Human activities recognition in smart living environment - Teh, Min Yang (Nanyang Technological University, 2023)
Smartphones with embedded sensors can track users' movements and corresponding activities in real-time. This serves as the foundation for the recognition of human activity in smart environments where users can accurately monitor their lifestyle and physical health. There are various different well-known machine learning techniques that can process this sensor data to derive high-level information about users, including their locations, activities they are engaging in, and the associated energy devices they are using.