Purpose: This publication investigates preliminary data quality analyses to estimate the efforts and expected results of the use of data sets for ML solutions already in the data understanding phase of an implementation. Knowledge about the necessary data cleaning efforts and result qualities...

Purpose: Object detection is rapidly evolving through machine learning technology in automation systems. Well prepared data is necessary to train the algorithms. Accordingly, the objective of this paper is to describe a re-evaluation of the so-called Logistics Objects in Context (LOCO) dataset,...

Purpose: Traffic volume in empty container depots has been highly volatile due to external factors. Forecasting the expected container truck traffic along with having a dynamic module to foresee the future workload plays a critical role in improving the work efficiency. This paper studies the...