Delivery Of Medical Supplies Research Articles

Quantitative Ground Risk Assessment for Urban Logistical Unmanned Aerial Vehicle (UAV) Based on Bayesian Network

The Unmanned Aerial Vehicle (UAV) has been used for the delivery of medical supplies in urban logistical distribution, due to its ability to reduce human contact during the global fight against COVID-19. However, due to the reliability of the UAV system and the complex and changeable operation scene and population distribution in the urban environment, a few ground-impact accidents have occurred and generated enormous risks to ground personnel. In order to reduce the risk of UAV ground-impact accidents in the urban logistical scene, failure causal factors, and failure modes were classified and summarized in the process of UAV operation based on the accumulated operation data of more than 20,000 flight hours. The risk assessment model based on the Bayesian network was built. According to the established network and the probability of failure causal factors, the probabilities of ground impact accidents and intermediate events under different working conditions were calculated, respectively. The posterior probability was carried out based on the network topology to deduce the main failure inducement of the accidents. Mitigation measures were established to achieve the equivalent safety level of manned aviation, aiming at the main causes of accidents. The results show that the safety risk of the UAV was reduced to 3.84 × 10−8 under the action of risk-mitigation measures.

Targeted Delivery Platforms for the Treatment of Multiple Sclerosis.

Multiple sclerosis (MS) is a neurodegenerative condition of the central nervous system (CNS) that presents with varying levels of disability in patients, displaying the significance of timely and effective management of this complication. Though several treatments have been developed to protect nerves, comprehensive improvement of MS is still considered an essential bottleneck. Therefore, the development of innovative treatment methods for MS is one of the core research areas. In this regard, nanoscale platforms can offer practical and ideal approaches to the diagnosis and treatment of various diseases, especially immunological disorders such as MS, to improve the effectiveness of conventional therapies. It should be noted that there is significant progress in the development of neuroprotective strategies through the implementation of various nanoparticles, monoclonal antibodies, peptides, and aptamers. In this study, we summarize different particle systems as well as targeted therapies, such as antibodies, peptides, nucleic acids, and engineered cells for the treatment of MS, and discuss their potential in the treatment of MS in the preclinical and clinical stages. Future advances in targeted delivery of medical supplies may offer new strategies for complete recovery as well as practical treatment of progressive forms of MS.

Human drone interaction in delivery of medical supplies: A scoping review of experimental studies

The COVID-19 pandemic, ageing populations and the increasing shortage of skilled workers pose great challenges for the delivery of supplies for people with and without care needs. The potential of drones, as unmanned air vehicles, in healthcare are huge and are discussed as an effective new way to delivery urgent medicines and medical devices, especially in rural areas. Although the advantages are obvious, perspectives of users are important particularly in the development process. Investigating human drone interaction could potentially increase usefulness and usability. The present study aims to perform a systematic scoping review on experimental studies examining the human drone interaction in deliveries of drugs and defibrillators. Two databases (MEDLINE and CINAHL) and references of identified publications were searched without narrowing the year of publication or language. Studies that investigated the human drone interaction or medical delivery with drones in an experimental manner were included (research articles). All studies that only simulated the delivery process were excluded. The search revealed 83 publications with four studies being included. These studies investigated the user experience of drone delivered defibrillators, but no study was identified that investigated the human drone interaction in the delivery of drugs. Three categories of human drone interaction were identified: landing, handover, and communications. Regarding landing and handover, the most important issue was the direct physical contact with the drone while regarding communications users need clearer instructions about drone´s direction, sound and look like. The identified studies used technology-driven approaches by investigating human drone interaction in already existing technologies. Users must become integral part of the whole development process of medical drone services to reduce concerns, and to improve security, usability and usefulness of the system. Human drone interaction should be developed according to the identified categories of human drone interaction by using demand- and technology-driven approaches.

Supporting value sensitivity in the humanitarian use of drones through an ethics assessment framework

AbstractThe current humanitarian use of drones is focused on two applications: disaster mapping and medical supply delivery. In response to the growing interest in drone deployment in the aid sector, we sought to develop a resource to support value sensitivity in humanitarian drone activities. Following a bottom-up approach encompassing a comprehensive literature review, two empirical studies, a review of guidance documents, and consultations with experts, this work illuminates the nature and scope of ethical challenges encountered by humanitarian organizations embarking upon innovation programmes. The Framework for the Ethics Assessment of Humanitarian Drones (FEAHD) identifies five values and five key questions related to ethical considerations along the decision chain of humanitarian drone activities. It fills a gap between high-level, principle-based guidance related to humanitarian innovation, and detailed operation-oriented checklists for projects involving the use of drones. In this way, the FEAHD contributes to support value sensitivity in the humanitarian use of drones.

