Announcements & Events

Despite the significant potential of AI-enabled edge computing in smart healthcare systems, several challenges remain critical, particularly in real-time patient monitoring environments where latency, reliability, data accuracy, and continuous connectivity are essential. Conventional cloud-centered healthcare architectures may introduce delays because patient data must be transmitted to remote servers before analysis and decision-making. In critical healthcare scenarios, even a small delay can affect the effectiveness of monitoring and early warning systems. Therefore, this thesis proposes an AI-enabled edge computing architecture that processes healthcare data closer to the source using edge devices such as ESP32, Raspberry Pi, and an Edge PC. The system collects physiological and environmental data, applies local preprocessing and AI-based classification, and transmits structured data through an MQTT-based communication framework to a real-time dashboard. This approach improves response time, reduces dependency on remote cloud processing, supports scalable monitoring, and enhances the practical deployment of smart healthcare systems.

We cordially invite all faculty members and students to attend this important event. The defense will take place on Thursday, April. 30, 2026, at 09:30 AM. in room 3-1-012 at the College of Engineering, University City of Fara’a. Your presence and participation will not only support Khalid Saad but also foster engaging academic discussion.

We look forward to seeing you there!