LifeLine Sentinel

LIFELINE SENTINEL - AI SAFETY AND PERFORMANCE COACH FOR EXTREME SPORTS ATHLETES

Executive summary

LifeLine Sentinel is an AI-driven extreme sports athlete safety and performance system that fuses wearable vitals, smartphone/edge analytics, Galileo/EGNOS GNSS positioning, and satellite fallback messaging. It provides early warnings for heat stress, dehydration, overexertion, and falls, off-grid and in real time, while giving crews and race organizers a live map with risk scores and recommended actions. Galileo/EGNOS deliver precise, integrity-enhanced positioning; Copernicus datasets (DEM, atmosphere/temperature) enrich environmental context for risk estimation.

Problem (beta)

Ultramarathons (50-300+ km) increasingly traverse remote terrain with poor cellular coverage, high heat exposure, altitude gain, and sleep deprivation. Crews and organizers lack continuous vitals and position telemetry, delaying interventions; extreme sports athletes often miss subtle physiological warning signs until it’s too late. Existing wearables rarely provide personalized risk assessments or function reliably beyond cellular networks.

Target users and value

• Extreme sports athletes: real-time, personalized coaching (cooling, hydration, pacing) and automatic fall/SOS detection.

• Crews: live Risk Score (0-100), location, last alert, and specific recommended actions.

• Organizers/medics: course-wide situational awareness, faster triage, incident heat map, audit trail.

• Insurers/venues: documented risk mitigation and improved event safety posture.

Objectives and success metrics

• Safety: detect risky states (heat stress/overexertion/fall) with <45 s time-to-alert in demo conditions.

• Reliability: operate with satellite fallback when cell is unavailable; 60-120 s burst cadence.

• Accuracy: GNSS track error ~1-2 m in open terrain with dual-frequency receivers where available; integrity flags for crews (EGNOS region).

• Usability: one-tap start; clear green/amber/red states; actionable, short recommendations.

• Privacy-by-design: on-device processing by default; minimal data sent (risk + last fix).

System overview

Extreme sports athlete kit (BLE sensors + smartphone) computes a real-time Risk Score from HR/HRV, skin temp, SpO₂, motion, and terrain/ambient context. A GNSS module prioritizes Galileo signals and leverages EGNOS integrity in Europe. Primary backhaul is cellular; when unavailable, a satellite short-burst payload (compressed JSON) is sent at a set cadence. A crew/organizer dashboard displays live tracks, risk states, and guidance; alerts trigger notifications.

Space components

• Galileo + EGNOS: high-quality positioning plus integrity message for reliability in Europe.

• Copernicus data: DEM (COP-DEM GLO-30) for grade/elevation context; atmosphere/temperature products for environmental overlays during planning and post-race analysis.

• Satellite IoT (e.g., Iridium SBD) for off-grid alerting when cellular is unavailable.

Components and architecture

Mobile (Extreme Sports Athlete) app

• Inputs: BLE chest HR/HRV, skin/ambient temp, SpO₂; phone IMU and barometer; GNSS raw or Fused Location.

• Edge AI: computes per-athlete baseline, detects anomalies, and fuses risks into a single Risk Score.

• GNSS: uses dual-frequency (E1/E5) when the handset supports it; on Android 10+ raw GNSS is widely available for advanced processing.

• Comms: HTTPS/WebSocket (cellular). Satellite mode sends compressed bursts (60-120 s) with last fix, risk, and reason codes.

• UX: large color states (Green/Amber/Red), hydration/cooling tips, manual SOS, and 'satellite mode' toggle.

Backend (lightweight)

• Ingest API: receives updates; authenticates extreme sports athletes; stores rolling 60-120 min window.

• Processing: validates EGNOS integrity flag where available; enriches with DEM/elevation and route GPX.

• Events: pushes alerts to crews/organizers via WebSocket; maintains a minimal audit log.

Crew/Organizer dashboard (Web)

• Map: live extreme sports athlete positions with accuracy/age badges, elevation profile, recent risk timeline.

• Alerts: prioritized queue (extreme sports athlete, level, reason, recommended action).

• Overlays: course profile (DEM), heat/temperature layer for context (preloaded tiles for demo).

• Admin: team management; opt-in data sharing; export incident report.

Data and models

Signals and features (30 s windows)

• Cardio: HR, HRV (rMSSD), HR drift vs pace/grade.

• Thermal: skin temp and trend; optionally ambient T.

• Motion: cadence variance, vertical oscillation, fall G-spike; no-movement detector.

• Terrain: grade from DEM; elevation gain rate; altitude.

