Method and system to estimate smoking episodes from smoke puffs using a wearable device

Abstract

This disclosure relates generally to method and system for estimating smoking episodes from smoke puffs using a wearable device. Since the expense of treating diseases is rising, a digital smoking cessation improves healthcare systems such as cardiovascular issues. To achieve an optimum model given the platform limitations a very compact model is built specifically for the target microcontroller platform. The method of the present disclosure generates an optimum model for deployment on the wearable device using a pretrained deep neural network (DNN). A set of sensor signals are inputted to a convolutional neural network (CNN) smoke detection model to detect smoke puffs. Gesture classifier determines whether the user of the wearable device is engaged/engaging in a smoking session. Further, the method provides users of the wearable device with a cloud estimated smoking behavior analysis based on a set of smoking episodes to generate a set of user risk scores.