Search Results (21)

Background: The integration of drone technology into healthcare logistics presents a significant opportunity to enhance the speed, reliability, and efficiency of medical sample transportation. Methods: This paper provides a narrative review of current advancements in drone technology, focusing on its application in the rapid and secure delivery of medical samples, particularly in urban and remote regions where traditional transportation methods often face challenges. Drawing from recent studies and case reports, the review highlights the role of technologies such as artificial intelligence (AI)-driven navigation systems, real-time monitoring, and secure payload management in mitigating logistical barriers like traffic congestion and geographical isolation. Results: Based on findings from various case studies, the review demonstrates how drones can significantly reduce transportation time and costs, while improving accessibility to healthcare services in underserved areas. Conclusions: This paper concludes that, while challenges such as regulatory hurdles and privacy concerns remain, ongoing technological advancements and the development of supportive regulatory frameworks have the potential to revolutionize medical logistics, ultimately improving patient outcomes and healthcare delivery. Full article

The application of drones to assist with healthcare delivery has grown rapidly over the last decade. This industry is supported by a growing research field, and we have undertaken a systematic review of the published literature. Web-based searches returned 290 relevant manuscripts published between 2010 and 2024. We applied Topic Modelling to this corpus of literature, which examines word association and connectedness within the research papers. The modelling identified two emerging research themes with little connection between them: those who used drones to deliver time-critical medical items and those who used drones to deliver non-time-critical medical items. The former was in response to medical emergencies, while the latter was for enhancing resilience in the healthcare supply chain. The topics within these research themes exhibited notable differences. The delivery of time-critical medical items theme comprised the topics of ‘Emergency Response’, ‘Defibrillator and Organ Delivery’, and ‘Search and Rescue’, whilst non-time-critical delivery researched the topics of ‘Supply Chain Optimisation’ and ‘Cost-Effectiveness’, ‘Overcoming Remoteness’, and ‘Pandemic Response’. Research on ‘Engineering and Design Considerations’ and ‘Ethical and Social Considerations’ cut across both research themes. We undertook further analysis to assess research topic alignment and identify knowledge gaps. We found that efforts are needed to establish a more standardised terminology for better alignment across the two emerging research themes. Future studies should focus on evaluating the impact of drone delivery on patient health using systematic methods. Additionally, exploring the economic viability of drone-based health services and addressing regulatory barriers are crucial for efficient and effective drone deployment in healthcare delivery systems. Full article

Background: Drone transport regulations in Europe require a crash-protected container (CPC) to be used for the carriage of dangerous goods. With increasing interest in the use of drones for medical logistics, the motivation behind this research was to investigate whether the existing approved medical carriers could also pass as CPCs. To date, there has been little practical experimentation on or theoretical research into the crash protection performance of medical containers. Methods: Addressing this gap, this paper reports findings from a series of drop test experiments to investigate the crashworthiness of a standard medical carrier bag used by the National Health Service (NHS) in the UK. Th drop tests were performed from heights of up to 122 m using standard medical carriers containing bags of dyed saline to examine the robustness of the carrier and whether it could contain any leakages, a key requirement for transporting dangerous goods. Results: The tests found that the medical carrier failed on some drops, with the zipped lid being identified as the main weakness. Conclusions: A new understanding of the carrier’s terminal velocity, impact acceleration, and failure mechanisms were gained and subsequent strengthening and waterproofing remedial measures recommended. New insights and practical recommendations are provided relating to performing formal drop tests and how to conduct these using a drone. Full article

The implementation of medical drones can quickly and efficiently expand the coverage range of an area, allowing for a faster response to incidences of out-of-hospital cardiac arrest and improving the subsequent survival rate of such incidences, while promoting sustainable health development goals under the configuration standards for automatic external defibrillators in China. In response to the problem of the selection of locations for medical drone vertiports (for take-off and landing) that are equipped with automatic external defibrillation facilities, a survival function was introduced to establish a model for site selection, with the primary optimization objective of maximizing the average survival rate of patients and taking the operating costs of a system into account. At the same time, considering the constraints of drone phase operation time, energy consumption, coverage range, etc., a medical drone vertiport site selection model was established for emergency cardiac arrest needs. An improved immune algorithm was applied to the model’s calculations and the analysis of the results, using the Jinnan District in Tianjin as an example. The results show that the proposed model and algorithm are feasible and applicable. The Jinnan District in the city of Tianjin requires a total of 24 medical drone vertiports in order to achieve full coverage of an area under the “golden 4-minute” rescue time. When the average survival rate of patients is 0.9, the operation results are deemed optimal, and the average survival rate of patients is 64.06%. Compared to ground ambulances currently used in hospitals, the implementation of medical drones could significantly shorten response time, improve the average survival rate of patients by 41.96%, and effectively improve the existing low survival rate and the accessibility of medical services. The results of this study can provide decision-making support for the planning of automatic external defibrillators in public places and the construction of sustainable and efficient emergency medical service systems. Full article

