SMART ASSISTANT SYSTEM FOR ALZHEIMER'S PERSON

Computer Engineering

Alzheimer's disease (AD) presents significant challenges for both patients and caregivers. This paper proposes a smart assistant system designed to improve patient safety, independence, and quality of life. The system leverages machine learning algorithms and a user-friendly mobile application. Machine learning techniques such as LSTM (Long Short-Term Memory), SVM (Support Vector Machine), Logistic Regression, Random Forest, and others are employed for various functionalities. Real-time location tracking and geofencing utilize sensor data to ensure patient safety and prevent wandering. Personalized reminders and schedule management support medication adherence and daily routines. Anomaly detection based on activity patterns can identify potential dangers or health risks. The application is developed using Flutter, a cross-platform framework, for a user-friendly interface accessible to both patients and caregivers. Firebase serves as the backend, providing secure data storage (including medical records, anonymized if applicable) and real-time functionalities for functionalities like alerts and notifications. This project outlines the system design, explores the potential benefits for patients and caregivers, and discusses the ethical considerations involved in developing such a technology. The project aims to contribute to advancements in AD care by offering a technological solution that empowers patients and eases caregiver burdens.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.