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kumar embedded devices internet things technologies apps 2025

Type:: E-books
Files:: 2
Size:: 17.9 MB
Uploaded On:: July 22, 2024, 7:41 a.m.
Added By:: andryold1
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Info Hash:: 9288AF4EF6A1C64FBBA446148F8C243BF6155799

Textbook in PDF format The text comprehensively discusses machine-to-machine communication in real-time, low-power system design and estimation using field programmable gate arrays, PID, hardware, accelerators, and software integration for service applications. It further covers the recent advances in embedded computing and IoT for healthcare systems. The text explains the use of low-power devices such as microcontrollers in executing deep neural networks, and other machine learning techniques. Field programmable gate arrays (FPGAs) are programmable devices that are utilized by end users to create digital circuits. Configurable logic blocks (CLBs), also known as FPGA building blocks, are arranged in a two-dimensional array and linked to one another via a routing network. The communication-oriented structure supporting multiple resources and their networks on a single chip is known as NoC communication architecture. The NoC offers a solution that enables the resources to function independently as building blocks and as components of a specific network. Reconfigurable computing is an architecture that arranges highly flexible computing hardware and software components on processing platforms like FPGAs. After production, they are reprogrammed to a particular application based on their functional requirements. This distinguishing feature of FPGAs sets them apart from ASICs, which are created specifically for a given purpose or application. The capacity of FPGAs to upgrade or reuse hardware designs after implementation. FPGAs provide several benefits over ASICs or full-custom designs, including lower silicon chip costs, improved performance, and low power consumption. This book: Discusses the embedded system software and hardware methodologies for system-on-chip and FPGA. Illustrates low-power embedded applications, AI-based system design, PID control design, and CNN hardware design. Highlights the integration of advanced 5G communication technologies with embedded systems. Explains weather prediction modeling, embedded machine learning, and RTOS. Highlights the significance of machine-learning techniques on the Internet of Things (IoT), real-time embedded system design, communication, and healthcare applications, and provides insights on IoT applications in education, fault attacks, security concerns, AI integration, banking, blockchain, intelligent tutoring systems, and smart technologies. It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, and computer engineering

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Kumar A. Embedded Devices and Internet of Things. Technologies, and Apps 2025.pdf 17.9 MB

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kumar embedded devices internet things technologies apps 2025