Fog Computing Assisted Anaesthesia Monitoring to Enhance Realtime Surgical Efficiency.

Anaesthesia plays a crucial role in modern surgical procedures, ensuring patient comfort and allowing surgeons to perform necessary interventions without interruptions. However, managing anaesthesia comes with significant challenges, such as avoiding underdosage or overdosage, which can lead to severe complications like intraoperative awareness or cardiovascular instability. This paper proposes a fog computing-based approach to improve real-time anaesthesia monitoring, leveraging IoT nodes armed with EEG tools for continuous updates on the patient's brain activity and eventually translating into anaesthetic depth. By strategically deploying fog nodes and offloading task distribution from IoT nodes to fog nodes as well as cloud services, the proposed system aims to reduce response time for performing complex computations on brain activity signals, thereby increasing the workflow efficiency of anesthesiologists. To achieve this, a dashboard using a web platform is developed to provide anesthesiologists with a comprehensive interface for real-time monitoring and control, which will help anesthetists predict anaesthetic depth and make informed decisions. By improving the accuracy and timeliness of anaesthesia management, the proposed approach not only enhances patient safety but also optimises the operational efficiency of surgical procedures.