Hayat El Asri

Papers

Total Citations

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About

Hayat El Asri is a researcher at the intersection of robotics, artificial intelligence, and assistive technologies for aging populations. Her primary research focuses on developing autonomous systems that enhance elder care, with particular emphasis on fall detection and response mechanisms. Her most cited work, "Mobile Robot Detecting Elderly Falls: Representing Aesthetic Technologies, Theory, Software, and Hardware" (2018), introduces an innovative autonomous surveillance mobile robot that leverages Convolutional Neural Networks to detect falls in older adults and immediately alert caretakers. This contribution addresses a critical challenge in geriatric care—timely fall response—by combining aesthetic design with robust software and hardware integration. Though her citation count currently stands at 4, the work represents an early and important step toward practical, AI-driven elder care solutions. El Asri’s research bridges robotics, computer vision, and human-centered design, offering a glimpse into how autonomous systems can support independent living for the elderly. Her work is particularly relevant for students and researchers exploring the ethical and technical dimensions of assistive robotics in healthcare.