{"id":495,"date":"2026-02-27T13:04:35","date_gmt":"2026-02-27T12:04:35","guid":{"rendered":"https:\/\/research.dblue.it\/dialog\/?p=495"},"modified":"2026-02-28T23:23:16","modified_gmt":"2026-02-28T22:23:16","slug":"anatomy-of-a-dry-run-behind-the-scenes-of-ai-integration-in-air-traffic-management","status":"publish","type":"post","link":"https:\/\/research.dblue.it\/dialog\/2026\/02\/27\/anatomy-of-a-dry-run-behind-the-scenes-of-ai-integration-in-air-traffic-management\/","title":{"rendered":"Anatomy of a Dry Run: Behind the scenes of AI integration in Air Traffic Management"},"content":{"rendered":"<p><em>A Dry Run is the critical bridge between scientific theory and operational constraints. Ahead of the upcoming Human-in-the-Loop trials, the DIALOG project team gathered to test interoperability and robustness under real-time conditions.<\/em><\/p>\n<h4 data-path-to-node=\"5\"><b data-path-to-node=\"5\" data-index-in-node=\"0\">Testing Operational Readiness<\/b><\/h4>\n<p data-path-to-node=\"6\">During the sessions in Salon-de-Provence, we migrated our three core services from isolated lab environments to the SIMADES platform (developed by SINTEF and hosted at ONERA).<\/p>\n<p data-path-to-node=\"7\">The primary focus was ensuring the entire system\u2019s operational readiness. We verified the multi-partner architecture\u2019s ability to support real-time data exchange, confirming that the full technical pipeline is stable, integrated, and functioning exactly as expected for the upcoming trials.<\/p>\n<h4 data-path-to-node=\"8\"><b data-path-to-node=\"8\" data-index-in-node=\"0\">Synchronizing Multimodal Streams<\/b><\/h4>\n<p data-path-to-node=\"9\">The &#8220;anatomy&#8221; of the Teamwork Assistant we are building relies on three pillars: Pilot requests, Environment, and Controller state.<\/p>\n<p data-path-to-node=\"10\">During the run, a major focus was Data Exchange and Temporal Alignment. We worked to ensure that multimodal inputs, such as a spike in heart rate or a specific voice command, are perfectly timestamped across all logs. This synchronization is mandatory to accurately associate a specific operator state to his or her task goals. We are fine-tuning this approach to create an AI that truly adapts to the needs of the operator.<\/p>\n<h4 data-path-to-node=\"11\"><b data-path-to-node=\"11\" data-index-in-node=\"0\">Verifying the Feedback Loop<\/b><\/h4>\n<p data-path-to-node=\"12\">Before testing how the AI supports the operator, the system needs a solid communication baseline. We used these sessions to verify the full loop, from initial data ingestion to displaying suggestions on the controller&#8217;s interface. With the connectivity challenges successfully addressed, we can now proceed to the next step, focusing entirely on human factors and operational strategy.<\/p>\n<h4 data-path-to-node=\"13\"><b data-path-to-node=\"13\" data-index-in-node=\"0\">From Data to Insight<\/b><\/h4>\n<p data-path-to-node=\"14\">For an applied research project, the ultimate product is not just data. It is <b data-path-to-node=\"14\" data-index-in-node=\"78\">actionable knowledge that brings us closer to the operational solutions of tomorrow.<\/b> By resolving integration issues early, we ensure that the Operational Validation in March generates clean and reproducible results. This preparation clears the way for what matters most: allowing us to gather human insights from expert controllers and truly understand the dynamics of Human-AI Teaming.<\/p>\n<p data-path-to-node=\"14\"><!--more--><\/p>\n<p data-path-to-node=\"14\">\u27a1\ufe0f We are sharing live updates and further technical details with our professional network. Follow the progress of the DIALOG project on <a href=\"https:\/\/www.linkedin.com\/feed\/update\/urn:li:activity:7433138988833660928\">LinkedIn<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>A Dry Run is the critical bridge between scientific theory  [&#8230;]<\/p>\n","protected":false},"author":19,"featured_media":496,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5,13],"tags":[],"class_list":["post-495","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","category-validations"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Anatomy of a Dry Run: Behind the scenes of AI integration in Air Traffic Management - DIALOG<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link 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