Titlebook: Big Data Platforms and Applications; Case Studies, Method Florin Pop,Gabriel Neagu Book 2021 Springer Nature Switzerland AG 2021 Big Data P

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Cloud-Based mHealth Streaming IoT Processing,nvironment. A lot of challenges are met to realize such a system, and this paper presents an overview of architectural approaches and organizational methods to realize a cloud-based mHealth IoT application that will cope with the Big data concept of incoming data streams with high velocity and volume.

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Cloud-Enabled Modeling of Sensor Networks in Educational Settings,educational solution, a virtual machine is associated with each student who works to accomplish a task for a given laboratory class, or during the entire semester. The provisioning process and experimental results for several test scenarios are also described.

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https://doi.org/10.1007/978-3-0348-9286-5n. Moreover, we describe our complete solution for such a system, implemented on Somes River, that includes data acquisition implemented using WSNs, standard-compliant data storage, data provision services, and automatic assessment of water quality.

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Undergraduate Texts in Mathematicsirculates. Since the device determines in real time the degree of agglomeration in the streets, such data may also be sent to the cloud for further analysis. This helps analyze traffic on public streets.

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Introduction to Combinatorial Optimizationpose methods and techniques for reducing the data without losing important information in order to produce sets of data that can be easily processed in real time. Furthermore, the deriving data are visualized so as to present that data reduction does not affect the visualized data which is a very common application of AIS data.

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Data Center for Smart Cities: Energy and Sustainability Issue,interconnected systems. These processing demands have led to a tremendous increase in DC power consumption. Therefore, the concepts of DC energy efficiency and sustainability represent future challenges in smart cities. While assessment of DC energy efficiency with a set of globally recognized metri

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Apache Spark for Digitalization, Analysis and Optimization of Discrete Manufacturing Processes, that monitor the manufacturing processes are characterized by noise, missing values, many features due to the fact that the assembly processes involve many different assembly steps and often the resources that are used in the manufacturing processes are applied inefficiently. Digitalization of asse