Integrated Machine Learning Approach for Healthcare Disabilities Tracing and Detection

Abstract

The convergence of internet of things (IoT) technology and machine learning has paved the way for innovative solutions in the healthcare domain. This chapter presents an integrated approach that leverages IoT devices and advanced machine learning techniques to trace and detect healthcare-related disabilities. By continuously monitoring physiological signals and activity patterns, the proposed system enables early intervention and personalized care. The authors outline the key components of this approach, including data collection from IoT devices, data preprocessing, feature extraction, and the application of machine learning algorithms. Furthermore, ethical and privacy considerations are discussed, along with the potential benefits and challenges of deploying such a system. This chapter sheds light on the potential of IoT and machine learning to revolutionize healthcare by providing proactive and data-driven solutions for disabilities tracing and detection.