An approach based on IoT and machine learning for monitoring patients on healthcare centers - Bezerra, Thiago; Vinicius, Marcos; Ciane, Aline; Callou, Gustavo; França, Cleunio; Tavares, Eduardo (Anais do Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS), 2025)
Internet of Things (IoT) enables remote monitoring using existing networks, integrating diverse computing systems and communication protocols. This adaptability makes IoT applicable across domains, including healthcare. Hospitals leverage the Internet of Medical Things (IoMT) to collect and transmit patient data, enabling real-time diagnoses, operational efficiency, and personalized care. This paper presents a patient monitoring system for healthcare centers using IoMT and machine learning (ML). The system is capable of performing facial recognition of patients, identifying movement patterns associated with falls, using cameras, and sending alerts to caregivers or healthcare professionals. Results demonstrate the system’s feasibility in enhancing healthcare outcomes. The system achieved a precision of 95% for facial recognition and 97% for fall detection.