Smart Microcontrollers and FPGA Based Architectures for Advanced Computing and Signal Processing

M. Savitha, Dr. Raj Kumar Gupta

Indexed In: Google Scholar

Release Date: 26/06/2025 | Copyright:@2025 | Pages: 468

DOI: 10.71443/9789349552425

ISBN10: 9349552426 | ISBN13: 9789349552425

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Smart Microcontrollers and FPGA-Based Architectures for Advanced Computing and Signal Processing combine the versatility of programmable microcontrollers with the high-performance parallelism of FPGAs. This integration enables real-time data acquisition, complex signal analysis, and adaptive control in modern applications. These architectures are vital for edge computing, IoT devices, robotics, and high-speed communication systems. They support flexible reconfiguration, energy-efficient processing, and rapid prototyping of customized algorithms. By leveraging hardware-software co-design, engineers achieve enhanced computational speed, low latency, and optimized resource utilization. Such systems are increasingly pivotal in autonomous vehicles, industrial automation, biomedical devices, and next-generation embedded computing solutions.

Smart microcontrollers and FPGA-based architectures are transforming advanced computing and signal processing by delivering high-performance, energy-efficient solutions for complex applications. These technologies enable real-time data acquisition, parallel processing, and adaptive system reconfiguration, which are essential for modern embedded systems, IoT devices, and intelligent automation. Smart microcontrollers integrate sophisticated peripherals and low-power modes, while FPGAs offer customizable hardware acceleration for intensive algorithms, enhancing speed and precision. Together, they support cutting-edge applications in areas like wireless communication, biomedical instrumentation, automotive electronics, and industrial automation. Their flexibility and scalability make them vital components in the development of next-generation smart and connected systems.

Table Of Contents

Detailed Table Of Contents


Chapter 1

Design and Implementation of Low Power ARM Cortex Microcontrollers for Edge AI Computing

Shaik Maheboob, Shaik Lal John Basha

(Pages:34)

Chapter 2

FPGA Based Real Time Image Processing Architectures for Autonomous Navigation Systems

Jesmin Zakaria, L. Malathi

(Pages:34)

Chapter 3

Optimized Hardware Acceleration of Deep Learning Algorithms Using Xilinx Zynq SoCs

Saravanan D, S. Pragadeeswaran

(Pages:33)

Chapter 4

Reconfigurable Computing with FPGA for Adaptive Signal Processing in Communication Systems

V. Bhoopathy, Guntu Nooka Raju

(Pages:36)

Chapter 5

IoT Enabled Smart Sensing Systems Using RISC V Based Microcontrollers and Embedded AI

G. Kharmega Sundararaj, Geetha C Megharaj

(Pages:37)

Chapter 6

High Speed Digital Signal Processing Using VHDL and Verilog for Biomedical Applications

Parul Saxena, Muralidharan J

(Pages:38)

Chapter 7

FPGA Based Real Time ECG Signal Processing for Smart Health Monitoring Devices

A. Selin Vironicka, Muralidharan J

(Pages:32)

Chapter 8

Design and Simulation of Smart Microcontroller Based Control Systems for Industrial Automation

R. K. Parate, R. D. Wakodikar

(Pages:35)

Chapter 9

Energy Efficient Data Acquisition and Processing Architectures Using ARM Cortex M Series

Bramah Hazela, C. E. Rajaprabha

(Pages:34)

Chapter 10

Parallel Processing Frameworks on FPGA for High Throughput Neural Network Inference

R. Jegadeesan, A. Devi

(Pages:32)

Chapter 11

FPGA Implementations of Secure Cryptographic Algorithms for Embedded Systems

Debabrata Dansana, Rakesh K Kadu

(Pages:37)

Chapter 12

Smart Wearable Systems with Integrated Microcontroller Based Edge Intelligence

R. D. Wakodikar, R. K. Parate

(Pages:34)

Chapter 13

FPGA Based Wireless Sensor Network Gateway Architectures for Distributed Systems

Surbhi Khare, Mrudula M Gudadhe

(Pages:36)

Chapter 14

Design of Power Optimized Microcontroller Systems for Battery Operated Signal Processing Devices

Anand Kumar, M. Gayathri

(Pages:38)

Chapter 15

Smart Agriculture System Using Microcontroller Controlled Multi Sensor Data Fusion

Subhasish Halder, Maaz Allah Khan

(Pages:37)


Contributions


M. Savitha is an accomplished educator and administrator with over 15 years of multidisciplinary experience spanning academia, industry, and healthcare administration. She holds degrees in Engineering and Business Administration and is currently pursuing a Ph.D. in Hospital Management, focusing on AI integration in radiology. Her career includes teaching, technical roles in the electronics industry, and leadership positions in private and university administration. A gold medalist and university rank holder, she has published extensively in internationally indexed journals. Savitha’s expertise bridges technology and management, with interests in robotics, AI, embedded systems, and human resource development. Her unique blend of industrial and clinical experience drives her passion for innovation and operational excellence. M. Savitha, B.E., M.E., M.B.A., Ph.D. (Pursuing).

Dr. Raj Kumar Gupta is currently an Senior Assistant Professor, Sardar Vallabhbhai Patel College, Bhabhua, Constituent unit of Veer Kunwar Singh University, Ara, Bihar. He completed his Ph. D. from University of Delhi, Delhi.His area of interest is Material Science & Computing, IoT. He has 10 years of experience in teaching and research. He is a Life Member of STAMI. He has co-authored & published patent, copyright, also participated in national & international conferences like AICTE, ISTE approved-sponsored, IEEE and published research papers in renowned international journals including Scopus indexed. He has participated in AICTE, and university sponsored FDP & workshops including material Science, AI related studies. He has been worked as a Reviewer of research papers in conference. He has delivered Expert Talks various seminars.            

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