Secure and Responsive Human-Robot Interaction for Dementia Patients Using LSTM and IoT

Abstract

An innovative architecture that combines Long Short-Term Memory (LSTM) networks with Internet of Things (IoT) technology is presented in this paper to assist dementia patients. It solves Human-Robot Interaction (HRI) difficulties in dementia care. It also ensures security and responsiveness in HRI to establish a secure and trustworthy environment for dementia patients. LSTM networks help the robot to recognize and to adapt based on the dementia patients’ behaviors. Through real-time data gathering and exchange, IoT devices offer seamless and context-aware interactions. The system protects user privacy and sensitive data with strong encryption and authentication processes. The framework uses adaptive learning methods to improve the robot’s comprehension of the user’s preferences and needs, offering a personalized and responsive assistance system. Simulations and real-world situations show that the proposed technology provides safe, responsive, and personalized human-robot interactions for dementia care. By presenting a potential solution to dementia care difficulties it advances assistive technology and improves quality of life for dementia patients.