In-Memory Storage based Real-Time Data Pipeline for Transportation Equipment in Port

Digital transformation has been widely adopted by smart port systems owing to its opportunities to provide innovative applications. As the importance of storing data for port applications has been noticed, the interest in the data pipeline system that refines and stores the port data in near real-time is also increasing. We proposed and implemented a real-time data pipeline system for port equipment taking full advantage of in-memory storage by leveraging an optimized data model. Experimental results indicate that our proposed architecture significantly improves the data processing, compared to the data processing system with the conventional database system. Our research demonstrates that the proposed architecture can speed up handling the data from port transportation equipment.