Autonomous Ski-Companion Rescue Drone for Backcountry Incapacitation Incidents: A Scientific Research Proposal

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Authors: Amirhossein GORDBAGLI
Cited by: 0

Abstract

Backcountry and extreme off-piste skiing exposes participants to time-critical emergencies, particularly avalanche burial, traumatic injury, disorientation, and incapacity. While avalanche transceivers, airbags, and satellite messengers reduce risk, they may fail to trigger timely rescue when the victim is incapacitated, unconscious, or unable to initiate an SOS (distress signal). This proposal investigates a Ski-Companion Rescue Drone: a lightweight UAV (Unmanned Aerial Vehicle) that follows a skier in uncharted terrain, detects anomalous events (e.g., sudden impact, abrupt immobilization, loss of motion consistent with burial or incapacitation), and autonomously performs three actions: (i) localize the last known victim position; (ii) mark the site by deploying a high-visibility flag/marker and activating a beacon; and (iii) transmit an SOS (distress signal) via an integrated communication chain (direct cellular where available, or via a direct or paired satellite messenger carried by the skier).The research focuses on (a) feasibility and failure modes in harsh winter environments, (b) reliable anomaly detection with low false-alarm rates, (c) localization accuracy and marker deployment precision, and (d) regulatory and economic viability. The work will benchmark against existing off-the-shelf solutions (avalanche transceivers, RECCO reflectors, satellite messengers) and drone follow-me capabilities. The expected outcome is an experimentally validated prototype concept with quantified performance, safety constraints, and a commercialization pathway (if justified).

Fields of Study & Subjects

Winter Sports Injuries and Performance UAV Applications and Optimization Aerospace and Aviation Technology

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
29 January 2026
Language
EN
Document type
Preprint