In a recent AI Studio Challenge Project, a team of Break Through Tech Fellows worked with Marsh McLennan, a major consulting and risk strategy firm, to tackle the high-stakes issue of predicting the impact of hurricanes on vessel traffic off the Atlantic coast.
Published
06/3/2025
The East Coast of the United States is no stranger to hurricanes—powerful storms that pose serious risks to lives, infrastructure, and the economy. Among the many disruptions caused by hurricanes are delays to freight traffic and port operations, which can ripple throughout global supply chains. In a recent AI Studio Challenge Project, a team of Break Through Tech AI Fellows worked with Marsh McLennan, a major consulting and risk strategy firm, to tackle the high-stakes issue of predicting the impact of hurricanes on vessel traffic off the Atlantic coast.
The Challenge
The challenge centered on using machine learning to forecast disruptions in vessel movement caused by storm activity. When ports are forced to close or restrict traffic due to approaching hurricanes, the consequences extend beyond delayed shipments—they affect inventory availability, production timelines, and the financial stability of companies that depend on maritime transport. For businesses and stakeholders, the ability to anticipate these disruptions could make the difference between resilience and major operational setbacks.
The Approach
Break Through Tech AI Fellows approached the problem by leveraging a supervised learning model informed by historical data. They used geospatial datasets including hurricane tracking information and vessel position data. By mapping storm paths against historical vessel movements, the team aimed to identify patterns in traffic slowdowns, port closures, and rerouting behaviors in response to hurricane activity.
The Impact
The project invited a range of analytical techniques and required thoughtful interpretation of complex spatial and temporal data. Through this work, fellows not only advanced their technical skills in machine learning and data science but also explored real-world implications for climate resilience and logistics strategy. The resulting model holds promise for enhancing the ability of businesses to prepare for and mitigate the cascading effects of severe weather events.
This AI Studio challenge highlights how innovative data approaches can support critical decision-making in any extreme climate—empowering companies to better protect their operations, supply chains, and the communities they serve.
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