IoT (Internet of Things) devices and smart sensors are used in different life sectors, including industry, business, surveillance, healthcare, transportation, communication, and many others. These IoT devices and sensors produce tons of data that might be valued and beneficial for healthcare organizations if it becomes subject to analysis, which brings big data analytics into the picture. Recently, the novel coronavirus pandemic (COVID-19) outbreak is seriously threatening human health, life, production, social interactions, and international relations. In this situation, the IoT and big data technologies have played an essential role in fighting against the pandemic. The applications might include the rapid collection of big data, visualization of pandemic information, breakdown of the epidemic risk, tracking of confirmed cases, tracking of prevention levels, and adequate assessment of COVID-19 prevention and control. In this paper, we demonstrate a health monitoring framework for the analysis and prediction of COVID-19. The framework takes advantage of Big data analytics and IoT. We perform descriptive, diagnostic, predictive, and prescriptive analysis applying big data analytics using a novel disease real data set, focusing on different pandemic symptoms. This work's key contribution is integrating Big Data Analytics and IoT to analyze and predict a novel disease. The neural network-based model is designed to diagnose and predict the pandemic, which can facilitate medical staff. We predict pandemic using neural networks and also compare the results with other machine learning algorithms. The results reveal that the neural network performs comparatively better with an accuracy rate of 99%.

物联网（IoT）设备和智能传感器用于不同的生活领域，包括工业，商业，监视，医疗保健，运输，通信等。这些物联网设备和传感器产生大量数据，如果这些数据需要进行分析，可能会对医疗保健组织产生价值并从中受益，从而使大数据分析成为现实。最近，新型冠状病毒大流行（COVID-19）爆发正严重威胁着人类健康，生命，生产，社会互动和国际关系。在这种情况下，物联网和大数据技术在对抗大流行中发挥了至关重要的作用。这些应用程序可能包括大数据的快速收集，大流行信息的可视化，流行病的分解，已确诊病例的追踪，跟踪预防水平，并对COVID-19预防和控制进行充分评估。在本文中，我们演示了用于COVID-19的分析和预测的健康监控框架。该框架利用了大数据分析和物联网。我们使用大数据分析，使用新颖的疾病真实数据集进行描述性，诊断性，预测性和规范性分析，重点关注不同的大流行症状。这项工作的主要贡献是将大数据分析和物联网相集成，以分析和预测一种新型疾病。基于神经网络的模型旨在诊断和预测大流行，这可以为医务人员提供便利。我们使用神经网络预测大流行，并将结果与​​其他机器学习算法进行比较。