Blockchain-based secure delivery of medical supplies using drones

The advantages provided by the drones with regards to three dimensional mobility and ease of deployment makes them a viable candidate for 5G and beyond (B5G) networks. Significant amount of research has been conducted on the aspect of networking for using drones as base stations to provide different services. In this work, we deviate from the traditional use of drones to provide connectivity and explore the delivery of products through drones in the context of maintaining social distancing. However, drone delivery process for critical applications such as delivering medical supplies is vulnerable to attacks such as impersonation attacks. The security of drone operation is important to save the users from any breaches that can lead to financial and physical losses. To cope with these security issues and to make the delivery process transparent, we propose a blockchain-based drone delivery system that registers and authenticates the participating entities including products (medical supplies), warehouse (medical centers) and drones. To this end, we utilize Ethereum platform for implementation of blockchain and smart contract and we present an analysis of different factors that influence the authentication process in terms of time and the number of transactions. Furthermore, to make the communication of a drone with command and control center more secure and robust, we use machine learning (ML)-based intrusion detection system.

GaRuDa: A Blockchain-Based Delivery Scheme Using Drones for Healthcare 5.0 Applications

Over the years, the healthcare industry has transformed from being hospital-centric to patient-centric. This shift is mainly due to the convergence of emergent technologies such as Internet of Things (IoT)-based healthcare, fifth generation (5G)-assisted networking, and data-driven analytics through artificial intelligence. The convergence, referred to as Healthcare 5.0, has improved healthcare services to support real-time analytics, user mobility, remote monitoring, and personalized user experience through decentralized applications. However, the medical supply chain systems and delivery operations among healthcare stakeholders suffer from limitations of harsh environmental conditions due to restricted zones, rough terrains, war-prone areas, poor road conditions, congested traffic, and remote locations. Thus, the Internet of Drones (IoD) is deployed in Healthcare 5.0 supply chains to streamline and expedite the medical delivery process through open channels (i.e. the Internet). However, the Internet is an open channel that is prone to malicious activities which can violate the privacy and confidentiality of patient data. Blockchain is a promising technology that can handle the security and reliability of drone delivery among untrusted open channels. Motivated by the aforementioned facts, we propose GaRuDa, a blockchain-based drone delivery scheme for Healthcare 5.0 applications. The proposed scheme integrates IoD and blockchain through 5G-enabled tactile Internet to facilitate low-latency responsive delivery of medical supplies that can be chronologically monitored and tracked among different stakeholders. We compared the proposed scheme with the traditional medical delivery scheme with payment gateways to demonstrate its effectiveness in terms of data storage, computation, and communication costs. The simulation results obtained show that the average transaction cost has been reduced by ≈ 44.56 percent, and 5G tactile Internet has a reduced latency of 0.051 ms compared to 18.3 ms in 4G LTE service. The average communication overheads have reduced by ≈ 67.34 percent compared to traditional 4G LTE and orthogonal frequency-division multiplexing channels, which indicates the scheme's viability.

Development of Medical Drone for Blood Product Delivery: A Technical Assessment

Drone is the well-known technology in military and amateur application. Recently, the drone was used to deliver goods and parcels. There is an increasing need for urgent delivery of medical supplies in low resource setting due to traffic congestion and terrain obstacles. The delivery of blood in emergency cases such as postpartum hemorrhaging is challenging and can be delayed due to geographical condition in underserved area. Postpartum hemorrhaging needs an immediate blood transfusion with proper blood product to save the life of mother and baby. To address to this need, a drone that can deliver blood supply to the desired location may be a good option. Therefore, research has been conducted to identify the baseline of drone specifications for blood delivery. A Hexacopter with the ArduPilot firmware and a Lithium-Polymer battery of 16,000 mAh were used to study the applicability of blood products delivery using drone. Using several tests to assess drone limitations, experimental data was obtained and analyzed using distinctive methods. The results indicated that the thrust-to-weight ratio of the drone play a paramount role for the drone performance and flight time. The GPS guidance performance showed a reliable and stable flight with only a slight deviation of ±6 meters during the tests. Finally, a test flight was conducted to simulate the actual test location from Queen Elizabeth Hospital and Hospital Wanita dan Kanak-Kanak, Likas, Sabah. The developed drone reached a flight time of 25 minutes covering 8.38 km with 4.3 kg take-off weight.

