Communications Integration of 5G-WSN Towards Environment Monitoring Based on Deep Learning Techniques.
DOI:
https://doi.org/10.31185/wjes.Vol14.Iss2.845Keywords:
Deep learning, Internet of Things (IoT), health monitoring, WSN, cloud serverAbstract
Healthcare monitoring-based systems are experiencing a surge in conventional methods with the integration of cutting-edge technologies such as the Internet of Things (IoT) and deep learning. This paper suggests a Wireless Sensor Network (WSN) with IoT architecture to monitor patients in real-time using the 5G networks. The system can effectively process the data that the wearable sensors capture regarding the heart rate, blood pressure, oxygen levels, and body temperature, and use deep learning models such as CNN-LSTM to process that data and convey the results to the user. It is created to update patients, especially the elderly, about their health promptly and to be able to contact healthcare providers remotely. The experimental results show that the system is effective as the accuracy of the system reaches 0.988% with a Maximum relative error of “heart rate” (2.19), “body temperature” (3.06), “systolic blood pressure” (3.3), “diastolic blood pressure” (3.4), and “SpO2” (1.03). The solution enhances access and offers a strong health monitoring system that is real-time and supports timely intervention and better patient care, particularly in remote locations.
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