ABSTRACT
With the advancement in technology and also with increasing demand of users in mobile communication, particularly during this pandemic situation, the data rate needed for the end users (customers) is in high demand. To cope with this demand in the data rate and technology innovations, the Internet of Things (IoT) provides a solution for this demand in the present and also in the future.
IoT by itself cannot provide the required data rate. Hence, IoT with the concept of data science or certain algorithms is needed to balance the demand in data rate. There are various traditional methods to serve the customers in the world with the allocated bandwidth and data rate but this method cannot manage the velocity and speed of transmission. Thus, a special algorithmic approach has been proposed for IoT services.
Data analytics depends on data with time series from IoT devices with additional techniques like deep learning, sensor fusion, and streaming. Deep learning is also considered as cameras are treated as sensors and also include many reinforcement neural networks for IoT devices. Ironically, due to the emphasis on data, the contents are concerned primarily with applying analytical learning algorithms on IoT datasets, and the dataset is personalized.
In data science, research is static and limited. The data obtained cannot be updated, so the results obtained in the context of the preparation may not be usable. But, as IoT information is constantly being collected, research is supplemented by the latest market designs, making this research more important and smarter when it is routinely invested. Furthermore, as more and more layers of integrated or integrated with IoT, it is tricky to access and process a massive amount of information. So, really, data scientists upgrade their skills with the primary goal of understanding the information generated by the IoT. Because the amazing quality of the IoT develops the subsequent data flow, this is bound to change the way data science works for some time. The burst of information requires not only a better foundation, but also more sensible data scientists. Computer science for the Internet of Things can help overcome some far-reaching challenges and make better choices. The purpose of this chapter is to satisfy the reader and to provide an opportunity to define the effective use of data science as a safe path to data science as an opportunity for the Internet of Things in the coming era.
