Primary operating owner
Narcotics Commissioner; Agriculture/Horticulture Director; Enforcement/Survey Head
P23 · Representative solution case · Government / Agriculture / Enforcement
Which plots should inspectors visit first, and can current evidence defend the acreage and yield assessment?
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
Licensed/regulated cultivation is difficult to verify consistently across plots, crop stages, yield and field inspections.
Narcotics Commissioner; Agriculture/Horticulture Director; Enforcement/Survey Head
Revenue/Home/Agriculture Secretary; Agency Commissioner
Remote Sensing/AI; GIS; Field Survey; Licensing/Permit IT
Annual crop licensing cycle, acreage/yield dispute, remote-sensing modernisation, enforcement review, scheme expansion.
02 · Before and after
Licensed/regulated cultivation is difficult to verify consistently across plots, crop stages, yield and field inspections.
GIS plot registry, mobile survey, imagery preprocessing, crop/yield/biophysical models, change detection, inspection planning and monitoring application.
03 · Stakeholder experience
Narcotics Commissioner
Agriculture/Horticulture Director
Enforcement/Survey Head
Revenue/Home/Agriculture Secretary
Agency Commissioner
Remote Sensing/AI
GIS
Field 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
Plot/licence data quality? Imagery frequency/resolution? Ground truth? Model accuracy? Inspection capacity? Legal evidentiary needs?
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.
One-season/district pilot with plot registry, imagery, field samples, model/change detection and application.
Operationalise the model through Per area/season data and analytics + platform/users + field app + managed modelling/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
Plot match and model accuracy; anomaly precision; inspection productivity; evidentiary acceptance; scale data plan.
Geotagged 360 imagery, photos and videos
Product detailsML/AI, risk, demand, accessibility, image and anomaly models
Product detailsSurvey, orthomosaic, point cloud, 3D and inspection outputs
Product detailsField survey, data creation, integration, migration, validation and O&M
Product details06 · Outcome and evidence
One-season/district pilot with plot registry, imagery, field samples, model/change detection and application.
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.