Uncrewed aerial vehicles (UAVs), commonly known as drones, have emerged as transformative tools in the healthcare sector, offering the potential to revolutionize medical logistics, emergency response, and patient care. This scoping review provides a comprehensive exploration of the diverse applications of drones in healthcare, addressing critical gaps in existing literature. While previous reviews have primarily focused on specific facets of drone technology within the medical field, this study offers a holistic perspective, encompassing a wide range of potential healthcare applications. The review categorizes and analyzes the literature according to key domains, including the transport of biomedical goods, automated external defibrillator (AED) delivery, healthcare logistics, air ambulance services, and various other medical applications. It also examines public acceptance and the regulatory framework surrounding medical drone services. Despite advancements, critical knowledge gaps persist, particularly in understanding the intricate interplay between technological challenges, the existing regulatory framework, and societal acceptance. This review highlights the need for the extensive validation of cost-effective business cases, the development of control techniques that can address time and resource savings within the constraints of real-life scenarios, the design of crash-protected containers, and the establishment of corresponding tests and standards to demonstrate their conformity. Full article

In major metropolitan areas, the growing levels of congestion pose a significant risk of supply chain disruptions by hindering surface transportation of commodities. To address this challenge, cargo drones are emerging as a potential mode of transport that could improve the reliability of the pharmaceutical supply chain and enhance healthcare. This study proposes a novel hybrid workflow that combines machine learning and a geographic information system to identify the fewest locations where providers can initiate cargo drone services to yield the greatest initial benefits. The results show that by starting a service in only nine metropolitan areas across four regions of the contiguous United States, drones with a robust 400-mile range can initially move more than 28% of the weight of all pharmaceuticals. The medical community, supply chain managers, and policymakers worldwide can use this workflow to make data-driven decisions about where to access the largest opportunities for pharmaceutical transport by drones. The proposed approach can inform policies and standards such as Advanced Air Mobility to help address supply chain disruptions, reduce transportation costs, and improve healthcare outcomes. Full article

Natural disasters, including earthquakes, floods, landslides, tsunamis, wildfires, and hurricanes, have become more common in recent years due to rapid climate change. For Post-Disaster Management (PDM), authorities deploy various types of user equipment (UE) for the search and rescue operation, for example, search and rescue robots, drones, medical robots, smartphones, etc., via the Internet of Robotic Things (IoRT) supported by cellular 4G/LTE/5G and beyond or other wireless technologies. For uninterrupted communication services, movable and deployable resource units (MDRUs) have been utilized where the base stations are damaged due to the disaster. In addition, power optimization of the networks by satisfying the quality of service (QoS) of each UE is a crucial challenge because of the electricity crisis after the disaster. In order to optimize the energy efficiency, UE throughput, and serving cell (SC) throughput by considering the stationary as well as movable UE without knowing the environmental priori knowledge in MDRUs aided two-tier heterogeneous networks (HetsNets) of IoRT, the optimization problem has been formulated based on emitting power allocation and user association combinedly in this article. This optimization problem is nonconvex and NP-hard where parameterized (discrete: user association and continuous: power allocation) action space is deployed. The new model-free hybrid action space-based algorithm called multi-pass deep Q network (MP-DQN) is developed to optimize this complex problem. Simulations results demonstrate that the proposed MP-DQN outperforms the parameterized deep Q network (P-DQN) approach, which is well known for solving parameterized action space, DQN, as well as traditional algorithms in terms of reward, average energy efficiency, UE throughput, and SC throughput for motionless as well as moveable UE. Full article

The world has been proactively seeking solutions to control the spread of the COVID-19 virus since 2020. A major defensive action is implementing contactless services into everyday activities to reduce viral spread. Drones can provide contactless services in transporting goods and medical supplies, thus reducing the risk of spreading the virus. This paper aims to investigate the future trends of commercial uses for drones in Australia in the next five years. It will explore the impact of the COVID-19 pandemic on the unmanned aerial vehicles (UAVs) industry and its different applications in Australia over the same timeframe; it also considers whether the use of drones in medical services will increase due to the epidemic. Primary data are gathered and evaluated to consider these issues, supported by a set of secondary data. The research aims to provide a holistic direction for the UAV industry, and in particular, for the Australian drone service providers and regulator to modify their operation strategies. Full article

