Monitoring devices and systems are indispensable tools for patients with cardiovascular health issues. These tools are typically operated by trained personnel in healthcare institutions. However, the need to monitor patients’ vital signs at home remains a significant challenge. To address this, we propose the design of a non-invasive, autonomous IoT (Internet of Things.) device capable of recording heart rate, blood oxygen levels, and body temperature. The proposed device integrates with monitoring and data control platforms using IoT protocols. For validation, the data collected by the proposed device was compared with that of a smartwatch using statistical methods based on mean, median, and mode determination. The prototype demonstrated results comparable to those of a smartwatch, with measurements of 77.49 bpm (heart rate), 98.79% ( \(S_p O_2\) ), and 37.37  \(^{\circ}\) C (body temperature). In contrast, the smartwatch recorded 75.38 bpm, 98%, and 37.4  \(^{\circ}\) C, respectively. The proposed predictive model serves as an analytical framework for the study variables, consisting of three layers that can be adapted to wearable monitoring devices with the proposed architecture. The model achieved an RMSE of 0.470 for blood oxygen, 5.769 for heart rate, and 1.534 for body temperature. The developed algorithm is intelligent enough to provide accurate predictions, helping to prevent major cardiovascular health complications in patients.