Abstract by Stephen McKechnie
Human Activity Recognition with Smartphones
We are living in a world where advanced technology can detect motion and identify various human activities. One of the advanced and easily accessible technologies we have are our smartphones. With accelerometers and gyroscopes embedded in smartphones, apps can measure extreme and subtle forces exerted on the phone. For this research, I will use machine learning algorithms to assess how accurately smartphones can recognize simple daily human activities. These algorithms make use of dimensionality reduction techniques to determine which accelerometer and gyroscope readings give the best prediction of human activity.