Sharkeye: Real-Time Autonomous Personal Shark Alerting via Aerial Surveillance

Risks of Drone Use in Light of Literature Studies

This article aims to present the results of a bibliometric analysis of relevant literature and discuss the main research streams related to the topic of risks in drone applications. The methodology of the conducted research consisted of five procedural steps, including the planning of the research, conducting a systematic review of the literature, proposing a classification framework corresponding to contemporary research trends related to the risk of drone applications, and compiling the characteristics of the publications assigned to each of the highlighted thematic groups. This systematic literature review used the PRISMA method. A total of 257 documents comprising articles and conference proceedings were analysed. On this basis, eight thematic categories related to the use of drones and the risks associated with their operation were distinguished. Due to the high content within two of these categories, a further division into subcategories was proposed to illustrate the research topics better. The conducted investigation made it possible to identify the current research trends related to the risk of drone use and pointed out the existing research gaps, both in the area of risk assessment methodology and in its application areas. The results obtained from the analysis can provide interesting material for both industry and academia.

Utility of Spectral Filtering to Improve the Reliability of Marine Fauna Detections from Drone-Based Monitoring

Monitoring marine fauna is essential for mitigating the effects of disturbances in the marine environment, as well as reducing the risk of negative interactions between humans and marine life. Drone-based aerial surveys have become popular for detecting and estimating the abundance of large marine fauna. However, sightability errors, which affect detection reliability, are still apparent. This study tested the utility of spectral filtering for improving the reliability of marine fauna detections from drone-based monitoring. A series of drone-based survey flights were conducted using three identical RGB (red-green-blue channel) cameras with treatments: (i) control (RGB), (ii) spectrally filtered with a narrow 'green' bandpass filter (transmission between 525 and 550 nm), and, (iii) spectrally filtered with a polarising filter. Video data from nine flights comprising dolphin groups were analysed using a machine learning approach, whereby ground-truth detections were manually created and compared to AI-generated detections. The results showed that spectral filtering decreased the reliability of detecting submerged fauna compared to standard unfiltered RGB cameras. Although the majority of visible contrast between a submerged marine animal and surrounding seawater (in our study, sites along coastal beaches in eastern Australia) is known to occur between 515-554 nm, isolating the colour input to an RGB sensor does not improve detection reliability due to a decrease in the signal to noise ratio, which affects the reliability of detections.

Counting animals in aerial images with a density map estimation model

Animal abundance estimation is increasingly based on drone or aerial survey photography. Manual postprocessing has been used extensively; however, volumes of such data are increasing, necessitating some level of automation, either for complete counting, or as a labour-saving tool. Any automated processing can be challenging when using such tools on species that nest in close formation such as Pygoscelis penguins. We present here a customized CNN-based density map estimation method for counting of penguins from low-resolution aerial photography. Our model, an indirect regression algorithm, performed significantly better in terms of counting accuracy than standard detection algorithm (Faster-RCNN) when counting small objects from low-resolution images and gave an error rate of only 0.8 percent. Density map estimation methods as demonstrated here can vastly improve our ability to count animals in tight aggregations and demonstrably improve monitoring efforts from aerial imagery.

Factors Affecting Shark Detection from Drone Patrols in Southeast Queensland, Eastern Australia

Drones enable the monitoring for sharks in real-time, enhancing the safety of ocean users with minimal impact on marine life. Yet, the effectiveness of drones for detecting sharks (especially potentially dangerous sharks; i.e., white shark, tiger shark, bull shark) has not yet been tested at Queensland beaches. To determine effectiveness, it is necessary to understand how environmental and operational factors affect the ability of drones to detect sharks. To assess this, we utilised data from the Queensland SharkSmart drone trial, which operated at five southeast Queensland beaches for 12 months in 2020−2021. The trial conducted 3369 flights, covering 1348 km and sighting 174 sharks (48 of which were >2 m in length). Of these, eight bull sharks and one white shark were detected, leading to four beach evacuations. The shark sighting rate was 3% when averaged across all beaches, with North Stradbroke Island (NSI) having the highest sighting rate (17.9%) and Coolum North the lowest (0%). Drone pilots were able to differentiate between key shark species, including white, bull and whaler sharks, and estimate total length of the sharks. Statistical analysis indicated that location, the sighting of other fauna, season and flight number (proxy for time of day) influenced the probability of sighting sharks.

