Industrial IoT to Predictive Analytics: A Reverse Engineering Approach from Shipping

Abstract

A novel mathematical framework to support industrial digitization of shipping is presented in this study. The framework supports a data flow path, i.e. from Industrial IoT (i.e. with Big Data) to Predictive Analytics, where digital models with advanced data analytics are introduced. The digital models are derived from ship performance and navigation data sets and a combination of such models facilitates towards the proposed Predictive Analytics. Since the respective data sets are used to derive the Predictive Analytics, this mathematical framework is also categorized as a reverse engineering approach. Furthermore, a data anomaly detection and recover procedure that is associated with the same framework to improve the respective data quality are also described in this study.