The rapid loss of biodiversity worldwide is unprecedented, with more species facing extinction now than at any other time in human history. Key factors contributing to this decline include habitat destruction, overexploitation, and climate change. There is an urgent need for innovative and effective conservation practices that leverage advanced technologies, such as autonomous drones, to monitor wildlife, manage human-wildlife conflicts, and protect endangered species. While drones have shown promise in conservation efforts, significant technological challenges remain, particularly in developing reliable, cost-effective solutions capable of operating in remote, unstructured, and open-ended environments. This paper explores the technological advancements necessary for deploying autonomous drones in nature conservation and presents the interdisciplinary scientific methodology of the WildDrone doctoral network as a basis for integrating research in drones, computer vision, and machine learning for ecological monitoring. We report preliminary results demonstrating the potential of these technologies to enhance biodiversity conservation efforts. Based on our preliminary findings, we expect that drones and computer vision will develop to further automate time consuming observational tasks in nature conservation, thus allowing human workers to ground conservation actions on evidence based on large and frequent data.

Highlights What are the main findings? In conservation environments, ground risk is largely driven by transient populations (e.g., tourism and ranger activity), which are not reliably captured by standard population raster datasets. Formal safety requirements and field realities are often misaligned in wildlife operations, creating operational friction between prescribed procedures and practical execution. What are the implications of the main findings? Ground-risk assessments in conservancies should prioritise bottom-up, activity-based population estimates, using raster products primarily for triangulation and sensitivity analysis. Reducing friction between safety requirements and field needs, through iterative crew optimisation and mission-specific procedure design, can improve both operational efficiency and procedural compliance.Highlights What are the main findings? In conservation environments, ground risk is largely driven by transient populations (e.g., tourism and ranger activity), which are not reliably captured by standard population raster datasets. Formal safety requirements and field realities are often misaligned in wildlife operations, creating operational friction between prescribed procedures and practical execution. What are the implications of the main findings? Ground-risk assessments in conservancies should prioritise bottom-up, activity-based population estimates, using raster products primarily for triangulation and sensitivity analysis. Reducing friction between safety requirements and field needs, through iterative crew optimisation and mission-specific procedure design, can improve both operational efficiency and procedural compliance.Abstract Safe Beyond Visual Line of Sight (BVLOS) operations are increasingly required for wildlife monitoring and conservation, yet existing regulatory frameworks are rarely tailored to protected areas characterised by low population density and limited infrastructure. This paper presents a field-based use case illustrating how the Specific Operations Risk Assessment (SORA) methodology can be applied to conservation-oriented BVLOS missions under Kenyan airspace conditions, including coordination within military-controlled airspace. We evaluate three population-density estimation approaches (qualitative, bottom-up, and top-down) against available ground truth, and compare tabulated and analytical SORA methods for deriving the Ground Risk Class. The work illustrates how SORA 2.5 structures ground and air risk reasoning in a conservation context, while retrospective review identifies limitations in containment, Operational Safety Objectives, and tactical mitigation performance requirements. Field trials involved five concurrent teams and 30 personnel conducting over 260 flights and more than 60 h of UAS activity across the Ol Pejeta Conservancy, providing insights into multi-team coordination under field conditions. Field implementation revealed areas of misalignment between prescribed safety requirements and operational realities, prompting iterative adaptation of workflows and procedures. Observed outcomes included reductions in team size (25-50%) and procedural steps (18%), derived from retrospective comparison of field procedures. A lightweight Uncrewed Traffic Management prototype was also trialled, revealing practical limitations in conservancy environments. Finally, we present a ten-step framework for developing field-ready safety procedures to support risk-informed decision-making in non-standard operational contexts. The findings provide empirically grounded guidance on applying SORA principles to conservation UAS missions, without proposing a new risk framework or generalised operational model.

Beyond Visual Line of Sight (BVLOS) operations of Uncrewed Aerial Systems (UAS) hold significant potential for transforming many sectors, but face significant regulatory, safety, and operational complexity challenges. This paper presents a framework developed for planning and executing safe and compliant BVLOS missions in the context of wildlife conservation. While validated through a case study at the Ol Pejeta Conservancy, Kenya, this approach may also serve as a foundation for similar operations in other complex environments. Leveraging the widely adopted Specific Operations Risk Assessment (SORA), we developed an operational framework that addressed both air and ground risks. Key measures include strategic planning, coordination with local authorities, and the establishment of contingency volumes and operational procedures to ensure safety. Field trials have demonstrated the practical challenges of ensuring airspace safety and highlighted the importance of close collaboration with Air Traffic Control (ATC) and the need for more robust, and redundant Command & Control (C2) solutions for long-range or remote operations. This study provides a replicable framework applicable to diverse BVLOS scenarios while offering insights specific to wildlife conservation. Documentation related to this work is publicly accessible: https://github.com/GuyMaalouf/ WD-June24- BVLOS-Docs