The Relative Abundance and Occurrence of Sharks off Ocean Beaches of New South Wales, Australia

There is still limited information about the diversity, distribution, and abundance of sharks in and around the surf zones of ocean beaches. We used long-term and large-scale drone surveying techniques to test hypotheses about the relative abundance and occurrence of sharks off ocean beaches of New South Wales, Australia. We quantified sharks in 36,384 drone flights across 42 ocean beaches from 2017 to 2021. Overall, there were 347 chondrichthyans recorded, comprising 281 (81.0%) sharks, with observations occurring in <1% of flights. Whaler sharks (Carcharhinus spp.) had the highest number of observations (n = 158) recorded. There were 34 individuals observed for both white sharks (Carcharodon carcharias) and critically endangered greynurse sharks (Carcharias taurus). Bull sharks (Carcharhinus leucas), leopard sharks (Stegostoma tigrinum) and hammerhead species (Sphyrna spp.) recorded 29, eight and three individuals, respectively. Generalised additive models were used to identify environmental drivers for detection probability of white, bull, greynurse, and whaler sharks. Distances to the nearest estuary, headland, and island, as well as water temperature and wave height, were significant predictors of shark occurrence; however, this varied among species. Overall, we provide valuable information for evidence-based species-specific conservation and management strategies for coastal sharks.

An automated work-flow for pinniped surveys: A new tool for monitoring population dynamics

Detecting changes in population trends depends on the accuracy of estimated mean population growth rates and thus the quality of input data. However, monitoring wildlife populations poses economic and logistic challenges especially in complex and remote habitats. Declines in wildlife populations can remain undetected for years unless effective monitoring techniques are developed, guiding appropriate management actions. We developed an automated survey workflow using unmanned aerial vehicles (drones) to quantify the number and size of individual animals, using the well-studied Scandinavian harbour seal (Phoca vitulina) as a model species. We compared ground-based counts using telescopes with manual flights, using a zoom photo/video, and pre-programmed flights producing orthomosaic photo maps. We used machine learning to identify and count both pups and older seals and we present a new method for measuring body size automatically. We evaluate the population’s reproductive success using drone data, historical counts and predictions from a Leslie matrix population model. The most accurate and time-efficient results were achieved by performing pre-programmed flights where individual seals are identified by machine learning and their body sizes are measured automatically. The accuracy of the machine learning detector was 95–97% and the classification error was 4.6 ± 2.9 for pups and 3.1 ± 2.1 for older seals during good light conditions. There was a clear distinction between the body sizes of pups and older seals during breeding time. We estimated 320 pups in the breeding season 2021 with the drone, which is well beyond the expected number, based on historical data on pup production. The new high quality data from the drone survey confirms earlier indications of a deteriorating reproductive rate in this important harbour seal colony. We show that aerial drones and machine learning are powerful tools for monitoring wildlife in inaccessible areas which can be used to assess annual recruitment and seasonal variations in body condition.

