Why it matters
Without AI, misreads of contact zone faults or unsafe entries can lead to repeated errors, frustrated athletes, refunds, and insurance concerns due to inconsistent method application and delayed safety interventions.
From design to safety
Design
Design AI data inputs and criteria
Define data requirements, sensor placements, and performance criteria to grade contact zones and obstacle fluency for future training plans. Specify camera angles, lighting tolerances, resolution targets, and frame timestamps for precise scoring. Establish a metadata schema for sessions, dogs, and course IDs to support traceability and audits.
- A-frame contact zone pad
- Dog walk contact plank
- Video frames recorder
- Criteria standard sheets
Build
Install sensing and video capture
Deploy durable sensors, camera quality targets, calibration routines, and integration with the criteria system to ensure reliable data streams. Install weatherproof housings, surge protection, power redundancy, and network isolation for data integrity during field sessions.
- A-frame contact zone pad
- Dog walk contact plank
- Video frames recorder
- A-frame platform components
Operation
Run live and batch analysis
Continuously read video frames, compute contact accuracy scores, flag inconsistencies, and generate coaching prompts and progress notes. Produce per-dog summaries, session-level flags, and a weekly trend dashboard for staff reviews.
- Video frames recorder
- Contact zone sensors
- Criteria standard sheets
- A-frame platform components
Maintenance
Validate and recalibrate sensors
Schedule routine checks for sensor drift, camera alignment, frame rate integrity, and data integrity of contact zone scoring. Implement a quarterly calibration report and issue-tracking linked to maintenance tickets.
- Video frames recorder
- Contact zone sensors
- A-frame contact zone pad
Safety
Audit safety thresholds and coaching scope
Review AI decisions with qualified trainers to ensure welfare-first methods, proper desensitisation, and adherence to Canine Good Citizen and CPD standards. Log safety reviews in the welfare file and ensure inclement weather adaptations are documented.
- Criteria standard sheets
- Video frames recorder
- Contact zone sensors
Part by part
- 1
A-frame contact zone pad
- Watch for
- Wear at the contact surface causing uneven pressure readings or gaps during peak repetitions.
- AI action
- Trigger alert for pad recalibration and surface inspection by lead trainer.
- 2
Dog walk contact plank
- Watch for
- Inconsistent contact with the center line or missing contact zone during rushed sequences.
- AI action
- Flag frames and request review by performance coach to adjust cue timing.
- 3
Seesaw contact surface
- Watch for
- Delayed contact reporting or uneven contact edge readings across cycles.
- AI action
- Generate trainer report with recommended pacing and desensitisation steps.
- 4
Video frames recorder
- Watch for
- Frame loss or low resolution affecting analysis accuracy.
- AI action
- Pause data intake and run integrity check; notify technician.
- 5
Criteria standard sheets
- Watch for
- Mismatch between observed performance and defined criteria thresholds.
- AI action
- Annotate deviations and generate updated training plan for coaching group.
- 6
Contact zone sensors
- Watch for
- Sensor drift or misalignment causing false positives in contact detection.
- AI action
- Trigger calibration workflow and archival of calibration results.
Worked example
Performance Monitoring for an Intro Level Agility Course
Illustrative scenario with sample data.
A four-dog class evaluates A-frame, dog walk, and seesaw to determine consistency and safety.
Signal in
dog_id: 42, course_id: C1, frameRate: 30fps, A-frame: centerContact: true, walkContact: true, seesawContact: false, videoQuality: 1080p
System out
alert: seesaw contact inconsistency; action: trainer to review seesaw angle, adjust cue timing, and re-test in 2 sessions.
Human sign-off: Head trainer reviews AI alert, confirms intervention plan, and signs off on updated coaching notes.
How to roll it out
Phase 1
Weeks 1 to 4
Baseline data capture and initial criteria setup across A-frame, dog walk, and seesaw.
Phase 2
Weeks 5 to 8
Calibration, threshold tuning, and integration with coaching workflows for live classes.
Phase 3
Weeks 9 to 12
Full production monitoring with maintenance checks and welfare-focused safety sign-offs.
Where people stay in charge
- All decisions about training adjustments based on AI must be approved by a certified agility coach or lead trainer.
- The welfare-first protocol requires human sign-off before medical or pharmacological considerations are made.
- Any medical or behavioural concerns flagged by AI require veterinary or veterinary behaviourist sign-off before coaching changes.
Questions owners and crews ask
What data feeds does the AI require for contact zone analysis?
The AI requires high-resolution video frames, frame rate metadata, sensor status, and defined criteria thresholds to compute contact zone accuracy.
Who reviews AI alerts in a typical academy?
A qualified head trainer or programme lead reviews alerts, with veterinary input for medical concerns.
How are the contact zone criteria updated?
Criteria are revised through periodic CPD reviews and coaching meetings, reflecting Canine Good Citizen standards and safety guidelines.
What protects dog welfare when AI flags a potential issue?
A welfare-first protocol requires immediate human assessment and, if needed, temporary coaching adjustments until veterinary clearance.