Primary operating owner
Survey/Engineering; Asset Integrity; Digital Twin
P57 · Representative solution case · Cross-industry / Government / Infrastructure
Drone, LiDAR, Reality Capture & Inspection
Which high-cost field inspection or survey can be converted into repeatable digital evidence?
Evidence distinction: this is a representative solution case constructed from the source requirements and Mappls delivery pattern. It is not presented as a named-customer outcome unless a separate verified customer story is explicitly linked.
01 · Operating context
The decision environment and the problem to change
Assets, corridors and sites lack current, measurable ground truth, making inspection, planning and change detection slow and costly.
Economic decision
COO; Project/Asset Director
Technical influence
GIS; Drone Ops; Survey; HSE
Why action becomes urgent
New project, asset audit, incident, DPR/master plan, maintenance backlog, digital twin programme.
02 · Before and after
Change the operating model, not only the interface
Fragmented context and delayed action
Assets, corridors and sites lack current, measurable ground truth, making inspection, planning and change detection slow and costly.
- Location, operational and enterprise data remain separated
- Stakeholders make inconsistent decisions from partial context
- Exceptions are found late and evidence is difficult to reconstruct
A governed location-aware decision loop
Drone/LiDAR/360/imagery capture, orthomosaic/3D models, feature extraction, inspection analytics, change detection, GIS/digital twin integration.
- One role-aware workspace in Mappls Asset Inspection AI
- Live context moves directly into the responsible workflow
- Every decision, scenario and outcome can be measured and audited
03 · Stakeholder experience
One shared system, different role moments
Own and govern
Survey/Engineering
Own and govern
Asset Integrity
Decide and coordinate
Digital Twin
Decide and coordinate
COO
Decide and coordinate
Project/Asset Director
Execute and verify
GIS
Execute and verify
Drone Ops
Execute and verify
Survey
Inside Mappls Pro, the same user can hold this role here and a different role in another application. Membership, saved runs and administration remain app-specific.
04 · Day-in-the-life journey
How the solution turns information into an operational result
Frame the operating decision
What accuracy, frequency and legal/safety standards apply? Which decisions consume the output?
Connect the location foundation
Bring the required map, address, road, place, imagery, asset, customer and operational data into a governed Inspection AI workspace.
Act through role workflows
Asset risk, Imagery review, Inspection, Defects, Remediation give each stakeholder the information, decision and action appropriate to their role.
Prove the intervention
Capture representative site/corridor and deliver accepted model plus one inspection/change workflow.
Scale and continuously improve
Operationalise the model through Per-area/asset survey + analytics/platform + recurring update service., adoption governance, service measurement and a managed improvement backlog.
05 · Solution and data architecture
The Mappls capabilities behind the experience
Location foundation
Map, address, place, route, imagery, boundary and context layers
Operational context
Customer, asset, order, sensor, incident, task or transaction records
Application workflow
Asset risk · Imagery review · Inspection · Defects · Remediation
Outcome loop
Accuracy/completeness accepted; cycle time and field exposure reduce; repeat update method agreed.
Drone/LiDAR/Reality Capture
Survey, orthomosaic, point cloud, 3D and inspection outputs
Product detailsRealView 360 & Ground Imagery
Geotagged 360 imagery, photos and videos
Product detailsSurvey, Integration & Managed Updates
Field survey, data creation, integration, migration, validation and O&M
Product detailsGeoAI & Spatial Decision Models
ML/AI, risk, demand, accessibility, image and anomaly models
Product details06 · Outcome and evidence
Make the value claim measurable before scaling
Bounded proof
Capture representative site/corridor and deliver accepted model plus one inspection/change workflow.
- Confirm the baseline and decision scope: What accuracy, frequency and legal/safety standards apply? Which decisions consume the output?
- Use representative and, where approved, customer data in the configured workspace
- Review measurable success with the operating and economic owners: Accuracy/completeness accepted; cycle time and field exposure reduce; repeat update method agreed.
- Document data quality, adoption, security, service and scale findings
- Convert evidence into a phased production scope and accountable value plan
07 · Governance and scale
Operate the solution safely and sustainably
Identity and access
Server-enforced identity, least-privilege app membership, role-specific actions and auditable administration.
Data governance
Source lineage, quality thresholds, update cadence, retention, consent and controlled data sharing.
Operating governance
Named process owners, exception SLAs, escalation, change control and adoption measurement.
Value governance
Baseline, intervention and outcome metrics reviewed on an agreed cadence with accountable owners.
Your outcome, powered by Mappls
Put Drone, LiDAR, Reality Capture & Inspection into your operating context
Bring the baseline, workflow, users, data and success criteria. Mappls will shape a bounded proof and production path.