Improving Elder Care
A. Anitha, N. Nandhini, Balakrishnan Kamaraj, Thinagaran Perumal · 2024
The proposed framework combines sensors connected to wearables such as an accelerometer, ultrasonic, and vision sensor to propose a unique method of detecting falls in the elderly. By combining the advantages of these sensors, the framework seeks to improve fall detection accuracy as well as reliability. A thorough examination of wearables, highlighting their critical role in improving fall detection systems. From an extensive investigation of image and video processing methods to the intelligent arrangement of sensors, by creating durable and efficient wearable technology. It also explores the combination of artificial intelligence and machine learning, demonstrating their innovative effects on timely warning production and continuous monitoring. An active and user-focused method of fall reduction is ensured by constant real-time tracking and adaptation to various circumstances. The framework also establishes the foundation for possible future integration with various additional sensors, thus advancing the development of elderly people’s health tracking systems.