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.

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.