Forty-two (42) Orange Côte d'Ivoire employees officially received their certificates of completion in September 2026 in Yamoussoukro, after completing 1 000 hours of drone piloting training, including 5 photogrammetry specialists and one information system expert. This graduation ceremony illustrates the ambition of Orange CI: to make innovation a concrete lever for employees, operational performance, and customer experience.
It is part of the strategic project initiated since 2022 by the telecom operator, which is deploying a drone-assisted inspection solution to monitor the condition of its sites (towers, buildings, solar fields, etc.). After the initial experimental phases, this project reached a milestone in 2025 with the transition to its industrialization phase.
Through this scaling up and the qualification of field teams in 2026, Orange Côte d'Ivoire intends to strengthen the safety of network personnel, optimize its maintenance costs, and improve the quality of service offered to its subscribers. More than a simple tower inspection tool, these flying devices pave the way for new business applications.
For example, 3D modeling helps improve radio coverage in populated areas. Furthermore, an educational component is aimed at children to teach them the design, programming, and piloting of the devices.
Technical Process. For the telecommunications company, the challenge is no longer just to fly drones, but to organize a complete operational chain, from the initial request to reporting.
In practical terms, initiators formulate their intervention request on the iFlex web and mobile application. This specifies the site to be inspected, the period, the equipment used, and the designated remote pilot.
After validation by managers, technicians go on-site and fly the device. During the flight, the equipment captures technical high-definition footage of the sites to be inspected.
Finally, the application automatically saves the photos and GPS coordinates to generate precise reports for the operations teams. DroneAI Inspection.
In order to accelerate the analysis of data collected in the field, the technology incorporates an artificial intelligence module (IA). This tool automatically processes images using YOLO and ResNet50 models to identify several types of anomalies.
The algorithms detect aging with 86% precision, rust and oxidation at 92%, verticality defects at 95%, as well as thermal overheating at 97%. Thanks to this automated analysis, the examination time per site drops from 3 or 4 hours manually to less than 30 minutes.
The platform establishes a criticality level to classify infrastructure and prioritize technician deployment. Investment and Operational Results.
This industrialization and investment strategy is yielding very concrete results for the operator. The current fleet counts 12 devices and has enabled 83 inspections in different areas of the country, notably in Yamoussoukro, Abengourou, Bouaké, Daloa, and San-Pedro, during two maintenance campaigns.
All of these operations took place with zero reported incidents. By avoiding systematic manual climbing along the towers, Orange Côte d'Ivoire reduces risk exposure for its technicians while improving the reliability of its inventory.
Early detection of corrosion or cracks allows for the repair of structures before any network outage. Anselme Akéko.
Published on 29/09/26 17:23. The Editorial Staff.