This paper presents experimental results of utilizing the 3GPP standardized RTK Observation State Representation (OSR). The work investigates the 3GPP LTE Positioning Protocol (LPP)'s applicability for enabling reliable and accurate global localization during UAV operations. The experiments are conducted with a UAV connected to a 5G network, utilizing a cellular connection for 1) directly receiving RTCM data via an open-source 3GPP LPP client developed by the authors, and 2) establishing a C2 link to the Ground Control Station. A 24-hour measurement with the UAV remaining at a static position has been conducted. The results indicate a reliable performance with no loss of RTK GNSS fixed solution. Furthermore, two similar static experiments have been conducted with: 1) receiving RTCM data via an NTRIP client connected to an RTK reference network service, indicating no difference in the two approaches' performance when compared, and; 2) with no RTCM data provided, to compare the baseline performance of the UAV's GNSS. The operational reliability, meaning its performance during operational conditions when receiving RTCM data via LPP, has been investigated with UAV flights. The results consist of measurements from 1) the UAV's RTK GNSS to investigate its performance during flight, and; 2) the 5G network to investigate its performance in different altitudes and potentially correlate loss of RTK GNSS fixed solution due to the network connectivity. Seventeen flight experiments have been conducted, resulting in a total flight time of 3 hours and 19 minutes distributed over 32.06 kilometers. No loss of RTK GNSS fixed solution was observed, showing stable operational reliability in the area where the flight tests were conducted.

The integration of UAS into lower airspace requires trustworthy Detect and Avoid (DAA) capabilities, which hinge on robust Airspace Situational Awareness (ASA) technologies. This paper introduces a structured approach to effectively address and simplify the challenges of ASA for UAS. It introduces Operational Classes (OCs) for categorising airspace risks, System Configurations (SysCons) for grouping distinct system structures, and DAA Strategies, based on ACAS-Xu, for improving UAS safety and operational efficiency through proactive and reactive measures. Furthermore, it explores diverse detection technologies for both cooperative and non-cooperative aircraft, analysing their strengths and limitations, and recommends which technologies to use for various SysCons.

Facemasks have been employed to mitigate the spread of SARS-CoV-2. The community effect of providing cloth facemasks on COVID-19 morbidity and mortality is unknown. In a cluster randomised trial in urban Bissau, Guinea-Bissau, clusters (geographical areas with an average of 19 houses), were randomised to an intervention or control arm using computer-generated random numbers. Between 20 July 2020 and 22 January 2021, trial participants (aged 10+ years) living in intervention clusters (n = 90) received two 2-layer cloth facemasks, while facemasks were only distributed later in control clusters (n = 91). All participants received information on COVID-19 prevention. Trial participants were followed through a telephone interview for COVID-19-like illness (3+ symptoms), care seeking, and mortality for 4 months. End-of-study home visits ensured full mortality information and distribution of facemasks to the control group. Individual level information on outcomes by trial arm was compared in logistic regression models with generalised estimating equation-based correction for cluster. Facemasks use was mandated. Facemask use in public areas was assessed by direct observation. We enrolled 39,574 trial participants among whom 95% reported exposure to groups of >20 persons and 99% reported facemasks use, with no difference between trial arms. Observed use was substantially lower (~40%) with a 3%, 95%CI: 0–6% absolute difference between control and intervention clusters. Half of those wearing a facemask wore it correctly. Few participants (532, 1.6%) reported COVID-19-like illness; proportions did not differ by trial arm: Odds Ratio (OR) = 0.81, 95%CI: 0.57–1.15. 177 (0.6%) participants reported consultations and COVID-19-like illness (OR = 0.83, 95%CI: 0.56–1.24); 89 participants (0.2%) died (OR = 1.34, 95%CI: 0.89–2.02). Hence, though trial participants were exposed to many people, facemasks were mostly not worn or not worn correctly. Providing facemasks and messages about correct use did not substantially increase their use and had limited impact on morbidity and mortality. Trial registration: clinicaltrials.gov: NCT04471766 .

