Motion Detection and Prediction Using ML: Logistic Regression

Abstract: Machine Learning is a subset of Artificial Intelligence (AI). Huge set of data is provided to the machine which is trained using any of the Machine Learning algorithms. In this paper we acquire data from real-time motion sensors continuously over a long period of time. Along with historical data stored in the database, the present runtime data is analysed and used to train the machine. The machine is provided with enough data to learn for itself creating a predictive model with a particular accuracy. Ultrasonic sensors are mounted at different orientations, continuously gathering data of the ether. The data acquired is then analysed, visualized and used for future predictions/ conclusions. Accuracy check is carried out to verify the exactness of the predicted data. Keywords: Data Analytics & Machine Learning, Data pre-processing, Logistic regression, precision, F1 score, categorical values, visualization, an array of ultrasonic sensors is placed at different orientations