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The Internet of Things (IoT) is an interconnected network of physical objects, software, and hardware. IoT- based solutions are becoming increasingly critical to solving these concerns elderly who live alone, limited healthcare resources, and rising medical expenses. The goal of this literature review evaluation was to determine the most common IoT applications in healthcare. Fifty relevant research publications were evaluated and assessed between 2013 and 2021. The most applied fields of IoT in healthcare coverage according to this study were both home health care and outdoor. Most of the studies evaluated have used cloud-based architecture since it provides a lot of flexibility and scalability. In many IoT models, communication technology, for example, Bluetooth, Wi-Fi, ZigBee, and Long-Range Wireless Area Network (LoRaWAN) have been widely deployed. The IoT has enabled the sharing of information, the reduction of hospital stays, and the reduction of healthcare expenses. [ABSTRACT FROM AUTHOR]

The rapid advancement of Network modernization within recent years has bolstered alliances of numerous intelligent things with sensing devices and established continuous data exchange amongst systems. Hence it requires cloud computing and fog computing for data storage and analysis. One of the applications in IoT is E-health services that pay attention to industry, research community and the societal zone. In the therapeutic industry, IoT and distributed systems are improving enduring privacy, personnel fulfillment, and operational effectiveness. This assessment aims to deconstruct most contemporary IoT elements, solutions, and industry dynamics in healthcare care, as well as examine state of IoT and decentralized virtualization health care implementations from 2015. We also look upon how promising innovations like edge computing, ambient elder care, data science, and wearables are used in in the healthcare industry, and also distinct IoT, e-health, and e-wellness guidance and agreements from around the globe in seeing how those who contribute to the connectivity and computational resources in the healthcare system. [ABSTRACT FROM AUTHOR]

The stock market is fundamentally nonlinear, and Stock market analysis has become one of the most important areas of research in recent years. People are interested to invest in the company stocks in the hopes of making a profit. People who want to forecast stock market prices look for strategies and resources that can raise their income while lowering their risks. In the stock market, which is a complex and difficult operation, prediction plays a critical role. Traditional approaches such as fundamental and technical analysis cannot guarantee the prediction's accuracy. Our strategy is to use the ARIMA (Autoregressive Integrated Moving Average) model to company stock price prediction. [ABSTRACT FROM AUTHOR]