Saudi Arabia’s health sector faces pressing challenges in disaster and prehospital care delivery, such as prolonged response times, limited access to remote areas, and strained medical resources. Integrating drone technology has emerged as an innovative approach to address these challenges and revolutionize healthcare delivery. Drones can significantly enhance response times, increase access to underserved areas, and reduce the burden on existing medical infrastructure. A detailed analysis of global case studies demonstrates the successful use of drones in healthcare delivery, emphasizing the importance of regulatory frameworks and public–private partnerships. These examples provide valuable insights into Saudi Arabia’s health sector transformation. The potential benefits of integrating drone technology include improved patient outcomes, increased efficiency, and cost savings. To ensure the successful implementation of this transformative approach, it is crucial to establish clear regulatory guidelines, invest in research and development, and foster collaboration between the government, private sector, and healthcare stakeholders. The aim of this study is to explore the potential of drone technology in transforming healthcare delivery in Saudi Arabia, particularly within disaster response and prehospital care services. Full article

Drones may be able to deliver automated external defibrillators (AEDs) directly to bystanders of out-of-hospital cardiac arrest (OHCA) events, improving survival outcomes by facilitating early defibrillation. We aimed to provide an overview of the available literature on the role and impact of drones in AED delivery in OHCA. We conducted this scoping review using the PRISMA-ScR and Arksey and O’Malley framework, and systematically searched five bibliographical databases (Medline, EMBASE, Cochrane CENTRAL, PsychInfo and Scopus) from inception until 28 February 2022. After excluding duplicate articles, title/abstract screening followed by full text review was conducted by three independent authors. Data from the included articles were abstracted and analysed, with a focus on potential time savings of drone networks in delivering AEDs in OHCA, and factors that influence its implementation. Out of the 26 included studies, 23 conducted simulations or physical trials to optimise drone network configuration and evaluate time savings from drone delivery of AEDs, compared to the current emergency medical services (EMS), along with 1 prospective trial conducted in Sweden and 2 qualitative studies. Improvements in response times varied across the studies, with greater time savings in rural areas. However, emergency call to AED attachment time was not reduced in the sole prospective study and a South Korean study that accounted for weather and topography. With growing interest in drones and their potential use in AED delivery spurring new research in the field, our included studies demonstrate the potential advantages of unmanned aerial vehicle (UAV) network implementation in controlled environments to deliver AEDs faster than current EMS. However, for these time savings to translate to reduced times to defibrillation and improvement in OHCA outcomes, careful evaluation and addressing of real-world delays, challenges, and barriers to drone use in AED delivery is required. Full article

The term unmanned aerial vehicle (UAV) was post-applied in the 1980s to describe remotely piloted multi-purpose, unmanned, autonomous aircraft. The terms unmanned aircraft systems with data terminal connectivity (UAS) and remotely piloted aircraft systems (RPV, RPAS—military systems) are also used. This review aims to analyze the feasibility of using UAVs to support emergency medical systems in the supply and urgent care ranges. The implementation of drones in the medical security system requires proper planning of service cooperation, division of the area into sectors, assessment of potential risks and opportunities, and legal framework for the application. A systematic literature search was conducted to assess the applicability based on published scientific papers on possible medical drone applications in the field of urgent mode. The widespread applications of UAVs in healthcare are concerned with logistics, scope, and transportability, with framework legal constraints to effectively exploit opportunities for improving population health, particularly for costly critical situations. Full article

Recently, unmanned aerial vehicles (UAVs), also known as drones, have come in a great diversity of several applications such as military, construction, image and video mapping, medical, search and rescue, parcel delivery, hidden area exploration, oil rigs and power line monitoring, precision farming, wireless communication and aerial surveillance. The drone industry has been getting significant attention as a model of manufacturing, service and delivery convergence, introducing synergy with the coexistence of different emerging domains. UAVs offer implicit peculiarities such as increased airborne time and payload capabilities, swift mobility, and access to remote and disaster areas. Despite these potential features, including extensive variety of usage, high maneuverability, and cost-efficiency, drones are still limited in terms of battery endurance, flight autonomy and constrained flight time to perform persistent missions. Other critical concerns are battery endurance and the weight of drones, which must be kept low. Intuitively it is not suggested to load them with heavy batteries. This study highlights the importance of drones, goals and functionality problems. In this review, a comprehensive study on UAVs, swarms, types, classification, charging, and standardization is presented. In particular, UAV applications, challenges, and security issues are explored in the light of recent research studies and development. Finally, this review identifies the research gap and presents future research directions regarding UAVs. Full article

