DEVELOPING A GEODATABASE FOR EFFICIENT UAV-BASED AUTOMATIC CONTAINER CRANE INSPECTION

Abstract. Inspection of container cranes is an important task to maintain the all-day operation in harbours. In practice, manually carrying out inspection process not best solution due complexity, time consumption, and cost. The manual often performed by specialists who capture images areas interest then check analyse these visually. Once a critical area spotted, industrial climbers are hired part in-situ. visual pre-inspection should be reliable accurate, because in-situ expensive, but miss defected might lead failure crane. From this point view, we came up with main idea joint research project ABC-Inspekt which embodies exploratory investigation providing automatic using technology Unmanned Aerial Vehicles (UAV). Images, captured systematically regularly, managed database facilitate access. access done operator, also image analysis approach automatically identifies possible defects stores them back into database. paper, introduce schema, web frontend for data storage, access, viewing, show intermediate results processing workflow.