AI-BASED DESIGN AND ANALYSIS OF SECURE SMART TELEMEDICINE PLATFORM WITH REMOTE MONITORING CROSS-BORDER COMPLIANCE

Abstract

Imagine a patient 200km away from the nearest cardiologist. An unexpected surge in his or her blood pressure or irregular heartbeats is only noticed once symptoms are severe enough to require a visit to the emergency room—by then, proactive choices have been reduced. This occurs millions of times every day, both across developing and developed countries. We demonstrate a solution within this context, a functional telemedicine platform that incorporates three interlocking parts. First, secure communication between patient and specialist is possible via video and message transmissions, so travel is no longer a hindrance. Additionally, sensors continuously record critical patient data between appointments, tracking heart rate, blood pressure, and oxygen saturation levels, resulting in a dynamic instead of static documentation system. Third, these data are automatically reviewed to meet regional legal standards, regardless of the patient being within the US, EU, India, or other countries. Machine learning integration allowed us to detect patterns indicative of human error: slowly reducing oxygen levels, peculiar relations between stress levels and heart patterns, and warning signs of deterioration. Our platform has been thoroughly tested under realistic conditions and heavy loads of simulated patient data. Results have been gratifying, proving that warning alerts are forwarded to medical staff within times significant enough to make a difference that data remains secure and under protective custody, and that it can handle multiple connections concurrently and safely. Most significantly, this setup allowed in-area patients access to constant expert care with no need to leave their homes.