Intricacies of medical drones in healthcare delivery: Implications for Africa

Unmanned aerial vehicles, also known as drones, can play a critical role in delivering health care. In this paper, we reviewed the literature to ascertain (1) the various medical supplies delivered by drones, (2) the challenges to the successful use of medical drones and (3) the potential benefits of medical drones. Implications for the African context is then provided. In achieving this objective, we employed a systematic literature review methodology and defined search strings, searched for relevant literature from PubMed, Scopus and Web of Science databases following a review protocol. The snowball technique was similarly used to search for other papers as well. A total of 17 out of 69 papers were included in the review after screening and applying a quality appraisal criterion. The results indicate that blood, AEDs, drugs, vaccines, and laboratory test samples etc were identified as part of the medical supplies aerially delivered by drones. Regulations, cost, misuse (evasion of people's privacy) and psychological effect on people who experienced drones used for bombing are part of the challenges that could result from using the technology for delivery of medical supplies. The benefits derived from drones range from reducing response times during health emergencies thus helping to save more lives, to being environmentally friendly as the CO2 emissions levels are lower than conventional delivery by trucks and cars. In conclusion, drone technology has opened a new phase for the health sector and to sustain this technological innovation in Africa, there is the need for inclusive innovation to make drones safer and acceptable. This could be achieved by developing the needed policy framework with the regulators, providing other health resources to complement the use of drones, embarking on sensitizations on the usefulness of drones through cultural underpinnings of rural communities about drones and training the needed health personnel to handle dispatches of medical supplies with drones.

“As It Is Africa, It Is Ok”? Ethical Considerations of Development Use of Drones for Delivery in Malawi

Since 2016, drones have been deployed in various development projects in sub-Saharan Africa, where trials, tests, and studies have been rolled out in countries, including Tanzania, Uganda, Rwanda, Malawi, Ghana, and the Democratic Republic of the Congo. The use cases of drones vary, ranging from imagery collection to transportation of vaccines, lab samples, blood products, and other medical supplies. A wide range of stakeholders is involved, including governments, international organizations, educational institutions, as well as industry. Based on a field study conducted in 2019, this article investigates how drones are used for medical supply delivery in Malawi—a country where the community is underserved for healthcare and related infrastructure underdeveloped, while airspace is largely open and regulations generally relaxed. The objective of presenting this case study is to contribute to the evidence regarding the rapid deployment of medical cargo drones across the African continent, and to spark critical reflections over the utility, suitability, and impacts of incorporating drones in the existing health supply chain systems in resource-poor settings. The discussion revolves around two aspects: 1) the emergent “African Drone Rise”—is it ok “as it is Africa”? and 2) the normative role of technology in the aid sector—is it “a solution looking for a problem”? In conclusion, a call for more structured guidance for the systematic examination and evaluation of the medical cargo drone case is raised.

Design and Implementation of Drone in Healthcare Applications

A drone, in simple words, is a type of flying robot that can be remotely controlled by a human operator. It is in technology terms also known as Unmanned Aerial Vehicle (UAV). With many new advancements in drone technology, it is expected that drones may expand further to include diagnostic capabilities, namely in the imaging field. The drone presented in this paper will also be used for the delivery of medical supplies. With a lock system implemented on the container attached, it ensures the safety of the supplies till they reach the rightful person. The drone could be used by online pharmaceuticals, which are booming as people are gaining interest in them. The designed system is an internet-based drone using the principles of IoT.

Design and Implementation of a Quadcopter Based on a Linear Quadratic Regulator (LQR)

This paper presents the design and construction and control of a quadcopter drone for Aerial Data Collection (ADC). The frame of the drone was designed using CadDian Software and the parts were printed using a 3D printer. The flight controller was based on Arduino board using an Atmega328p microprocessor with GSM, GPS and GPRS for sending data over the internet and also enhancing long range flight. A feedback control system was developed and tested to control the stability of drone. The proposed control strategy of the drone was tested for a case of pursuit of trajectory and also for speed of response and the findings were very positive confirming the appropriateness of the control measures for independent and autonomous flying with promising precision. This Unmanned Aerial Vehicle (UAV) fitted with IoT has the capability of collecting and sending data over the internet and therefore can be used in many applications including risk assessment, forestry management, urban planning, coastal zone management, infrastructure monitoring, post-disaster damage assessment and delivery of medical supplies.

