{"id":8330,"date":"2026-09-29T09:18:21","date_gmt":"2026-09-29T08:18:21","guid":{"rendered":"https:\/\/zal.aero\/?post_type=news&p=8330"},"modified":"2026-10-07T14:27:53","modified_gmt":"2026-10-07T13:27:53","slug":"elo-ai-offshore-drones","status":"publish","type":"news","link":"https:\/\/zal.aero\/en\/news\/elo-ai-offshore-drones\/","title":{"rendered":"ELO: High-Tech for Safer Seas"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text css=””]The research project ELO turns drones into smart helpers at sea. Supported by AI, they provide emergency responders with a real-time situational picture during maritime accidents \u2013 but only once they become even more autonomous can they unlock their full potential.<\/p>\n

Germany’s coasts are more than holiday destinations: this is where wind farms, pipelines and busy shipping lanes meet \u2013 a hub of critical infrastructure. Yet these very areas are also vulnerable. The need for protection is growing, covering accidents, maritime emergencies and environmental hazards as well as defending against targeted sabotage. In every case, one thing matters most: fast detection and response. But by the time reconnaissance aircraft are airborne and delivering reliable information to the command center, valuable time may already have been lost. This is exactly where the research project ELO \u2013 Echtzeitlagebild Offshore comes in.<\/p>\n

The aim is to develop an intelligent system that reaches maritime emergencies as quickly as possible, monitors them in real time and improves the coordination of emergency responders during incidents. Drones play a central role: they collect live data and transmit it in real time to the responsible emergency services. The result is a rapid situational picture that supports responders in their decisions and strengthens maritime safety.[\/vc_column_text][vc_single_image image=”8353″ img_size=”large” css=”” el_class=”zal-image-large”][vc_column_text css=””]ELO’s key questions<\/strong><\/p>\n

To achieve this goal, the project addresses several central questions:<\/p>\n

How can offshore drone missions be planned and carried out with fast response times?
\nHow can large volumes of live data from maritime incidents be processed and transmitted reliably and in real time?
\nHow can this information be integrated into the existing data systems of emergency services?
\nHow can drones be automatically inspected, maintained and prepared for the next mission after deployment?[\/vc_column_text][vc_single_image image=”9312″ img_size=”large” css=”” el_class=”zal-image-large”][vc_column_text css=””]The untapped potential of drones<\/strong><\/p>\n

Drone missions are significantly more cost-effective than helicopter or aircraft deployments. Drones can be used flexibly and launched much faster. So far, however, their potential has only been partially realized: although the drone flies to its mission area on its own, the manual preparation it requires means that pilot and drone usually remain at the same launch site \u2013 so its full mobility goes unused. In addition, after a fully remote-controlled mission, the drone has to be prepared again for its next flight.<\/p>\n

Autonomous maintenance<\/strong><\/p>\n

This is where the drone team at ZAL GmbH comes in. Existing drone-in-a-box systems already enable autonomous takeoffs and landings, but they lack automated maintenance functions. The ZAL team is therefore developing an integrated system: after landing, the drone moves on its own to the maintenance container, a robotic arm docks onto it and charges it, cameras check its condition using AI-based image recognition, a cleaning system removes salt deposits, for example \u2013 and once maintenance is complete, the drone is immediately ready for its next mission.<\/p>\n

The final process is planned to look like this:<\/p>\n