U-space, the EU implementation of air traffic management of drones, is one of the key enablers to realizing a safe integration of crewed and uncrewed aviation in shared airspace. The development and integration of U-space and its services will support a high level of digitalization and automation of drones and has been ongoing since 2017 when its blueprint was published by SESAR. Now with the Commission Implementing Regulation (EU) 2021/{ 664/665/666} in force, the establishment of U-space airspace in the EU is becoming a reality. This paper surveys available research and state-of-the-art on U-space. A total of 60 publications have been identified using the presented literature search method. Based on the insights gained from the literature search, eight subdomains have been defined. Each publication has been assigned to one primary subdomain and one or more secondary subdomain(s) within U-space. The subdomains are described and discussed and probable future research perspectives are extracted.

One of the main challenges in the real-world adoption of multi-Uncrewed Aerial Vehicle (UAV) systems lies in the specification of operations and the management of dynamic tasks in varied operational contexts. In this paper, we propose a multi-UAV planning architecture to reduce the level of specialized expertise necessary for handling multi-UAV systems. Furthermore, this work is the first step towards designing a multi-UAV planning architecture that integrates with the U-space services specified in EU regulatory 2021/664. We propose two declarative languages: (i) an Agent-Language for expressing mitigation and safety objectives for individual UAVs, and (ii) an Operation-Language to enable users to plan high-level multi-UAV operations based on the available resources. The languages enable automatic on-the-fly re-planning if any UAVs abort the mission unexpectedly. The initial result of the multi-UAV planning architecture is showcased in three simulated UAVs running as Software-In-The-Loop (SITL), to demonstrate its capabilities.

In this paper, we propose a concept design for an Airspace Advisory Service (AAS), assisting Unmanned Aerial System (UAS) operators with Detect and Avoid capabilities during flight operations. The AAS utilizes the traffic information service from the U-space service providers. Based on adjacent air traffic, two risk indexes are introduced for each aircraft near the operating Unmanned Aerial Vehicle (UAV); 1) a Collision Risk Index, assessing the probability of the aircraft entering the UAV's Remain Well Clear volume, and; 2) Intruder Risk Index, assessing the probability of the aircraft breaching the UAV's Operational Volume. Both risk indexes are fuzzy logic-based, and the calculation of them is presented using real flight data for two different flight scenarios. Moreover, the Traffic Advisory and Resolution Advisory principles from the TCAS concept are applied for each aircraft by calculating dynamic elliptical models based on their horizontal velocity and expected angular change of heading. A recommended advisory is determined for each aircraft and provided to the UAS operator for maintaining a safe operation. The proposed concept design has been integrated into an existing ground control station software, named QGroundControl, as a proof of concept. Input from experienced UAS operators, eg. how to visually display relevant information for decision-making, have been included in the integration process. The comparison between QGroundControl with/without the AAS integrated shows the enhancement of situational awareness. Simulated air traffic has been used for validating the behavior of the AAS and for testing its CPU usage when processing up to 15 aircraft simultaneously. A higher CPU usage was observed but is not considered to have a significant influence on the overall CPU performance.

Unmanned Aerial System (UAS) Traffic Management (UTM) is a key enabler for unleashing the full potential of the UAS technology. Europe is currently in the progress of implementing the initial services of the U-Space framework, the European Union (EU) version of UTM. With the Commission Implementing Regulation (EU) 2021/664 now in force, defining the regulatory framework for U-Space, the establishment of U-spaces in EU will soon be a reality in some countries. In this paper, a stand-alone component, named DroneID5G, is designed to comply with the Network Identification (ID) service specified in 2021/664. The Drone5GID is capable of providing the Remote ID of a UAS to the national Common Information Service Provider using LTE for Machine Type Communication (LTE-M) technology. A custom protocol, based on the ASTM F311-19 standard, has been implemented between the DroneID5G and a USSP prototype for reducing the message size being transmitted. Additionally, Detect And Avoid (DAA) capabilities have been implemented by relaying air traffic data, obtained from the Traffic Information service specified in 2021/664, into a UAS's flight controller via the DroneID5G. We present the initial experimental results, consisting of both ground and flight measurements, for investigating the performance and reliability of LTE-M network. The RSSI, RSRP, and RSRQ values have been collected at different geographical positions and altitudes from 20 to 100 meters above the ground. The ground measurements demonstrate the handover capabilities and reliability. From the flight measurements, it can be seen that the RSRP and RSRQ values decreases in relation to the altitude. Finally, the DAA capabilities are demonstrated, enabling the UAS to automatically detect an incoming aircraft and activate its failsafe.

