ASAP: Assistant System for Alzheimer's Patients

Alzheimer's patients who emphasize improving their quality of life and reducing the workload on carers. This paper proposes an Alzheimer's partner framework that utilizes confront discovery to recognize family individuals and remind patients of vital assignments through voice messages. The framework moreover incorporates live checking through message passing, where the content message is changed over to voice and patients get the message through an earpiece. The proposed framework is outlined to address the challenges confronted by Alzheimer's patients, such as memory misfortune, trouble in recognizing family individuals, and communication barriers. It almost has calm and direct patients as its focal point. The primary goal of the paper is to use the Haar cascade classifier to determine if the individual in front of you is a family member or not. The system's design, together with a web application is used for live message passing. To determine the viability and use of the system, a client survey is taken. These factors show how the suggested framework has a remarkable potential to improve the lives of Alzheimer's patients and their carers. The system's capacity to distinguish family individuals and remind patients of imperative assignments through voice messages, as well as its live checking capabilities through message passing, makes it an important apparatus for tending to the challenges of caring for Alzheimer's patients. Overall, the suggested collaborative framework appears to be a promising step towards improving the support and care of Alzheimer's patients and adds to the growing body of research on the use of innovation to address the problems associated with this infection.