Sensor Networks and AI Integration in Health Monitoring Systems: A STEM Innovation
Palabras clave:
Sensor networks, artificial intelligence, health monitoring systems, wearable devices, wireless sensor networks, IoT in healthcare, machine learning, chronic disease management, biomedical engineering, digital health, predictive analyticsResumen
The integration of sensor networks and artificial intelligence (AI) has revolutionized the field of health monitoring systems, creating a dynamic intersection of biomedical engineering, computer science, and data analytics. This STEM innovation enables real-time, continuous, and non-invasive tracking of physiological parameters such as heart rate, blood pressure, glucose levels, and body temperature. Wireless sensor networks (WSNs), when embedded in wearable or implantable medical devices, collect patient data that AI algorithms analyze to detect anomalies, predict health events, and support medical decision-making. Machine learning models, particularly deep learning and support vector machines, are increasingly employed to classify health conditions and personalize patient care. These technologies significantly enhance chronic disease management, early diagnosis, and post-operative monitoring, reducing hospital visits and improving patient outcomes.
