Why it matters
Without this system, misidentifications, delayed responses, and incomplete reporting can lead to pest spread, unmanaged disease, and failed contractor audits.
From design to safety
Design
AI-assisted survey planning and risk mapping
Reads survey replies, species lists, spacing, and historical pest pressure to draft a monitoring plan, establish baseline crown metrics, and set trigger thresholds aligned with BS 3998 and LOLER requirements.
- smartphone camera
- symptom photo library
- digital field notebook
- monitoring risk map
Build
tech-enabled field setup and data scaffolding
Configures field routes, sampling plots, and reporting templates using sensor feeds, canopy surveys, and soil checks to support early detection workflows during planting or establishment.
- smartphone camera
- infrared thermal imaging camera
- field diagnostic kit
- digital field notebook
Operation
on-site symptom assessment and scoring
Aggregates symptom photos, signs of Phytophthora, OSS indicators, and pest clues to generate risk flags, recommended inspections, and scout routes for the week.
- smartphone camera
- infrared thermal imaging camera
- field diagnostic kit
- symptom photo library
Maintenance
data-driven reinspection cadence and QA
Automates reinspection calendars based on symptom evolution, supports lab submission workflows, and maintains a living record for each tree with chain-of-custody evidence.
- digital field notebook
- field diagnostic kit
- laboratory submission form
- mobile reporting form
Safety
traceable safety and reporting
Links pest risk to public protection plans, sets exclusion zones, logs sightings with timestamps, and generates compliant reports for authorities and clients.
- mobile reporting form
- digital field notebook
- laboratory submission form
- risk-trace ledger
Part by part
- 1
smartphone camera
- Watch for
- visible pest symptoms in crowns and bark lesions that indicate early infestations or disease
- AI action
- classify images and assign risk score for triage
- 2
infrared thermal imaging camera
- Watch for
- canopy stress hotspots and irregular heat patterns
- AI action
- identify candidate locations for targeted field inspection
- 3
field diagnostic kit
- Watch for
- sample collection signs of Phytophthora or root disease
- AI action
- flag specimens for rapid lab testing and result linkage
- 4
digital field notebook
- Watch for
- incomplete observations, missing coordinates or dates
- AI action
- compile observation ledger and generate site log
- 5
laboratory submission form
- Watch for
- collected samples awaiting analysis
- AI action
- route to lab queue and track turnaround
- 6
mobile reporting form
- Watch for
- unreported sightings or incidents
- AI action
- create field incident report and notify supervisor
Worked example
Catching a sample before spread of Phytophthora in a stand of oaks
Illustrative scenario with sample data.
A contracting team detects leaf fade and root collar lesions on several Black Oaks and flags potential Phytophthora in the canopy edge.
Signal in
site: Ashwood Forest; date: 2026-11-03; species: Quercus robur; photos: canopy_closeup1.jpg, canopy_closeup2.jpg; soil_moisture: 22%; GPS: 51.5074,-0.1278; symptoms: chlorosis, nitid root lesions; equipment: smartphone camera, infrared camera, field kit; notes: high rainfall in past week.
System out
AI-generated risk: moderate; recommended actions: collect samples (lab), increase monitoring at coordinates 51.5074,-0.1278, prep incident report, assign crew lead for investigation; report ID: RPT-20261103-001.
Human sign-off: Crew leader approves sampling and report creation; arboricultural consultant signs off on field protocol before lab submission.
How to roll it out
Phase 1
Weeks 1 to 4: Baseline
Install primary sensors, configure field notebooks, and align reporting templates with BS 3998 and LOLER where applicable.
Phase 2
Weeks 5 to 8: Pilot
Test AI triage on 4 sites, refine watchFor thresholds, and route samples to the laboratory under BS 5837 guidance.
Phase 3
Weeks 9 to 12: Scale
Roll out across operations, integrate with tree survey reports, and complete staff training in safety and reporting.
Where people stay in charge
- Decisions on pest identification and action must be signed off by a chartered arboriculturist or eligible AP point of contact.
- All lab submission decisions and action triggers must be reviewed by the arboricultural supervisor prior to field work.
- Final reporting for authorities and clients must be approved by the contracting manager and recorded in the project file.
Questions owners and crews ask
What data does the AI read to detect tree pests and diseases?
The AI reads symptom photos, canopy observations, soil and moisture readings, GPS locations, timestamps, and lab test results to assess risk and trigger actions.
Who approves actions triggered by AI detections?
The arboricultural supervisor or chartered consultant signs off on recommended actions before work proceeds on site.
How are pest detections reported to authorities and clients?
AI-generated reports with incident IDs are routed to the main reporting portal, shared with clients, and filed with local authority records as required.
What are the critical safety checks connected to pest detections?
Public protection plans, exclusion zones, and aerial rescue readiness are reviewed and confirmed by the safety officer before access is granted.