Master’s Thesis Implements AI-Based Pandemic Patient Monitoring System

Heba Mahdi Falehi presented her thesis, “Design and Implementation of Monitoring System for Pandemic Patients Using Artificial Intelligence.” The research proposed a five-phase system to monitor patient vitals and environmental variables using sensors, AI algorithms like Convolutional Neural Networks (CNN), and Fuzzy Logic Controllers (FLC).
The system achieved a classification accuracy of 94.49% for CNN training, 92.79% for CNN testing, and 99.8% for FLC. It featured real-time alerts and a maximum delay of 15 seconds.
The committee included:

• Prof. Mithaq Nema Rahima (Chair)
• Dr. Sabah Abdul Hassan Katafa
• Dr. Alaa Mohammed Dawood
• Dr. Hussein Kareem Khalaf (Supervisor and Member).