Big Data-Based Risk Assessment Model for Dangerous Goods Transportation: A Case Study for Liguria Region in Italy

The Dangerous Goods Transportation (DGT) presents significant risks to human health, environment, and property. Traditional risk assessment methods have limitations in dealing with the large amounts of data associated with the transport of hazardous materials. However, recent technological advancements have enabled the collection and analysis of big data related to transportation of dangerous goods. In this article, we propose a model based on the use of big data for risk assessment in the dangerous goods transportation in the Liguria Region of Italy. This risk model explored various aspects of DGT transportation, including identification of potential hazards, prediction, and prevention of accidents, and evaluation of the effectiveness of risk management strategies.