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Predictive Analytics for Incident Prevention in the Transportation of Dangerous Goods: Leveraging AI to Enhance Safety in Hazardous Materials Transportation
Author(s): Takudzwa Musariri (Independent Researcher, Zimbabwe)
Copyright: 2025
Pages: 28
EISBN13: 9798337355641
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Abstract
This chapter explores how predictive analytics can enhance safety in transporting dangerous goods. By integrating artificial intelligence (AI) into transportation systems, companies can shift from reactive to proactive safety measures, preventing incidents before they occur. The chapter examines how predictive models use data from onboard cameras, driver monitoring systems, and advanced analytics to mitigate risks. A case study on TotalEnergies' fleet management highlights the benefits and challenges of implementing predictive systems are highlighted. The chapter concludes with recommendations for improving the accuracy of predictive models and addressing ethical concerns, such as data privacy.
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