Computer Vision-Assisted Smart ICU Framework for Optimized Patient Care

Computer vision (CV)-assisted emotion recognition and drowsiness detection technology in intensive care units (ICUs) can significantly decrease delirium and pulmonary diseases and improve patient results, particularly in respiratory ailments such as pneumonia. This research proposes a CV-assisted smart ICU framework for real-time patient monitoring via the Internet of Things (IoT). By detecting drowsiness, medical staff can better manage patients' sedation levels, reduce the risk of infection, and promote earlier mobilization, leading to better patient outcomes. Developing a smart ICU that can automatically detect patients' feelings is a significant step toward the early detection of melancholy and stress to initiate treatment. The proposed smart ICU framework is developed and deployed in NVIDIA Jetson Nano graphics processing unit computer. The processed data from the smart ICU camera are sent to the long range wide area network (LoRaWAN) server. The technology offers an efficient means for promptly diagnosing and treating patients with critical care and lung diseases in the ICU. The developed framework could assist healthcare practitioners in decreasing readmission rates and enhancing patient outcomes.