SASEEBO

The SASEEBO (Safe, Secure, Efficient Airport & Airline Baggage Operations) project addresses persistent inefficiencies in baggage handling by leveraging AI, machine learning, computer vision, and IoT-driven solutions. Despite advancements, baggage mishandling remains costly for airlines, leading to financial losses, security risks, and passenger dissatisfaction. SASEEBO introduces AI-powered baggage damage detection at check-in to reduce fraudulent compensation claims, distant barcode reading for seamless tracking, and deep learning-based untagged baggage recognition to minimize losses. Automated monitoring of handling violations will enhance compliance, while eSIM-based IoT tracking will enable real-time, cross-border luggage localization. AI-driven X-ray CT threat detection will strengthen security, identifying concealed threats like explosives and lithium batteries with greater accuracy than current systems. An AI-powered ownership verification system will also prevent unauthorized baggage exchanges and unattended luggage incidents. The project will be validated at major airports, including İzmir Adnan Menderes, Sabiha Gökçen, and Incheon International, ensuring its adaptability and scalability. A globally structured consortium addresses challenges like AI model training, system integration with legacy infrastructure, and regulatory compliance. By setting new standards in intelligent baggage management, SASEEBO will transform modern aviation's efficiency, security, and passenger experience.