Efficient pothole detection using smartphone sensors
In this paper, a Neural Network model is proposed, that uses data acquired from accelerometer and gyroscope sensors, both built in the modern day smartphones, to classify the potholes from the non-potholes. The neural network gives a classification accuracy of 94.78 percent. It also presents a solid precision-recall trade-off with 0.71 precision and 0.81 recall, considerably high for a problem with class imbalance.
Jul 29, 2020
