IOT and Machine Learning-Powered Framework for Enhanced Alzheimer's Disease Care and Risk Management

Alzheimer's disease poses numerous challenges for both patients and caregivers, especially with regard to patient safety and well-being. In response, this research presents a state-of-the-art Internet of Things-based monitoring system specifically tailored for Alzheimer's patients. By using facial recognition and GPS tracking, the system provides real-time updates on the patient's location and health status. By incorporating person identification features for both known and unknown people, caregivers can be alerted when a patient meets someone they don't know, which increases safety measures. Additionally, the system updates a subset of web servers every hour with the precise location and health indicators of the patient, ensuring timely support and intervention. By combining cutting-edge IoT features with cutting-edge monitoring techniques, this system provides a thorough and useful approach to Alzheimer's patient care, promoting increased safety, peace of mind, and successful management of the condition.