Background: This preliminary report describes our experience using unmanned aerial vehicles (UAVs) to identify swimmers in distress at the 2018 Mont-Tremblant IRONMAN triathlon (Quebec, Canada). Methods: In a prospective pilot study, we sought to determine whether UAV surveillance could identify swimmers showing signs of distress quicker than conventional methods (i.e., lifeguards on the ground and on watercraft). In addition, we investigated the feasibility of using UAVs for medical surveillance at a triathlon event in terms of operations, costs, safety, legal parameters, and added value. Prior to the race, we screened participants for medical conditions that could elevate their risk of injury during the swim portion of the triathlon. Athletes deemed to be at increased risk were given a yellow swimming cap to enhance their surveillance by trained observers watching a live video feed from the UAVs. Results: On race day, a total of 3 UAVs (2 mobile, 1 tethered) were launched over Lake Tremblant and provided 3 observers with live video of the swimmers. Of the 2,473 race participants, there were 25 athletes with pre-identified medical conditions who wore a yellow cap during the swim. We did not detect any signs of distress among swimmers wearing yellow caps. Among the remaining 2,448 athletes, there were 5 swimmers who demonstrated signs of distress and required mobilization of water rescue boats; UAV surveillance identified 1 of these 5 distress events before it was seen by lifeguards on rescue boats. None of the athletes in the IRONMAN suffered an adverse event while swimming. Several technical and safety issues related to UAV surveillance arose including poor visibility, equipment loss, and flight autonomy. Conclusion: While our preliminary findings suggest that using UAVs to identify distressed swimmers during an IRONMAN race is feasible and safe, more research is necessary to determine how to optimize UAV surveillance at mass sporting events and integrate this technology within the existing emergency response teams.
Keywords: emergency medical services; surveillance; triathlon; unmanned aerial vehicles.