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 recent 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. Drones have been used to fill knowledge gaps around fundamental shark behaviours or movements, social interactions, and predation across multiple species and scenarios. The advancement in technology across sensors, automation, and artificial intelligence are improving our abilities in data collection and analysis and opening opportunities for shark-related beach safety.

For more information, see our review Butcher et al. 2021 The drone revolution of shark science.

Schematic illustrating the interrelated factors that researchers should consider when planning and performing shark research with drones. (Top) factors that influence the type of drone and payload required for a research activity, (Left) factors that influence pre-flight planning for a research monitoring activity, (Right) factors on the day that heavily influence successful flight and data collection during a research activity. (Inset) image of underwater ROV/UAV and (Bottom) additional factors for underwater drones.

Drones have been used to infer the density of sharks and rays in shallow waters such as the tropical lagoons of Moorea, French Polynesia (Kiszka et al. 2016). Here the drone identify a blacktip reef shark (Carcharhinus melanopterus) in the middle of the coral.

Representation of the types of imagery collected by drone: (a,b) tracking white sharks (Carcharodon carcharias) along coastal beaches of eastern Australia as part of behavioural and bather protection programs (Image credit—A Colefax), (c) great hammerhead (Sphyrna mokarran) predation event on blacktip sharks (Carcharhinus limbatus) (Image credit—S Kajiura), (d) tiger shark at a humpback whale (Megaptera novaeangliae) carcass off eastern Australia (Image credit—M Dujmovic), (e) hammerhead sharks (Sphyrna sp.) observed during the austral summer in Western Australia (Image credit—N.A. López), and (f) Epaulette shark (Hermiscyllium ocellatum, ~50 cm TL) captured feeding in sediments at low tide on Heron Reef flat, Great Barrier Reef, Australia from an altitude of 5 m (Image credit—V. Raoult).

Drone footage can be analysed to quantify swimming alignment, nearest-neighbour distances, velocity and tail beat frequency (Image—modified by J Mourier from Rieucau et al., 2018).

Evolution of artificial intelligence (AI) for shark identification: (a) automated evaluation of dorsal fins from video collected , (b) real time evaluation of shark analogues at beach (with reporting to in-water users) demonstrated in Kiama, Australia through blimp and drone-based camera, (c) automated marine animal detection based on images collected over Australian beaches post-collection, (d) UTS system was reportedly deployed on Little Ripper Drones in NSW beaches in Australia with Surf Life Saving as of 2019, (e) Sharkeye system reported by San Diego State University and Sales Force—where videos collected from drones flown over Southern California could be analyzed and reported to lifeguards (2019), and (f) in development AI on portable devices that can identify to species level in real time by Macquarie University and NSW Department of Primary Industries research teams.