11 June 2019

Title: Deep Vessel: A new Deep Neural Network for Vessel Arrival Time Prediction

Maritime transportation is a major mode of transportation for domestic and international trade due to the 1) its large capacity, 2) its environment-friendly nature, 3) covering more than 80% of the world trade. On the other hand, many countries with large rivers/canals promote waterway transportation to take a greater share in their total interior transportation market and reduce carbon emission. However, collision avoidance, travel time and arrival time have a key role in maritime transportation.
With the rapid advances in information technologies, a new technology/tool that can enhance safety and efficiency of maritime navigation, and provide customers with more diverse and dynamic information is required by users. Therefore, the main idea of this research is to design and develop a deep learning-based method to predict arrival time using Automatic Identification System (AIS) dataset and augmented information that could eventually be incorporated into a business intelligence dashboard. In order to achieve the aforementioned aim, the current research follows the following objectives: 1)collecting data  and analysis, 2) data cleaning and pre-processing, 3) the selection of a subset from the original set of features, 4) to develop the predictive model and 5) to evaluate the performance of the proposed method.

Bio: Asad Abdi is currently in a postdoctoral position. He held a postdoctoral position and a Research Assistant position at the UTM and UM, Malaysia, respectively.  He received the M.Tech and Ph.D degrees in software engineering and computer science from JNTU, India and University of Malaya (UM), Malaysia, respectively. He published several papers in various ISI journals. He also is reviewer and member of the editorial board of numerous journals. His research interests include Text Mining; Data Mining; Artificial Intelligence; Machine Learning.

Title: Autonomous Logistics Miners for Small- & Medium sized Businesses

The aim of the industrial research project “Autonomous Logistics Miners for Small- & Medium sized Businesses” is to increase the competitive power of the Dutch logistics sector by developing intelligent data mining agents, that can (semi-) autonomously perform the most common data mining functions and require minimal supervision and IT knowledge from the user. Thus, we help small- and medium sized businesses that are overwhelmed with data and have limited time, knowledge and resources to analyse it. We focus on providing insight in the overall performance of supply chains, trends in supply and demand patterns and identifying the critical factors that cause shipment delays and disruptions. Furthermore, we intend to create a symbiotic interaction between humans and intelligent agents, allowing humans to identify conditions of special interest to them and enable the intelligent agents to do the routine work, continuously monitor data streams and raise awareness to the human operator if events occur. During this talk I will introduce the industrial research project, share intermediate results and discuss future research directions.

Bio: Ing. Jean Paul Sebastian Piest MSCM MBA BHRM joined IEBIS in September 2018 as Professional Doctorate in Engineering Researcher. He conducts industrial research within the TKI Dinalog project Autonomous Logistics Miners for Small- & Medium sized Businesses under supervision of Prof. Dr. Maria Iacob and Prof. Dr. Jos van Hillegersberg. His current research interests are enterprise architecture, information systems, agent mining and artificial intelligence. Before joining the IEBIS department, he worked 10 years in the information technology and services industry and was involved in multiple research consortia as an industry partner. He has a strong network in the logistics industry and is actively contributing to the Dutch Assocation of Logistics Management (vLm) and Cross Chain Collaboration Centers supervisory board at TKI Dinalog. He has recently been appointed as the manager of the Logistics Association of Port of Twente.