Human Activity Recognition Using Sensors And Machine Learning

This article discusses the recent advances in hardware and acquisition devices that have enabled the deployment of the Internet of Things, and how this has enabled the task of human activity recognition. It is a challenging task due to many inherent issues and practical problems, such as filtering noisy sensor data and extracting high-quality features. Machine learning has been shown to be effective and achieves a state-of-the-art performance. This Special Issue offers an opportunity to report the progress in human activity recognition using sensors and machine learning.