Why it matters
Without AI, misjudged crane capacity, improper rigging, or unclear exclusion zones can lead to unsafe lifts, near-misses, and non-compliance with safety and planning requirements.
From design to safety
Design
AI enhances planning and method design
The system reads site surveys, tree risk assessments, load calculations, and capacity charts to propose a compliant lift method, crane selection, exclusion zones, and a staging sequence aligned to BS 5837 and LOLER requirements.
- crane capacity chart
- lift plan document
- piece weight database
- rigging slings inventory
Build
Precise prep for lift execution
It cross-checks exclusion zones, workscope, rigging setup, and crane access against现场 constraints, updating rigging plans, access routes, and equipment lists before mobilisation, with ground bearing checks and soil testing results.
- lifting plan document
- rigging slings inventory
- exclusion zone signage kit
- rigging hardware kit
Operation
Real-time lift monitoring and decisions
The AI tracks current load, wind, sway, and encroachment data; it prompts adjustments, retargets load paths, or aborts lifts to maintain a defined safety margin and keeps the lift log current.
- crane capacity chart
- lift plan document
- piece weight database
- exclusion zone signage kit
Maintenance
Ongoing inspection and calibration
It logs crane mobility checks, rigging wear, sling integrity, and weight data, triggering service intervals, recalibration of capacity charts, and automated QA checks against LOLER intervals and BS standards.
- crane capacity chart
- rigging slings inventory
- piece weight database
- lift plan document
Safety
Compliance, rescue, and public protection
Automated alerts ensure aerial rescue readiness, public protection, wildlife law adherence, and utility coordination, with sign-off by a qualified safety officer and client approvals in the formal project file.
- exclusion zone signage kit
- lift plan document
- rigging hardware kit
- crane capacity chart
Part by part
- 1
crane capacity chart
- Watch for
- under-rated capacity, wind drift, unexpected loads, dynamic effects to catches weaknesses
- AI action
- reads crane data, wind, and load signals; updates capacity buffer and alerts supervisor.
- 2
lift plan document
- Watch for
- incomplete method, missing constraints, improper access routes, conflicting plan elements
- AI action
- validates plan against site constraints; flags gaps and requests amendments.
- 3
piece weight database
- Watch for
- unknown limb weights, variable load centers, miscalculations in sling angles
- AI action
- verifies weights from species catalog and assigns safe lifting factors.
- 4
rigging slings inventory
- Watch for
- wear, knot damage, compromised slings, incorrect sling selection
- AI action
- checks sling condition against LO/TO requirements; suggests replacements.
- 5
exclusion zone signage kit
- Watch for
- ambiguous boundaries, missing barriers, inadequate visibility
- AI action
- generates zone maps and orders signage enhancements.
- 6
rigging hardware kit
- Watch for
- lost shackles, damaged hooks, worn bolts, incompatible gear
- AI action
- inspects hardware compatibility and flags unsafe components.
Worked example
Craned Removal of Specimen Oak with Complex Crown
Illustrative scenario with sample data.
A mid-size utility corridor job requires a staged removal with multiple rigging points and strict exclusion zones, demanding precise coordination with traffic management and ground protection.
Signal in
siteId=TX47; wind=12km/h; gust=18km/h; craneModel=G2-120; loadWeights=[branchA:420kg, branchB:380kg, limbC:520kg]; exclusionRadius=25m; soilType=clay; groundBearing=120kPa; weatherForecast=stable; crewCount=6
System out
liftPlanId=LP-2026-11-08; clearanceMap=CM-11-08; alert=ZoneActionRequired; recommendedAction=reconfigure rigging, re-route traffic, and extend exclusion zone; auditTrail=AR-2026-11-08
Human sign-off: Chief climber approves lift plan after validating AI-suggested margins, soil bearing data, and site constraints with the project engineer; sign-off retained in project file.
How to roll it out
Phase 1
Weeks 1 to 4: Baseline
Establish AI data feeds, integrate with existing lift plans, and validate against a small removal block, ensuring field operatives understand system prompts and logs.
Phase 2
Weeks 5 to 12: Ramp-up
Scale AI use to full project planning; train crews on AI-driven lift plan interpretation, zone management, and incident reporting workflows.
Phase 3
Weeks 13 onward: Operational maturity
Maintain AI governance, calibration, and performance reviews; embed learnings into standard operating procedures and client-facing documentation.
Where people stay in charge
- Decisions about lift aborts, zone safety, and significant plan changes must be signed off by the qualified safety officer or project engineer.
- All AI-derived changes must trigger an auditable human review prior to mobilisation.
- The safety case for the lift remains under the authority of the supervising site manager and utility liaison, who sign the final plan.
Questions owners and crews ask
What data feeds does AI use for crane planning?
AI uses crane capacity charts, piece weights, wind forecasts, site surveys, soil data, and exclusion zone requirements to generate and verify lift plans, with a traceable decision log for audits.
Who approves lift plans generated by the AI system?
The qualified safety officer and the project engineer must review and sign off on AI-generated lift plans before mobilisation, with a documented approval timestamp.
How does AI handle unexpected changes on site?
It recalculates loads, re-evaluates exclusion zones, and flags adjustments for supervisor approval, recording all deviations and rationale in the lift audit record.
Can AI integrate with existing site safety documentation?
Yes, it aligns lift plans with LOLER, BS 3998, and BS 5837 requirements, exports updated safety records, and maintains versioned safety dossiers for regulatory reviews.