MIAN MUHAMMAD YASIR2025-10-282025-10-282022https://escholar.umt.edu.pk/handle/123456789/9636Many industries, from manufacturing and commerce to law enforcement and healthcare, can benefit from the IOT applications and smart sensors. These Internet of Things based appliances and sensors generate a wealth of information that, if studied using big data analytics, might prove extremely useful to healthcare providers. Human health, life, and productivity are under danger due to the current new coronavirus pandemic (COVID-19) epidemic. The pandemic was successfully countered with the use of Internet of Things and big data technology. Methods that may be used to achieve this goal include speedy data gathering, the imagining of epidemic data, the interruption of wide spread risk, the following of complete cases, and the monitoring of preventative levels for COVID-19. In this study, the authors analyse and forecast COVID-19 inside a health monitoring system. The framework makes use of big data analytics and the IoT. With the help of big data branches, we achieve evocative, analytical, prognostic, and inflexible analyses of a novel illness data set that focuses on an extensive assortment of pandemic symptoms. The fundamental contribution of our work is participating giant data and Internet of Things to assess and forecast a rare disease. The deep learning & machine learning models may be used to identify and forecast the epidemic, which would be helpful to medical staff. Pandemic predictions are made using a range of ML methods. Additionally, GNB excels in comparison to other solutions, as seen by its accuracy rate of 81.5%.enThesis