Classic fault detection and classification has some classic problems. It’s reactive, time-consuming to set up, and any ...

AI adoption accelerates worldwide, with over a billion users. Lower AI literacy boosts usage, costs drop, and society enters ...

Digital transactions have emerged as a dominant force in today’s global commerce sector, empowering businesses and financial institutions like never before. However, at the ...

Wearable sensor data combined with machine learning predicts fall risk in Parkinson's patients, enhancing preventive care and clinical outcomes over five years.

Overview This project provides the implementation for the paper, Federated Learning for Hierarchical Fall Detection and Human Activity Recognition, which presents a federated learning framework for ...

Fall incidents are considered as the leading cause of disability and even mortality among older adults. To address this problem, fall detection and prevention fields receive a lot of intention over ...

Background: Fall detection is of great significance in safeguarding human health. By monitoring the motion data, a fall detection system (FDS) can detect a fall accident. Recently, wearable ...

Algorithm for Learning and Evaluation of Risks in Tumbles (ALERT) is a machine learning project dedicated to enhancing fall detection and prevention strategies. Utilizing advanced algorithms, ALERT ...

We get practical insights into the complexities of machine learning applications, which support the enhanced effectiveness of predictive models in disaster preparedness. The paper not only explains ...