The development of Unmanned Aerial Systems (UASs) continuously improves and advances the technology, which is a key enabler for many new applications, such as autonomous Beyond Visual Line of Sight (BVLOS) operations. However, ensuring a sufficient level of safety and performance of an UAS can be a challenging task, since it requires systematic experimental validation in order verify and document the reliability, robustness, and fault tolerance of the UAS and its critical components. In this paper we propose the UAV Auto Test Framework (UAVAT Framework), a framework for easy, systematic, and efficient experimental validation of the reliability, fault tolerance, and robustness of a multirotor small Unmanned Aerial Systems (sUAS) and its software and hardware components. We describe the hardware and software used for the UAVAT Framework setup, which consists of a Motion Capture (MoCap) system, a multirotor sUAS, and a tethered power system. In addition, we introduce the concept of test modules, a “plug-and-play” software component with a set of recommended guidelines for defining testing configurations and enabling easy reuse and distribution of software components for sUAS testing. The capabilities of the UAVAT Framework are demonstrated by presenting the results from two developed test modules targeting endurance testing of a multirotor sUAS and Fault Detection (FD) for abnormal behaviour detection.

While the complexity of development and cost of Unmanned Aerial Systems (UAS) decrease, the use and market of UASs continuously increase. The benefits of UASs can however only be fully realized when they are allowed to autonomously fly Beyond Visual Line of Sight (BVLOS). To allow safe and efficient autonomous BVLOS flights, the European initiative SESAR came out with the concept of U -space to integrate UASs into the already populated airspace. There is however currently no open high-level software architecture that realizes the concept of U -space for autonomous BVLOS operations. In this work, we present an initial proposal of such a system, a service-oriented architecture named ROS-DOTS. We follow a modular design that supports the integration of services that can be modified and replaced independently. The benefit of our modular design is the use of high-level abstraction models for UAS operations, using modular services that are developed independently between each other. To show the potential of ROS-DOTS, we present a use case where several services in the architecture and a commercial UAS traffic management system work together to generate a flight plan for a UAS operation, that then can be retrieved from our system and unloaded into a UAS.

With the advances in drone technology, the demand for long-distance drone flights Beyond Visual Line of Sight (BVLOS), is increasing. A prerequisite to BVLOS flights is reliable communication between Unmanned Aerial Vehicle (UAV) and Ground Control Station (GCS). Moreover, BVLOS operations can require multiple pilots during the flight, for example at takeoff and landing, who can take manual control if necessary. This necessitates a means to handover control between multiple pilots during the flight. This paper will explore options for line-of-sight radio links, for reducing the required bandwidth by optimizing the communication between the UAV and GCS, and for supporting multiple pilots. A MAVLink library to optimize the communication between the UAV and GCS has been designed and implemented. The library successfully reduced the communication from 11440 bytes/s to 951 bytes/s. A component for pilot handover has similarly been designed and successfully tested in real-world conditions. The LOS radios selected have been used successfully together with the MAVLink library in real-world SORA-approved BVLOS operations at a maximum radio LOS distance of 1375 m.

Safe autonomous Beyond Visual Line of Sight (BVLOS) flight is critical for the widespread exploitation of Unmanned Aerial Systems (UASs). Satisfying safety legislation requires documenting compliance with a raft of substantial requirements, a step which very few commercially available UASs have yet taken. Assessments under BVLOS conditions are required - but illegal for unassessed UASs. We propose to enable safe BVLOS flight tests using an Independent Failsafe System (IFS), which can be added to an Unmanned Aerial Vehicle (UAV) and enable a pilot to remotely monitor flights and terminate them safely via parachute if necessary. Our IFS has been designed for use under the European Union (EU) UAS legislation. In this paper, we describe this IFS and define a systematic approach for integrating its use into the Specific Operations Risk Assessment (SORA) process necessary for BVLOS certification. The use of this IFS to safely fly an (otherwise) unsafe UAV has been approved by the Danish Civilian Aviation Authority (CAA) for BVLOS flights with a range of small multirotor UAVs. The results of experimental evaluations in closed airspace are presented.

Autonomous drones operate in an airspace populated by other drones and manned aviation. Unmanned traffic management (UTM) systems are necessary to safely and efficiently integrate drones into the existing airspace traffic. Existing UTM systems however cannot resolve airspace conflicts without risking altering critical elements of planned drone operations. To enable the resolution of conflicts while ensuring that drone missions still fulfill their purpose, we propose DOTS, a declarative language to specify drone missions. From this specification, DOTS generates a planning system that can dynamically replan drone flights without compromising the purpose of the mission.

