone to take off vertically and return safely. Hence, the automatic return-to-home feature on the drone is crucial when operating in a woodland landscape. In this project, we assessed the return-to-home landing accuracy based on a permanently marked launch pad nested in a wooded area on the campus of Stephen F. Austin State University in Nacogdoches, Texas. We compared four models of the DJI drone line, with each flown 30 missions over multiple days under different weather conditions. When each drone returned to the home launch spot and landed, the distance and direction from the launch spot to the landing position was measured. Results showed that both the Phantom 4 Advanced and the Spark had superior landing accuracy, whereas the Phantom 3 Advanced was the least accurate trailing behind the Phantom 4 Pro.
Article
26 April 2024Exact and Heuristic Approaches to Surveillance Routing with a Minimum Number of Drones
The rising cost and scarcity of human labor pose challenges in security patrolling tasks, such as facility security. Drones offer a promising solution to replace human patrols. This paper proposes two methods for finding the minimum number of drones required for efficient surveillance routing: an ILP-based method and a greedy method. We evaluate these methods through experiments, comparing the minimum number of required drones and algorithm runtime. The findings indicate that the ILP-based method consistently yields the same or a lower number of drones needed for surveillance compared to the greedy method, with a 73.3% success rate in achieving better results. However, the greedy method consistently finishes within one second, whereas the ILP-based method sometimes significantly increases when dealing with 14 more locations. As a case study, we apply the greedy method to identify the minimum drone surveillance route for the Osaka-Ibaraki Campus of Ritsumeikan University.
Article
19 March 2024Designing a Quadcopter for Fire and Temperature Detection with an Infrared Camera and PIR Sensor
In agriculture, medicine, and engineering, sudden fire outbreaks are prevalent. During such events, the ensuing fire spread is extensive and unpredictable, necessitating crucial data for effective response and control. To address this need, the current initiative focuses on utilizing an Unmanned Aerial Vehicle (UAV) with an Infrared (IR) sensor. This sensor detects and analyses temperature variations, accompanied by additional camera footage capturing thermal images to pinpoint the locations of the incidents precisely. The UAV’s programming is executed using Arduino-Nano and mission planner software, interfacing with the Pixhawk flight controller operating in a guided mode for autonomous navigation. The UAV configuration includes a radio module interfacing with Arduino-Nano, a flight controller, and remote-control functionality. The flight duration is approximately 10–15 min, contingent upon flight dynamics and environmental temperature. Throughout its airborne operation, the UAV transmits live telemetry and log feeds to the connected computer, displaying critical parameters such as altitude, temperature, battery status, vertical speed, and distance from the operator. The Pixhawk flight controller is specifically programmed to govern the UAV’s behavior, issuing warnings to the pilot in case of low voltage, prompting a timely landing to avert potential crashes. In case of in-flight instability or a crash, the mission planner can trace the UAV’s location, facilitating efficient recovery and minimizing costs and component availability losses. This integrated approach enhances situational awareness and mitigation strategies, offering a comprehensive solution for managing fire incidents in diverse fields.
Article
26 January 2024A Lightweight Visual Navigation and Control Approach to the 2022 RoboMaster Intelligent UAV Championship
In this paper, an autonomous system is developed for drone racing. On account of their vast consumption of computing resources, the methods for visual navigation commonly employed are discarded, such as visual-inertial odometry (VIO) or simultaneous localization and mapping (SLAM). A series of navigation algorithms for autonomous drone racing, which can operate without the aid of the information on the external position, are proposed: one for lightweight gate detection, achieving gates detection with a frequency of 60 Hz; one for direct collision detection, seeking the maximum passability in-depth images. Besides, a velocity planner is adopted to generate velocity commands according to the results from visual navigation, which are enabled to perform a guidance role when the drone is approaching and passing through gates, assisting it in avoiding obstacles and searching for temporarily invisible gates. The approach proposed above has been demonstrated to successfully help our drone passing-through complex environments with a maximum speed of 2.5 m/s and ranked first at the 2022 RoboMaster Intelligent UAV Championship.