Abstract 151: Barriers and Opportunities for a Drone-Delivered AED Network in Durham, North Carolina

Background: The general public is unfamiliar with the concept of medical drones delivering life-saving technologies. Our research sought to define stakeholder attitudes towards development of drone-based emergency care for out-of-hospital cardiac arrest. Methods: Using qualitative methodology, we explored key stakeholder attitudes about using a drone to deliver automated external defibrillators (AED), challenges and facilitators to early establishment of a drone AED network, implementation considerations, and factors related to long-term sustainability. We identified 22 key individuals as potential respondents based on professional position; 16 respondents participated in data collection. Research participants included leaders in government, healthcare, emergency services, business, community, and the aviation industry (regulation and drone operation). Interview data were recorded and transcribed; data were analyzed using NVivo. A coding schema was developed based on constructs identified in previous literature and inductive consideration of this study’s data, including both thematic and descriptive coding. Results: We found broad support for a drone-delivered AED network. Such a network was perceived as valuable for reduced response times and for enhanced access to hard-to-reach areas. Identified challenges included operationalizing an autonomous drone AED network, privacy and safety concerns, current legal and regulatory requirements, financial liabilities, public buy-in and concern for public actually using an AED, and the need for research on treatment and cost- effectiveness of a drone network. Facilitators of development for a drone AED network included solidifying key partnerships (including integration into current EMS or fire services), identifying viable funding from private and public entities, and learning from existing drone models (e.g. commercial package or medical supply delivery). Conclusion: This study found general and conceptual support for the development of a drone network for AED delivery across key informants from an array of related fields. Such information should be considered in developing a regional drone AED network.

A prototype of Fixed Wing UAV for delivery of Medical Supplies

A prototype Unmanned Aerial Vehicle (UAV) is designed for the purpose of last mile delivery to supply medicines and vaccines. This work aims to ascertain that UAVs can be employed to decrease transportation times, increased power efficiency, and improved safety for transportation of necessary products. The prototype model is design to deliver 1 kg maximum payload up to 5 km with an endurance time of 30 minutes. The model is fabricated with a wing span of 1.5 m, Aspect ratio 7, and contains NACA 6 series airfoil shape as its cross section. During the transportation of payload, it has to fly beyond the line of sight which requires an autonomous Pixhawk flight controller installed in the model. Autonomous module aids in the safe flight avoiding the obstacles during the operation. To comply with government regulations for flying the model cruises at an altitude of 350 feet. After reaching the desired GPS destination, the payload is delivered to the target customer via parachute. However the model requires a runway length of 200 m for its takeoff and landing operation.

A location-driven approach for warehouse location problem

After a large-scale disaster occurred, medical service centers are needed to provide appropriate medical treatments for injured patients. To support those medical service centers, a warehouse should be set up to stock medical supplies that can be distributed to medical service centers in different quantities in multiple periods. However, the delivery of medical supplies depends on practical environmental conditions. In practice, the cost including the travel time and monetary cost from the warehouse to the medical service center presents a complex relationship. The existing methods do not consider this complex relationship. To overcome the pitiful of the existing methods, we propose a location-driven method. To implement the proposed location-driven method, three numerical algorithms are considered. Among them, the fixed-point-based heuristic algorithm is compared with the existing two algorithms to illustrate its superiority. Also, the bootstrap resampling technique is applied to obtain a reasonable region for improving the flexibility of locating the warehouse. To illustrate the effectiveness and efficiency of the proposed method, several simulation studies are considered. The computational results show the advantages of the proposed method in determining the warehouse location and identifying the reasonable region for locating the warehouse.

Drone for medical products transportation in maternal healthcare: A systematic review and framework for future research.

