Nomadic Drones provides autonomous drone inspection systems for TSOs and DSOs to monitor power grid assets continuously. The integrated self-recharge capability allows for extended deployment without manual intervention or external infrastructure. Their software solution uses machine learning for automated damage detection, ticket generation, and efficient data processing to reduce inspection timelines.
Funding
Funding not disclosed
Founders
Product
Problem
Utility companies rely on manual, crew‑based inspections of transmission and distribution lines, which are labor‑intensive, hazardous, and can take months to complete, leading to delayed defect detection and growing maintenance backlogs.
Solution
Nomadic Drones offers an autonomous, self‑recharging drone platform that conducts continuous visual inspections of power‑grid assets without human intervention. The drones land on live conductors to recharge, eliminating range limits and the need for ground support infrastructure. Flight missions are planned and executed automatically, capturing high‑resolution imagery along the entire line. Collected data are uploaded to a cloud service where machine‑learning models identify damages, link images to asset records, and generate maintenance tickets. Operators access a web‑based dashboard that visualizes asset conditions on an interactive map, supports human‑in‑the‑loop validation, and prioritizes backlog items. The end‑to‑end workflow reduces inspection cycles from months to minutes, improves safety, and enables proactive grid management.
Target Audience
Primary customers are transmission system operators (TSOs), distribution system operators (DSOs), and utility maintenance contractors that need fast, safe, and cost‑effective grid inspections.
Features
- Self‑recharging capability that lands on energized power lines, allowing indefinite on‑line operation without ground charging stations
- Fully autonomous flight planning and obstacle avoidance for large‑scale transmission corridors
- AI‑driven damage detection (corrosion, broken conductors, vegetation encroachment) with confidence scoring
- Human‑in‑the‑loop validation interface to confirm AI findings before ticket creation
- Automatic image‑to‑asset linking and generation of actionable maintenance tickets in the utility’s work‑order system
- Interactive GIS map view for real‑time asset condition monitoring and inspection status tracking
- Cloud‑based data sync with end‑to‑end encryption, supporting rapid upload of inspection footage and scalable storage
- Integration hooks (APIs) for exporting tickets and asset data to existing enterprise asset management platforms