Abstract: Machine Learning is a subset of Artificial Intelligence (AI). Huge set of data is provided to the machine which is trained using Logistic Regression algorithm. We have acquired 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. In this paper we carry out data visualization procedure and statistical analysis of the data which was acquired in our previous assignment, ‘Motion Detection and Prediction Using ML: Logistic Regression’. The acquired data is made to correspond to a particular Fuzzy Logic by means of programming.
Keywords: Fuzzy Logic, Data Analytics and Machine Learning, Data pre-processing, Logistic regression, accuracy, precision, F1 score
| DOI: 10.17148/IJARCCE.2019.81014