Medical products transportation has become an important research topic requiring multidisciplinary collaboration among experts in medicine, engineering, and health economics. Current modes of transportation are unable to overcome the limited settings in maternal healthcare, particularly during the event of obstetric emergencies. The drone is a promising medical product aerial transportation (MedART) that holds an enormous potential for delivery of medical supplies in the healthcare system. We conducted a systematic review to examine scientific evidence of positive impact of drone transportation on maternal health. The following electronic databases were searched from inception to July 2019: ScienceDirect, PubMed, and EMBASE. The report was made in accordance with the principles of PRISMA guidelines. The search terms used were related to drones including unmanned aerial vehicle (UAV) and unmanned aerial system (UAS), and related to obstetric/maternal including obstetric emergencies and postpartum hemorrhage. Studies were selected if the intervention used were drones, and if any direct or indirect maternal health indicators were reported. Meta-analysis was not done throughout the study in view of the anticipated heterogeneity of each study. Our initial search yielded a total of 244 relevant publications, from which 236 were carried forward for a title and abstract screening. After careful examination, only two were included for systematic synthesis. Among the reasons for exclusion were irrelevance to maternal health purpose, and irrelevance to drone applications in healthcare. An updated search yielded one additional study that was also included. Overall, two studies assessed drones for blood products delivery, and one study used drones to transport blood samples. A significant deficiency was found in the number of reported studies analyzing mode of medical products transportation and adaptation of drones in maternal healthcare. Future drone research framework should focus on maternal healthcare-specific drone applications in order to reap benefits in this area.

A DroneGo Disaster Relief Response System

<p>To support the Puerto Rico hurricane disaster scenario, we develop a DroneGo disaster response system by establishing the following models. First, we establish a location analysis model for ISO containers based on the coverage of video reconnaissance and the priority comparison between the two required missions–medical supply delivery and video reconnaissance. According to the locations of 11 harbors in Puerto Rico, we select three suitable harbors to position three cargo containers called CON 1, 2 and 3 to conduct the missions. Second, we build two packing configuration models to design the packing configuration for containers. In one model, we recommend a drone fleet for CON 1 and 3 according to reconnaissance conditions, and then put drones into containers in order. In another model for CON 2, we determine the type of drones according to the medical supply demands of hospitals. For both models, the number of drones of each type is determined by the enumeration method and the packing placement is determined by the greedy algorithm. The algorithms are coded in Visual C++ and MATLAB. The computational results show that the space utilizations for the three containers are all above 80.8%. Third, we design a drone flight plan model based on graph theory. According to the time and space constraints of drones, we devise flight plans as well as delivery routes and schedule. The computational results show that the coverage of video reconnaissance is up to 70.1%. Finally, we carry out the error and sensitivity analysis, discuss the strengths and weaknesses of our models, and design the future work. In addition, a two-page memo that summarizes our modeling results, conclusions, and recommendations is given at the end of the paper.</p>

Federated Learning for UAVs-Enabled Wireless Networks: Use Cases, Challenges, and Open Problems

The use of Unmanned Aerial Vehicles (UAVs) for wireless networks is rapidly growing as key enablers of new applications, including: surveillance and monitoring, military, delivery of medical supplies, telecommunications, etc. In particular, due to their unique proprieties such as flexibility, mobility, and adaptive altitude, UAVs can act as mobile base stations to improve capacity, coverage, and energy efficiency of wireless networks. On the other hand, UAVs can operate as mobile terminals to enable many applications such as item delivery and real-time video streaming. In such context, data-driven Deep Learning-assisted (DL) approaches are gaining a growing interest to not only exploit the huge amount of generated data, but also to optimize the network operations, and hence ensure the QoS requirements of these emerging wireless networks. However, UAVs are resource-constrained devices especially in terms of computing and power resources, and traditional DL-assisted schemes are cloud-centric, which require UAVs’ data to be sent and stored in a centralized server. This represents a critical issue since it generates a huge network communication overhead to send raw data towards the centralized entity, and hence may lead to network bandwidth and energy inefficiency of UAV devices. In addition, the transferred data may contain personnel data such as UAVs’ localization and identity, which can directly affect UAVs’ privacy concerns. As a solution, Federated Deep Learning (FDL), or distributed DL, was introduced, where the basic idea is to keep raw data where it is generated, while sending only users’ local trained DL models to the centralized entity for aggregation. Due to its privacy-preserving and low communication overhead and latency, FDL is much more adequate for many UAVs-enabled wireless applications. In this work, we provide a general introduction of FDL application for UAV-enabled wireless networks. We first introduce the FDL concept and its fundamentals. Then, we highlight the possible applications of FDL in UAVs-enabled wireless networks by addressing the suitability and how to use FDL to deal with target challenges. Finally, we discuss about key technical challenges, open issues, and future research directions on FDL-based approaches in such context.

