Sensor data can be used in predictive modeling in various ways. For instance, it can be used to predict equipment failure in industries by monitoring the condition of the equipment and predicting its failure based on the data collected. It can also be used in healthcare to predict patient health outcomes based on data collected from wearable devices. In agriculture, sensor data can be used to predict crop yields based on soil and weather conditions. In transportation, it can be used to predict traffic patterns and optimize routes.
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