Transportation & Logistics

Use cases: Machine Learning Solutions

Machine Learning solutions are an excellent tool to overcome challenges such as increasing globalization and traffic volume, or concerns of environmental protection. Machine Learning models can predict the optimal transportation patterns based on historical patterns, help businesses become time- and cost-efficient, as well as the whole industry become safer and more environmentally friendly.

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Predicting traffic and shipping volume by sophisticated traffic modeling

With historical data collected from a transportation management system, a Machine Learning model can predict future traffic and shipping volume. The model also considers external factors such as weather or holidays and can update experts with the frequency desired for each use case.

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Automatic visual inspection of cargo

Manually inspecting large amounts of cargo is time-consuming and requires trained humans who can recognize small imperfections. A modern Computer Vision system on the other hand can be trained to monitor cargo in real time, and recognize imperfection with a high precision.

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Optimizing cargo load and route planning

In order to minimize the loss caused by empty truck miles, Machine Learning can help create the optimal route for a set of vehicles. Analyzing historical traffic patterns, road and weather conditions and other factors, it can predict the ideal route including multiple stops, as well as update itself based on current events, in order to maximize the profit and minimize driving time.

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