Many Small Unmanned Aerial Systems (sUAS) are incapable of meeting the safety requirements to provide a sufficient low risk of a fatality while operating above populous areas or gatherings. A recognized mitigation of this risk is a failsafe system that in the event that the sUAS is unable to maintain stable flight, terminates the flight and activates an emergency parachute. This paper proposes a methodology for assessment of Commercial Off the Shelf parachutes for sUAS failsafe systems. The methodology encompasses the evaluation criteria for the selection of parachutes based on a user-defined Maximum Takeoff Weight and the failure scenario tests for assessment of reliability and efficiency. The current standard specification on parachutes for sUAS published by the American Society of Testing and Materials has inspired the failure scenario tests. These failure scenario tests consist of a bench/destructive test and a full power cut test. The multirotor used for test of the proposed methodology is a ~ 2kg hexarotor. The results suggests the use of one specific parachute. Furthermore, the deployment time and impact energy have been estimated to be 1.2s and 21J, respectively. This impact energy suggests a probability of fatality of less than 0.01. This work is the first step towards selecting and evaluating parachute systems for sUAS. The proposed next steps are the refinement of the assessment of parachutes and increase of parachutes included in the failure scenario tests. Additionally, this will lead to the development of parachute recovery systems for sUAS with manual and autonomous triggering.

This paper presents development of model-based fail-safe modules for autonomous multirotor Unmanned Aerial Vehicles (UAVs) with safety parachute systems. The module is based on the adaptive eXogenous Kalman filter for actuator fault diagnosis. We assume all states can be measured, such that the primary goal of the filter is not the state estimation from the measurements, but the accurate reconstruction of the multirotor dynamics in real-time. Numerical simulations show the proposed diagnostic filter can be used to estimate the magnitude of the actuator faults accurately. Furthermore, based on simulated and real data recorded during a hexacopter UAV flight when its actuators experiencing complete failure, the experiment results demonstrate the effectiveness of the approach.

Unmanned Aerial Systems (UAS) operations are evolving towards autonomous flight beyond visual line of sight (BVLOS), which requires moving assessments normally conducted by the remote pilot to the autonomous software. An important assessment currently conducted by the remote pilot is whether the current weather conditions pose a safety risk to the flight. This work deals with the development of a software framework for analysing weather data. The developed framework is capable of providing a weather analysis report to a remote supervisor or to an autonomous decision-making software. The software framework has been tested using historical weather data for a full calendar year provided by IBM. The weather data was applied to four different UAS ranging from small UAS to a passenger UAS. The results obtained show that during a full year, flight was possible from 53.9 % to 95.8 % of the time depending on the UAS. We consider the software framework an important step towards improving the operational safety for autonomous UAS operations under BVLOS conditions.

The Unmanned Aerial Systems (UAS) legislation in the European Union will expectedly become unified by 2020. This legislation divides UAS operations into three categories, one of which is the Specific category, in which operations of higher risk will be placed. Permission for UAS operations in the Specific category is granted based on a Specific Operations Risk Assessment (SORA). The risk assessment categorizes operations into Specific Assurance and Integrity Levels (SAILs), which determines the level of the requirements for the operation such as operational procedures, training of the remote crew, UAS specification and maintenance etc. However, a conceptual gap exists between the defined technology requirements for UAS and the available UAS platforms. In this work, a prototype assessment tool based on the SORA defined technology requirements has been developed. The tool is a web-based questionnaire, which pulls the questions from a data structure and stores the answers in a database for analysis. Upon completion of the questionnaire, the user receives an automatically generated evaluation report. The evaluation report points out the areas of inadequacy and provides suggestions for mitigating these. The tool in its current state has been used to evaluate four commonly used UAS. The four UAS have been tested for SAIL II through IV, and the results show that only one of the selected UAS complies with SAIL II. Future work is to refine the tool including the list of questions and the UAS evaluation report generator, based on feedback from UAS domain experts and to expand it to cover fixed-wing UAS.

The current disruptive innovation in civilian drone (UAV) applications has led to an increased need for research and development in UAV technology. The key challenges currently being addressed are related to UAV platform properties such as functionality, reliability, fault tolerance, and endurance, which are all tightly linked to the UAV flight controller hardware and software. The lack of standardization of flight controller architectures and the use of proprietary closed-source flight controllers on many UAV platforms, however, complicates this work: solutions developed for one flight controller may be difficult to port to another without substantial extra development and testing. Using open-source flight controllers mitigates some of these challenges and enables other researchers to validate and build upon existing research. This paper presents a survey of the publicly available open-source drone platform elements that can be used for research and development. The survey covers open-source hardware, software, and simulation drone platforms and compares their main features.