Sustainable AI-Driven IoT Health Monitoring System with Hybrid Solar-Wind Energy for Proactive Care

Evolving surroundings presents a difficulty for continuous real-time bio sign monitoring in chronic care patients located in rural and remote areas, providing in-hospital facility ICU models. Conventional healthcare systems rely on infrequent check-ups and symptomatic emergency treatment, resulting in delayed management and unnecessary morbidities, a medical error, and otherwise avoidable complications. Furthermore, the unpredictability of energy sources in off-grid places reduces the performance and accessibility of these solutions. Therefore, we introduce an AI-Driven IoT Health Monitoring System, which utilizes a hybrid solar-wind energy arrangement in a large healthcare facility in rural areas. The system uses Body Sensor Networks (BSNs) to collect biometric data, such as heart rate, ECG, temperature, and motion, via wearable sensors. These data are processed with 90% accuracy by advanced AI algorithms such as XG-Boost, which detect irregularities and send real-time alerts to caregivers. This use of renewable energy reduces management operational expenses while ensuring performance reliability in remote places. It is modular in design, which allows for scalability applicable to both individual residences and large healthcare facilities. Merging AI, IoT, and renewable energy into one unique solution changes healthcare from a reactive to a proactive management system to improve patient outcomes, reduce costs, and ensure sustainability.