Case Study: Piraeus Container Terminal achieves hyperlocal wind prediction for safer port operations with Ex Machina and WeatherXM

Piraeus Container Terminal boosts gust prediction accuracy by 55% with Ex Machina

Piraeus Container Terminal (PCT), one of the busiest container ports in the Mediterranean, faced major disruptions to its crane operations due to unpredictable, hyperlocal wind conditions that standard forecasts could not predict. To address this challenge, PCT partnered with Ex Machina to implement a solution using WeatherXM weather stations and machine learning-enhanced forecasting.

Ex Machina installed a network of 28 WeatherXM stations across the terminal that report data every three minutes. This infrastructure fed into ML models that learned the terminal's unique wind patterns, resulting in a 55% improvement in gust prediction accuracy. This solution provided PCT with the precise, location-specific forecasts needed to plan operations confidently, reduce unnecessary crane shutdowns, and significantly improve safety and efficiency.

Piraeus Container Terminal (pct)