A smart ontology-based IoT framework for remote patient monitoring

The Internet of Things (IoT) is the most promising technology in health technology systems. IoT-based systems ensure continuous monitoring in indoor and outdoor settings. Remote monitoring has revolutionized healthcare by connecting remote and hard-to-reach regions. Specifically, during this COVID-19 pandemic, it is imperative to have a remote monitoring system to assess patients remotely and curb its spread prematurely. This paper proposes a framework that provides the updated information of the Corona Patients in the vicinity and thus provides identifiable data for remote monitoring of locality cohorts. The proposed model is IoT-based remote access and an alarm-enabled bio wearable sensor system for early detection of COVID-19 based on ontology method using sensory 1D Biomedical Signals such as ECG, PPG, temperature, and accelerometer. The proposed ontology-based remote monitoring system analyzes the challenges of encompassing security and privacy issues. The proposed model is also simulated using cooza simulator. During the simulation, it is observed that the proposed model achieves an accuracy of 96.33 %, which establishes the efficacy of the proposed model. The effectiveness of the proposed model is also strengthened by efficient power consumption.