(untitled) (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Human activity recognition, or HAR for short, is a broad field of study concerned with identifying the specific movement or action of a person based on sensor data.The sensor data may be remotely recorded, such as video, radar, or other wireless methods. It contains data generated from accelerometer, gyroscope and other sensors of smart phone to train supervised predictive models using machine learning (ML) techniques like logistic regression, decision tree and support vector machine (SVM) to generate a model. These ML techniques can be used to predict the kind of movement being carried out by the person, which is divided into six categories walking, walking upstairs, walking down-stairs, sitting, standing and laying.Results show that the SVM approach is a promising alternative to activity recognition on smart phones compared to other ML techniques.