What modern input variable does AI/ML processing incorporate beyond traditional kinetic models?
Specific storage temperature logs rather than just the average storage temperature.
Modern predictive systems leveraging Artificial Intelligence and Machine Learning move beyond the limitations of traditional kinetic models, which often relied on simplified assumptions like uniform conditions or averaged temperature data. AI/ML algorithms are capable of processing high-dimensional, complex datasets that include highly granular information, such as detailed, time-stamped temperature logs from specific storage environments. By incorporating these specific logs, along with packaging permeability data and the interplay between chemical and physical indicators, AI can identify subtle, non-linear degradation relationships that were invisible to earlier, more restrictive single-variable kinetic calculations.