A “Wicked Problem” Reconciling Human-Shark Conflict, Shark Bite Mitigation, and Threatened Species

Conservation measures often result in a “wicked problem,” i.e., a complex problem with conflicting aims and no clear or straightforward resolution without severe adverse effects on one or more parties. Here we discuss a novel approach to an ongoing problem, in which actions to reduce risk to humans, involve lethal control of otherwise protected species. To protect water users, nets are often used to catch potentially dangerous sharks at popular bathing beaches, yet in Australian waters one of the targeted species, the white shark (Carcharodon carcharias) is listed as Vulnerable, while bycatch includes the Critically Endangered grey nurse shark (Carcharias taurus). Recent, highly publicised, shark attacks have triggered demands for improved bather protection, whilst welfare and conservation organisations have called for removal of lethal measures. This leaves management and policy makers with a wicked problem: removing nets to reduce impacts on threatened species may increase risk to humans; or leaving the program as it is on the premise that the benefits provided by bather protection are greater than the impact on threatened and protected species. We used multivariate analysis and generalised additive models to investigate the biological, spatial-temporal, and environmental patterns influencing catch rates of threatened and of potentially dangerous shark species in the New South Wales shark nets over two decades to April 2019. Factors influencing catches were used to develop a matrix of potential changes to reduce catch of threatened species. Our proposed solutions include replacing existing nets with alternative mitigation strategies at key beaches where catch rate of threatened species is high. This approach provides stakeholders with a hierarchy of scenarios that address both social demands and threatened species conservation and is broadly applicable to human-wildlife conflict scenarios elsewhere.

On the Dominant Factors of Civilian-Use Drones: A Thorough Study and Analysis of Cross-Group Opinions Using a Triple Helix Model (THM) with the Analytic Hierarchy Process (AHP)

This study explores the experts’ opinions during the consultation stage before law-making for civilian drones. A thorough literature study is first undertaken to have the set of influencing factors that should be suitable for the investigation from the perspective of designing and selecting civilian drones. Several rounds of surveys using the Delphi method, followed by an analytic hierarchy process (AHP), are performed to conform to the organized tree structure of constructs and factors and to obtain the knowledge about the opinions of the expert groups, with the expert sample being intentionally partitioned into three opinion groups at the beginning: academia (A), industry (I), and research institutes (R). Doing so facilitates a “mind-mining” process using the triple helix model (THM), while the opinions across the groups can also be visualized and compared. This exploits a new set of knowledge for the design and selection of civilian drones on a scientific yet empirical basis, and the observed differences and similarities among the groups may benefit their future negotiations to propose the drafts for regulating the design, manufacturing, and uses of civilian drones. As several significant implications and insights are also drawn and gained from the abovementioned results eventually, some possible research directions are worthwhile. The proposed hybrid methodological flow is another novelty.

Going Batty: The Challenges and Opportunities of Using Drones to Monitor the Behaviour and Habitat Use of Rays

The way an animal behaves in its habitat provides insight into its ecological role. As such, collecting robust, accurate datasets in a time-efficient manner is an ever-present pressure for the field of behavioural ecology. Faced with the shortcomings and physical limitations of traditional ground-based data collection techniques, particularly in marine studies, drones offer a low-cost and efficient approach for collecting data in a range of coastal environments. Despite drones being widely used to monitor a range of marine animals, they currently remain underutilised in ray research. The innovative application of drones in environmental and ecological studies has presented novel opportunities in animal observation and habitat assessment, although this emerging field faces substantial challenges. As we consider the possibility to monitor rays using drones, we face challenges related to local aviation regulations, the weather and environment, as well as sensor and platform limitations. Promising solutions continue to be developed, however, growing the potential for drone-based monitoring of behaviour and habitat use of rays. While the barriers to enter this field may appear daunting for researchers with little experience with drones, the technology is becoming increasingly accessible, helping ray researchers obtain a wide range of highly useful data.

The Drone Revolution of Shark Science: A Review

Over the past decade, drones have become a popular tool for wildlife management and research. Drones have shown significant value for animals that were often difficult or dangerous to study using traditional survey methods. In the past five years drone technology has become commonplace for shark research with their use above, and more recently, below the water helping to minimise knowledge gaps about these cryptic species. Drones have enhanced our understanding of shark behaviour and are critically important tools, not only due to the importance and conservation of the animals in the ecosystem, but to also help minimise dangerous encounters with humans. To provide some guidance for their future use in relation to sharks, this review provides an overview of how drones are currently used with critical context for shark monitoring. We show how drones have been used to fill knowledge gaps around fundamental shark behaviours or movements, social interactions, and predation across multiple species and scenarios. We further detail the advancement in technology across sensors, automation, and artificial intelligence that are improving our abilities in data collection and analysis and opening opportunities for shark-related beach safety. An investigation of the shark-based research potential for underwater drones (ROV/AUV) is also provided. Finally, this review provides baseline observations that have been pioneered for shark research and recommendations for how drones might be used to enhance our knowledge in the future.

