03470nas a2200373 a 4500 20260817162000.0 260427s20259999th u ms tm 000 eng d .b12500914 AIT RSPR no.RS-25-01 Jayanth, Dharavath AI-based geriatric care management system for achieving smart health Pathum Thani, Thailand : Asian Institute of Technology, 2025 134 leaves : ill.+ 1 online resource Research studies project report ; no. RS-25-01 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 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. Artificial intelligence Medical applications Medical care Sarawut Ninsawat, Chairperson Tripathi, Nitin Kumar, Co-chairperson Virdis, Salvatore G.P., Examination Committee Sanit Arunplod, Examination Committee AIT Fellowship, Scholarship Donor Asian Institute of Technology. Research studies project report ; no. RS-25-01 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B24012 .b12500914 mnarc a 260430 0 260429 m h a 0 mnarc 67 Barcode : - CREATED : 2026-04-27 RECORD # : i13597851 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 3382 3382 0 0 0 0 MAIN MAIN mnarc 2026-08-17 0 AIT RSPR no.RS-25-01 2026-08-17 16:20:00 1 2026-08-17 67