Why it matters
Without AI planning, searches risk longer recoveries, increased risk to birds on the ground, disorganized search efforts, and potential licence or insurance challenges due to poor recoveries.
From design to safety
Design
AI informs search area design
Develops data models for telemetry bearings, last sighting routes, terrain, and wind fields to shape initial search plans before build, ensuring scalable contingency coverage for all grounds.
- telemetry bearings
- terrain mapping grid
- wind drift sensors
Build
Hardware and data pipelines installed
Install sensors, set up roost site mapping, deploy roving teams, integrate last sighting logs, and establish secure data feeds for real-time planning, aligning with site licensing expectations.
- telemetry bearings
- roost site map
- search teams roster
Operation
Real-time search planning deployed
AI ingests live telemetry, last sighting updates, wind shifts, and terrain changes to generate current search grids and team assignments, including fallback routes for lost signals.
- telemetry bearings
- terrain mapping grid
- wind drift sensors
- roost site map
Maintenance
Data quality and updates maintained
Regularly calibrate sensors, update roost and last sighting records, verify terrain models, and refresh roaster of search teams, with periodic validation against drill exercises.
- roost site map
- search teams roster
- terrain mapping grid
Safety
Safety checks and compliance enforced
AI flags potential hazards, ensures proper handling of birds during retrieval, and verifies licensing and regulatory requirements are met for search operations, documenting approval trails.
- last sighting log
- wind drift sensors
- search teams roster
Part by part
- 1
Telemetry bearings
- Watch for
- Bearing drift during rapid flight, partial signal loss, mounting wear causing misalignment, or sensor bias that distorts direction.
- AI action
- Read bearing vectors; trigger grid recalculation when drift exceeds threshold; log anomaly and notify supervisor.
- 2
Last sighting log
- Watch for
- Unrecorded last sighting events, inconsistent timestamps, or duplicate entries that blur search start.
- AI action
- Flag missing data; prompt field staff to confirm exact time and position; timestamp all edits for audit.
- 3
Terrain mapping grid
- Watch for
- Terrain data gaps or outdated elevation models affecting plan quality or hazard avoidance.
- AI action
- Generate updated search grid with current terrain layers; alert for terrain shifts after weather events.
- 4
Wind drift sensors
- Watch for
- Wind field readings drift out of date during weather changes or sensor drift.
- AI action
- Update wind map; adjust search vectors for drift compensation; trigger re-tasking if drift exceeds threshold.
- 5
Roost site map
- Watch for
- Roost locations drifting due to weather, new perches, or bird movement patterns.
- AI action
- Reconcile roost map with field observations; suggest new roost fixes or temporary roost closures.
- 6
Search teams roster
- Watch for
- Roster gaps or unassigned teams during busy periods or during medical leave.
- AI action
- Reallocate teams; assign surge capacity alerts for missing personnel; confirm on-call replacements.
Worked example
Lost Peregrine Search Coordination
Illustrative scenario with sample data.
A peregrine falcon disappears during a flying display; rapid reorientation of search teams is required.
Signal in
birdTag: P7-410; lastSeen: 14:32; coordinates: 36.12N, -1.45W; wind: 12km/h W; terrain: mixed scrub and low ridge; roosts: near north gate; telemetry: active.
System out
New search grid generated; team assignments updated; wind-adjusted routes issued; alert sent to avian vet for potential hazards.
Human sign-off: Head falconer reviews AI suggested grid, approves search plan, confirms team assignments, and instructs display supervisor to pause routine flights if needed.
How to roll it out
Phase 1
Weeks 1 to 2
Baseline data capture and sensor checks; establish initial search model and team rosters.
Phase 2
Weeks 3 to 6
Iterate on wind, terrain, and last sighting inputs; refine grid generation rules to increase coverage.
Phase 3
Weeks 7 to 8
Transition to full operation with regular drills, after-action reviews, and licensing officer sign-offs.
Where people stay in charge
- All decisions affecting live birds must be signed off by the head falconer or accredited avian vet to ensure welfare and health compliance.
- Data changes impacting safety or licence compliance must be reviewed by a centre manager and, if required, licensing officer, with audit trails.
- Resolution of conflicts between AI recommendations and regulatory constraints must be escalated to the senior management for final approval and record keeping.
Questions owners and crews ask
How does AI determine the best search grid for a lost bird in a flying arena?
The system ingests telemetry bearings, last sighting, terrain, wind drift, and roost data to compute an optimal grid, then assigns teams to sectors based on proximity and skill, with a log of all adjustments.
Who approves changes to search plans during a recovery operation?
The head falconer reviews AI recommendations and signs off alongside the centre avian vet when health or safety issues arise, and licensing officer when regulatory constraints apply.
What records are kept to support future searches and licensing?
Logs include last sighting times and coordinates, bearing histories, wind maps, terrain models, roost changes, and team rosters for audit trails and licensing review.
How is safety ensured during AI-guided searches?
AI proposes risks, but all actions require qualified sign-off by the head falconer and adherence to zoo licence and licensing officer guidelines, with field supervisors maintaining oversight.