Elasmobranch Use of Nearshore Estuarine Habitats Responds to Fine-Scale, Intra-Seasonal Environmental Variation: Observing Coastal Shark Density in a Temperate Estuary Utilizing Unoccupied Aircraft Systems (UAS)

Many coastal shark species are known to use estuaries of the coastal southeastern United States for essential purposes like foraging, reproducing, and protection from predation. Temperate estuarine landscapes, such as the Rachel Carson Reserve (RCR) in Beaufort, NC, are dynamic habitat mosaics that experience fluctuations in physical and chemical oceanographic properties on various temporal and spatial scales. These patterns in abiotic conditions play an important role in determining species movement. The goal of this study was to understand the impact of environmental conditions around the RCR on shark density within the high-abundance summer season. Unoccupied Aircraft System (UAS) surveys of coastal habitats within the reserve were used to quantify shark density across varying environmental conditions. A combination of correlation analyses and Generalized Linear Modelling (GLM) revealed that density differs substantially across study sites and increases with rising water temperatures, conclusions that are supported by previous work in similar habitats. Additionally, density appears to increase moving towards dawn and dusk, potentially supporting crepuscular activity in coastal estuarine areas. By describing shark density dynamics in the RCR, this study provides new information on this population and presents a novel framework for studying elasmobranchs in temperate estuaries.

Coexisting with sharks: a novel, socially acceptable and non-lethal shark mitigation approach

Conflict between humans and large predators is a longstanding challenge that can present negative consequences for humans and wildlife. Sharks have a global distribution and are considered to pose a potential threat to humans; concurrently many shark species are themselves threatened. Developing strategies for coexistence between humans and this keystone group is imperative. We assess blimp surveillance as a technique to simply and effectively reduce shark encounters at ocean beaches and determine the social acceptance of this technique as compared to an established mitigation strategy—shark meshing. We demonstrate the suitability of blimps for risk mitigation, with detection probabilities of shark analogues by professional lifeguards of 0.93 in ideal swimming conditions. Social surveys indicate strong social acceptance of blimps and preference for non-lethal shark mitigation. We show that continuous aerial surveillance can provide a measurable reduction in risk from sharks, improving beach safety and facilitating coexistence between people and wildlife.

Determining Stingray Movement Patterns in a Wave-Swept Coastal Zone Using a Blimp for Continuous Aerial Video Surveillance

Stingrays play a key role in the regulation of nearshore ecosystems. However, their movement ecology in high-energy surf areas remains largely unknown due to the notorious difficulties in conducting research in these environments. Using a blimp as an aerial platform for video surveillance, we overcame some of the limitations of other tracking methods, such as the use of tags and drones. This novel technology offered near-continuous coverage to characterise the fine-scale movements of stingrays in a surf area in Kiama, Australia, without any invasive procedures. A total of 98 stingray tracks were recorded, providing 6 h 27 min of movement paths. The tracking data suggest that stingrays may use a depth gradient located in the sandflat area of the bay for orientating their movements and transiting between locations within their home range. Our research also indicates that stingray behaviour was influenced by diel periods and tidal states. We observed a higher stingray occurrence during the afternoon, potentially related to foraging and anti-predatory strategies. We also saw a reduced route fidelity during low tide, when the bathymetric reference was less accessible due to stranding risk. Considering the increasing threat of anthropogenic development to nearshore coastal environments, the identification of these patterns can better inform the management and mitigation of threats.