AI-Powered Grid Inspection Platform
Analyzes drone and field photos with AI, links each finding to the right grid equipment and feeds approved findings straight into your maintenance process. The inspection module of the GEOENER family.
GEONIVA is an AI-powered aerial and field inspection platform for electricity distribution grids. It analyzes imagery from drone flights and field crews' photos with AI, links every finding to the correct grid equipment in your GIS, and feeds approved findings automatically into your existing maintenance process — forms, alarms, work orders. Inspection maintenance shrinks from days of manual review to minutes of approval flow. It generates drone mission files from a work order in one click, produces orthophotos from flight imagery and overlays them on the grid map. Vegetation clearance analysis audits conductor-to-vegetation distances against regulatory tables. The core architecture is channel-agnostic: new inspection channels such as ground robots and satellite imagery are on the roadmap and plug in without touching the core. GEONIVA is fully integrated with the GEOENER platform, licensed as a standalone module, and supports on-premises deployment.
Module by module.
A drone mission file is generated in one click from the work order's equipment list and can be loaded into common flight planning software. Routing is deterministic — the same work order always yields the same mission. Altitude and speed are configurable per installation.
AI-powered anomaly detection runs on flight and field photos, with class-to-finding-type mapping managed by the organization. Detections below the confidence threshold are filtered out automatically. Vegetation clearance analysis audits conductor-to-vegetation distances against regulatory tables.
The model lifecycle runs through Draft → Test → Approved → Retired with one-click rollback. Every finding is permanently linked to the model version that produced it, and the active model is validated at inference time so nothing is ever produced with the wrong version.
A photo's EXIF location is matched automatically to the nearest grid equipment in the GIS, so field crews' photos arrive already linked with no extra work. Coverage checks report equipment in the work order that was never photographed.
Orthophotos are generated automatically from flight imagery. The resulting layers are overlaid with the grid on the map screen, with per-layer visibility, opacity control and automatic zoom.
An approved finding automatically fills in the corresponding answer on the maintenance form, triggering your existing alarm and work order mechanism unchanged. The review flow tracks pending findings, approve/reject decisions, the reviewer and the date.
Finding reports are exported as CSV/Excel with date and filter criteria. Findings can be ingested from external systems over REST with duplicate protection, then matched to GEONIVA detections by location and type.
Role-based authorization is enforced at endpoint level and modules are switched on or off by licence. For privacy compliance, personal data such as identity numbers and IBANs is masked automatically. The interface is available in Turkish and English, with on-premises deployment supported.
Pick the work order and let GEONIVA generate the drone mission file from its equipment list, then load it into your flight planning software. Routes are generated deterministically — the same work order always yields the same mission.
Once the flight is done, upload the photos in bulk. Field crews' tablet photos are already in the system — no extra step.
Every photo is linked to the correct equipment from its EXIF location; equipment left without a photo shows up in the coverage report.
Detection runs in the background; anomalies land in the finding pool with their confidence score and model version. Detections below the confidence threshold are filtered out automatically.
An engineer reviews findings with their imagery and approves or rejects them. Every decision is recorded with who and when.
The approved finding becomes an answer on the maintenance form; your alarm and work order mechanism takes over with no changes required.
Scale grid inspection obligations with drones and feed findings into your existing maintenance and work order process unchanged.
Photos taken in the field link themselves to equipment, and the coverage report shows which equipment was never captured.
Added as a module to your existing GEOENER installation: the same GIS infrastructure and asset records, with no new system to learn.
Capabilities in development.
Ground robots and satellite imagery are architecturally ready to feed the same finding pool as drone and mobile.
On top of today's clearance auditing, proactive pruning planning by forecasting vegetation growth in the coming period.
Structured data extraction from project and document imagery; a natural-language Q&A assistant over inspection data.
All products run on the same map, the same authorization model and the same asset records.
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