Volume 2 - Issue 2, March - April 2026

The increasing ageing population requires digital health systems that are safe, adaptive, and easy for older adults to use. However, many current health and fitness platforms emphasize isolated vital-sign monitoring or generic exercise delivery, with limited awareness of fatigue, emotion, long-term motivation, and ethical safety. This paper presents FitCare AI, an intelligent health and fitness monitoring system for senior citizens that integrates guided tutorials with multimodal artificial intelligence. The proposed system combines cognitive fatigue detection, emotion recognition, time-aware adaptation, psychological trend analysis, and ethical AI-based decision support within a senior-friendly web architecture. Real-time sensor data, interaction logs, and optional camera or voice inputs are processed to personalize exercise intensity, tutorial pacing, reminders, and safety recommendations. A prototype implementation using Python, TensorFlow, OpenCV, and Firebase demonstrates promising performance in responsiveness, usability, and adaptive support. FitCare AI offers a holistic framework for safe, explainable, and personalized healthy ageing.

N.Parameshwari, S.Aravind, M.Gowtham, E.Santhosh, C.Subash,"Fitcare AI: Development of An Intelligent Health and Fitness Monitoring System for Senior Citizens With Guided Tutorials" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(2): Page(1421-1426) Mar-Apr 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.