ALTITUDE – Automatic aeriaL neTwork InspecTion Using Drones and machinE learning


Period: 01/01/2023 – 31/03/2024

Project Coordinator: Renel Energy & Power Engineering

Project Website:

LinkedIn Page:

Funded by: Iceland, Liechtenstein, and Norway through the EEA Financial Mechanism 2014 - 2021, within the context of the Programme “Business Innovation Greece.”


• Renel Energy & Power Engineering


• HEDNO S.A. (Hellenic Electricity Distribution Network Operator S.A.)



The project ALTITUDE aims to develop an innovative product that uses Unmanned Aerial Vehicles (UAVs - drones) and machine learning algorithms to automatically conduct OHL (Overhead Lines) assessments.

An appropriate data collection protocol will be used, along with an online tool that will automatically analyze and assess the condition of the Medium/High Voltage (MV, HV) network infrastructure (poles, cross-arms, insulators, etc.). Machine learning algorithms that have been properly trained using UAV-taken, high-resolution aerial photos as well as infrastructure photos from the HEDNO archive will be used for the analysis and assessments.

HEDNO offers its feedback along with all the necessary technical data and information, which helps to validate and improve the inspection methodology. HEDNO also contributes significantly to the final design of the tool by conveying the company's unique requirements for the inspection of its aerial network.

To evaluate the feasibility of this proposal's implementation and its response to actual conditions, a pilot program has been implemented on the grid of the Greek island of Lesvos, which is operated by HEDNO and combines both Medium and High Voltage overhead lines.