Predicting whether temperature-sensitive items will transition outside of a target temperature range during transport using a machine learning model

Abstract

An online system generates a request to transport a set of items from a source location to a destination location. The set of items includes at least one temperature-sensitive item. The system extracts a set of input features about the request to transport the set of items. The set of input features includes an estimated transportation time for transporting the set of items from the source location to the destination location. The system applies a machine learning model to the set of input features to output a score for the temperature-sensitive item, indicating a likelihood that the temperature-sensitive item will transition outside of a target temperature range before completing the transportation. Responsive to the method outputting the score above a threshold, the system adjusts the request and outputs the adjusted request to one or more computing systems, causing the one or more computing systems to display the adjusted request.

CPC Classifications