Design And Implementation Of Gps Based Medical Services Using Drone

This paper is aimed to provide medical assistance to people through the delivery of medical supplies by unmanned drones. The use of unmanned drones’ benefits people in distant areas around the world. The paper gives attentionto the design of a biocompatible payload and a drone to accomplish medical supply delivery. Design of the drone healthcare delivery network isfacilitatingstructured and low-cost delivery of healthcare to save lives. Dronesare capable of sustainable flight, which need not human presence on board, and have enough control for performingnecessary functions. This paper utilizes a range of hardware components and software platforms that were integrated into the overall design of the medical drone. Hardware components includes IMU enabled GPS, ArduCopter 2.6 Flight Controller, Data Transmission and Receiving module, Electronic Speed Control Circuits, DC Motors, Propellers, LiPo battery, Servo Connectors. GPS is used for navigation in betweenground stations that are automated, to deliver necessary medications in locations that lack enough roads. Unmanned aerial vehicle is remotely or automatically controlled. Software platform used is ArduPilot Mission Planner and mobile phone or tabletapps can be used to track and navigate. Network is managed by drone operating system to monitor weather data from every ground stationand it optimizes the drone routes in this proposed approach we are designing a paper which is effective in many applications like transporting blood and small emergency medicines such as first-aid kits. Unmanned Aerial Vehicles can be used in future to provide medical help in field of surveillance and at the time of earthquake, drones help rescuers to locate survivors.The military in combat can use drones, and it can also be used for humanitarian aid.

Automated emergency paramedical response system.

With the evolution of technology, the fields of medicine and science have also witnessed numerous advancements. In medical emergencies, a few minutes can be the difference between life and death. The obstacles encountered while providing medical assistance can be eliminated by ensuring quicker care and accessible systems. To this effect, the proposed end-to-end system-automated emergency paramedical response system (AEPRS) is semi-autonomous and utilizes aerial distribution by drones, for providing medical supplies on site in cases of paramedical emergencies as well as for patients with a standing history of diseases. Security of confidential medical information is a major area of concern for patients. Confidentiality has been achieved by using decentralised distributed computing to ensure security for the users without involving third-party institutions. AEPRS focuses not only on urban areas but also on semi-urban and rural areas. In urban areas where access to internet is widely available, a healthcare chatbot caters to the individual users and provides a diagnosis based on the symptoms provided by the patients. In semi-urban and rural areas, community hospitals have the option of providing specialised healthcare in spite of the absence of a specialised doctor. Additionally, object recognition and face recognition by using the concept of edge AI enables deep neural networks to run on the edge, without the need for GPU or internet connectivity to connect to the cloud. AEPRS is an airborne emergency medical supply delivery system. It uses the data entered by the user to deduce the best possible solution, in case of an alerted emergency situation and responds to the user accordingly.

Use of Drone Technology for Delivery of Medical Supplies During Prolonged Field Care.

Care of trauma casualties in an austere environment presents many challenges, particularly when evacuation is not immediately available. Man-packable medical supplies may be consumed by a single casualty, and resupply may not be possible before evacuation, particularly during prolonged field care scenarios. We hypothesized that unmanned aerial drones could successfully deliver life-sustaining medical supplies to a remote, denied environment where vehicle or foot traffic is impossible or impractical. Using an unmanned, rotary- wing drone, we simulated delivery of a customizable, 4.5kg load of medical equipment, including tourniquets, dressings, analgesics, and blood products. A simulated casualty was positioned in a remote area. The flight was preprogrammed on the basis of grid coordinates and flew on autopilot beyond visual range; data (altitude, flight time, route) were recorded live by high-altitude Shadow drone. Delivery time was compared to the known US military standards for traversing uneven topography by foot or wheeled vehicle. Four flights were performed. Data are given as mean (± standard deviation). Time from launch to delivery was 20.77 ± 0.05 minutes (cruise speed, 34.03 ± 0.15 km/h; mean range, 12.27 ± 0.07 km). Medical supplies were delivered successfully within 1m of the target. The drone successfully returned to the starting point every flight. Resupply by foot would take 5.1 hours with an average speed of 2.4km/h and 61.35 minutes, with an average speed of 12 km/h for a wheeled vehicle, if a rudimentary road existed. Use of unmanned drones is feasible for delivery of life-saving medical supplies in austere environments. Drones repeatedly and accurately delivered medical supplies faster than other methods without additional risk to personnel or manned airframe. This technology may have benefit for austere care of military and civilian casualties.