Primary operating owner
Director Geology & Mining; District Mining Officer; Mine COO/Head Security
P14 · Representative solution case · Government / Mining / PSU
Where is the largest gap between permitted quantity, measured extraction, stock and transported material?
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
Illegal extraction/transport, uncertain lease boundaries and disconnected permit, vehicle and imagery data cause revenue leakage and weak enforcement.
Director Geology & Mining; District Mining Officer; Mine COO/Head Security
Mining Secretary; PSU CMD/Director Operations
GIS/Remote Sensing; Enforcement; e-Rawanna/IT; Drone Cell; Fleet
Illegal-mining incident, e-permit modernisation, auction/new leases, revenue shortfall, drone survey mandate, check-post digitisation.
02 · Before and after
Illegal extraction/transport, uncertain lease boundaries and disconnected permit, vehicle and imagery data cause revenue leakage and weak enforcement.
Drone/DGPS survey, lease/stockpile GIS, volumetric/change analytics, RFID/GPS/CCTV integration, e-permit linkage, command centre and mobile enforcement.
03 · Stakeholder experience
Director Geology & Mining
District Mining Officer
Mine COO/Head Security
Mining Secretary
PSU CMD/Director Operations
GIS/Remote Sensing
Enforcement
e-Rawanna/IT
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
Lease inventory/accuracy? Permit flow? Weighbridge/RFID/GPS data? Survey frequency? Enforcement process? Revenue leakage estimate?
Bring the required map, address, road, place, imagery, asset, customer and operational data into a governed Inspection AI workspace.
Asset risk, Imagery review, Inspection, Defects, Remediation give each stakeholder the information, decision and action appropriate to their role.
8–10 week cluster pilot with drone/DGPS, GIS, change/volume analysis and vehicle/permit integration.
Operationalise the model through Per area/lease survey + platform + per vehicle/device + analytics + managed operations/O&M., adoption governance, service measurement and a managed improvement backlog.
05 · Solution and data architecture
Map, address, place, route, imagery, boundary and context layers
Customer, asset, order, sensor, incident, task or transaction records
Asset risk · Imagery review · Inspection · Defects · Remediation
Survey accuracy; variance detection accepted; alert precision; enforcement actionability; quantified revenue opportunity.
Field survey, data creation, integration, migration, validation and O&M
Product detailsMarket, territory, network and spatial decision analytics
Product detailsSurvey, orthomosaic, point cloud, 3D and inspection outputs
Product detailsWeb/mobile maps, vector/raster tiles and visualisation
Product details06 · Outcome and evidence
8–10 week cluster pilot with drone/DGPS, GIS, change/volume analysis and vehicle/permit integration.
07 · Governance and scale
Server-enforced identity, least-privilege app membership, role-specific actions and auditable administration.
Source lineage, quality thresholds, update cadence, retention, consent and controlled data sharing.
Named process owners, exception SLAs, escalation, change control and adoption measurement.
Baseline, intervention and outcome metrics reviewed on an agreed cadence with accountable owners.
Your outcome, powered by Mappls
Bring the baseline, workflow, users, data and success criteria. Mappls will shape a bounded proof and production path.