Jayanth, Dharavath creator Sarawut Ninsawat Chairperson Tripathi, Nitin Kumar Co-chairperson Virdis, Salvatore G.P. Examination Committee Sanit Arunplod Examination Committee AIT Fellowship Scholarship Donor text series theses th Pathum Thani, Thailand Asian Institute of Technology 2025 continuing eng

print

134 leaves : ill.+ 1 online resource As global populations age at an accelerating rate, healthcare systems face increasing pressure to deliver accessible, efficient, and timely care to elderly individuals. Traditional caregiving models, often reliant on a younger workforce, are becoming increasingly unsustainable due to demographic shifts and resource limitations, resulting in delayed interventions, reduced in home support, and slower emergency responses. This research presents the Intelligent Geriatric Care Management System a real-time AI-powered platform that integrates simulated IoMT sensor data with advanced analytics to support proactive, continuous health management. The system continuously collects vital signs including heart rate, blood pressure, and SpO₂ from sensor-based streams, processes them for anomaly detection, and applies predictive assessment to identify early indicators of potential health deterioration. Its architecture combines a conversational AI assistant, powered by OpenAI{u2019}s GPT and Anthropic{u2019}s Claude, for personalized health interpretation; a real-time alert mechanism that issues voice prompts and escalates to emergency email notifications when abnormal readings are detected; and a monthly reporting module that generates AI-enhanced summaries and visual trend charts for long-term health tracking. By uniting continuous sensor-based monitoring with adaptive AI-driven interaction, I-GCMS delivers a scalable, automated, and personalized solution that bridges the gap between routine health tracking and timely intervention. This integration not only enhances safety and awareness for elderly users but also demonstrates how emerging AI and IoMT technologies can work together to strengthen preventive healthcare models in real-world community and home settings. A research submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Remote Sensing and Geographic Information Systems Research Studies Project Report (M.Eng.) - Asian Institute of Technology, 2025 Artificial intelligence Medical applications Medical care Asian Institute of Technology. http://203.159.5.9/ait-thesis/detail.php?q=B24012 http://203.159.5.9/ait-thesis/detail.php?q=B24012 260427 20260817162000.0