LoRaWAN-Based Artificial Intelligence Intensive Care Unit Framework for Tracking Patients With Severe Pneumonia

Artificial intelligence (AI) and computer vision has several potential applications in the intensive care unit (ICU). This letter presents an AI-powered long-range wide area network framework for monitoring ICU patients suffering from pneumonia. Strategies such as increasing the frequency of changing patient positions can be used to reduce the frequency of pneumonia. By accurately identifying and analyzing the movements and positions of a patient's body during an ICU stay, healthcare providers can develop more effective treatment plans that help patients recover more quickly and reduce complications. By detecting bad body posture, medical staff can better manage patients' head-of-bed elevation and sitting position levels; it can reduce the risk of infection, and promote earlier mobilization. Semifowler's position and high-fowler's position are advised for the pneumonia patients in this research. The proposed AI ICU framework is deployed in Raspberry Pi 4B computer and streamed to the Amazon Web Services (AWS) Internet of Things (IoT) cloud. It is an effective tool for reducing the effect of pneumonia in ICU patients, which can reduce readmission rates, lower healthcare costs, and improve patient outcomes.