Investigating on the Recent Synergies of IoT and Machine Learning for Proactive Healthcare

Abstract

This article explores how the Internet of Things (IoT) and Machine Learning (ML) may revolutionize healthcare management by shifting towards a proactive approach. The increase in IoT devices has allowed for the smooth incorporation of sensors and actuators into many healthcare applications, enabling the immediate collecting and monitoring of patient health data. Advancements in machine learning techniques have enabled healthcare systems to analyze large volumes of diverse data, allowing for tailored and preemptive responses. This study examines the synergistic connection between Internet of Things (IoT) and Machine Learning (ML) in healthcare management, emphasizing their joint ability to improve early illness identification, optimize treatment plans, and increase patient outcomes. The study explores the main obstacles and possibilities in using IoT and ML technologies for proactive healthcare management by thoroughly examining current research, case studies, and experimental results. It provides information on the design factors, integration difficulties, and ethical consequences of using IoT and ML technologies in actual healthcare environments. This article explores how the combination of IoT and ML may improve healthcare delivery by shifting it from reactive to proactive, leading to more efficient and enduring healthcare systems in the future