Risk classes and fusion

• Heat stress: rising skin temp + HRV drop + HR/effort decoupling, modulated by ambient temperature layer (if available).

• Overexertion: sustained HR above baseline zone with HRV suppression and high gain rate.

• Fall/SOS: IMU spike, speed collapse, no-movement ≥30 s; manual SOS override.

• Fusion: logistic scores per class → weighted sum → Risk Score (0-100) with hysteresis for stability.

Personalization

• Baseline adapter: rolling median and variance per extreme sports athlete/session; acclimatization factor over time.

• Calibration: 15-60 s warm-up to establish initial baselines; optional profile import from past runs.

Positioning and integrity (space)

• Galileo + EGNOS: We prioritize Galileo signals and apply EGNOS in Europe for higher accuracy and an integrity message (confidence on residual errors), which is crucial when triggering medical alerts.

• Dual-frequency readiness: modern Android devices support raw GNSS measurements, enabling improved accuracy and signal quality checks when available.

• High-accuracy path: future upgrade can ingest Galileo HAS PPP corrections for decimeter-level positioning where suitable hardware/software are available.

Environmental context (space)

• Terrain context: Copernicus DEM (GLO-30) gives grade/elevation for effort-normalized pacing and risk estimates (e.g., climbs with heat).

• Atmosphere/temperature: CAMS/C3S products provide authoritative data for heat-risk analysis and planning (e.g., pre-race heat maps, post-race analytics).

Satellite fallback (space)

When cellular is absent, the app enters satellite burst mode: compact, binary-encoded JSON (extreme sports athlete ID, timestamp, last GNSS fix, risk level, reason, and optional SOS) is sent via SBD-class services; crews receive periodic updates with low battery and bandwidth overhead.

Security, privacy, and ethics

• On-device by default: risk inference local to phone; cloud stores only short-term streams.

• Minimal data: position + risk + last 60-120 min unless extreme sports athletes opts in for analytics.

• Consent and control: per-athlete consent; explicit sharing with crew/organizers; manual SOS.

• Compliance: not a medical device; presents advisory guidance, not diagnosis.

• Safety UX: conservative thresholds + hysteresis to limit false positives; clear human-override.

Implementation plan

Hackathon MVP (what we will demo)

• Extreme sports athlete app: BLE simulator for HR/HRV/temp/SpO₂; GNSS track; Risk Score banner; satellite mode toggle.

• Dashboard: live map, per-athlete Risk Score timeline, alert panel, and action tips.

• Scenarios: (A) heat stress ramp → Amber→Red alert; (B) fall + no-movement → SOS and last fix.

• KPIs demoed: time-to-alert, alert stability, connectivity failover.

Post-hackathon milestones (90 days)

1. Field pilots with two trail clubs; collect de-identified telemetry for model tuning.

2. Hardware integrations (popular chest straps; optional temp patch).

3. EGNOS integrity display and handset validation; investigate HAS/PPP path.

4. Partner data (race routes, aid-station locations) for situational overlays.

5. Risk model v2 with semi-supervised personalization and WBGT proxy input.

Validation and testing

• Bench tests: simulator sweeps for HR/HRV/temp, terrain and cadence; ROC/PR metrics per class.

• Outdoor dry-runs: controlled heat/effort protocols; compare alerts vs. predefined triggers.

• Positioning: log GNSS quality; compare EGNOS-region integrity flags and track error on open trails.

• Usability: crews perform timed response drills based on alerts and recommendations.

Risks and mitigations

• Sensor variability: support multiple BLE devices; smooth via robust baselines; confidence flags.

• GNSS multipath/forest canyons: dual-frequency support; trail map-matching; integrity indicators.

• Connectivity costs: satellite used only in exception mode with compressed bursts.

• False alarms: multi-signal fusion + hysteresis; require persistence >N seconds; human acknowledge.

• Regulatory perceptions: clear non-medical labeling; conservative guidance; expert medical review panel.

Business and partnerships

• Model: B2B2C with organizers (per-athlete event fee) + crew/team packs; optional device rental.

• Partners: race organizers, insurer risk teams, satellite service providers, GNSS handset OEMs, sports medicine advisors.

• Moats: safety-grade UX, off-grid reliability, privacy-first design, and space-augmented context (EGNOS integrity + Copernicus overlays).

Roadmap highlights

• Coach Mode (training): adaptive sessions using terrain/heat context.

• Group Safety: expedition/team view with geofenced alerts.

• High-accuracy positioning: selective Galileo HAS adoption with compatible receivers for critical events.