Abstract
The disease that often affects the lung by blocking the airways is known as Chronic Obstructive Pulmonary Disease (COPD). There are several cause of COPD disease and especially smoking behaviour is the major cause of chronic illness. Howeover, offering treatment for COPD patients is a challengeable task, because the symptoms and actions are not similar for all patients. To diminish this problem, the technology called Internet of Things (IoT) is been introduced to monitor the patients and submit the report with a wide range of exactness rates. Furthermore, IoT is designed with different sensor hubs to sense the patient’s body condition with high accuracy. Thus, identification of the disease severity rate is possible by monitoring several biological parameters using different processes and sensors. Analysis of parameters are performed using an efficient Machine Learning (ML) or Deep Learning (DL) approach in a suitable platform. By, using IoT technology, anybody from anywhere can able to access the medical specialist suggestion based on their body conditions. The current review article has aimed to present the uses of IoT in COPD patient monitoring in different ways as well as the function of different models are compared in the form of graphs. Keywords: Biological Parameters, Chronic Diseases, Internet of Things, Sensors, Severity Prediction
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