To reduce distribution risk and improve the efficiency of medical materials delivery under major public health emergencies, this paper introduces a drone routing problem with time windows. A mixed-integer programming model is formulated considering contactless delivery, total travel time, and customer service time windows. Utilizing Dantzig–Wolfe decomposition, the proposed optimization model is converted into a path-based master problem and a pricing subproblem based on an elementary shortest path problem with resource constraints. We embed the pulse algorithm into a column generation framework to solve the proposed model. The effectiveness of the model and algorithm is verified by addressing different scales of Solomon datasets. A case study on COVID-19 illustrates the application of the proposed model and algorithm in practice. We also perform a sensitivity analysis on the drone capacity that may affect the total distribution time. The experimental results enrich the research related to vehicle routing problem models and algorithms under major public health emergencies and provide optimized relief distribution solutions for decision-makers of emergency logistics. Full article

One of the common causes of a heart attack is fibrillation, a condition that causes an irregular and often abnormally fast heart rate. There is scientific evidence that the survival rate of sudden cardiac arrest patients who are rescued with cardiopulmonary resuscitation (CPR) and with the use of an automated external defibrillator (AED) is significantly increased. Despite the recommendation that automated external defibrillators should be installed in the workplace, along with a proper management system and training for employees on how to use the device, less than 70% of non-residential areas have an AED installed. The situation is even worse in residential areas, with less than 30% having an AED installed. This research concerns the development of a medical drone managing system that can deliver an AED in case of emergency. An application was developed that can be installed on the mobile phone and/or tablet of the patient or the accompanying person. In the event of a heart attack, the patient or the accompanying person can call a medical drone by sending coordinates to the drone station and a notification to medical staff. The drone station administrator can respond by sending the drone, which automatically lands at the patient’s location. After being tested in a simulation situation, the operational field test yielded satisfactory results. The medical drone can land within 1.5 m of the destination. The designed AED drone can be used not only to deliver AEDs, but also first aid kits and prescribed drugs suitable for medical care. Such a system is especially useful in the current context of the COVID-19 pandemic. Full article

Wireless rechargeable sensor networks (WRSN) are utilized in environmental monitoring, traffic video surveillance, medical services, etc. In most existing schemes, WRSNs provide sustainable energy for sensor nodes by employing one or more wireless charging vehicles (WCVs). However, two essential drawbacks, regional limitations and traveling speed limitations, constrain these schemes when applied in hostile and large-scale environments. On the other hand, benefiting from the intrinsic flexibility, high flight speed, low cost, and small size of drones, some works have used drones to charge sensor nodes. However, suffering from limited battery capacities, it is also hard to only use drones in large-scale WRSNs. To overcome the drawbacks of WCVs and drones, we proposed a novelty wireless charging system that deploys WCV, WCV-carried drones, and wireless charging pads (pads) in a large-scale wireless sensor network. Based on this new wireless charging system, we first formulated a pad deployment problem for minimizing the total number of pads subject to each sensor in the pad region that only can be charged by drones. In this work, three near-optimal algorithms, i.e., greedy, K-mean, and static, for the pad deployment problem are proposed. Then, to form a sustainable WRSN, we elucidated the collaborative charging scheduling problem with the deadlines of sensors. To guarantee the maximum number of sensors to be charged before the deadlines, we also presented an approximation algorithm to find the collaborative charging scheduling of WCV and WCV-carried drones with the help of pads based on the three deployment pad schemes. Through extensive simulations, we demonstrate the effectiveness of the proposed deployment pad schemes. and that the number of pads obtained by the greedy and K-mean scheme was generally lower than that of the static scheme with respect to network density, WCV region, and flight range. Then, we also examined the proposed collaborative charging scheduling scheme by extensive simulations. The results were compared and showed the effectiveness of the proposed schemes in terms of lifetime, the percentage of nodes being charged in time, the average move time of drones, the percentage of nodes being charged late by the drones, and the charge efficiency of all vehicles under different traffic loads. Related statistical analyses showed that the percentage of nodes being charged in time and the percentage of nodes being charged late based on the greedy and K-mean schemes were slightly better than those of the static scheme, but the charge efficiency of drones of the static scheme was significantly superior to that of the K-mean scheme under a busy network. Full article