Smart Embedded Systems
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Smart Embedded Systems: Advances and Applications

Smart Embedded Systems: Advances and Applications

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About the Book

"Smart Embedded Systems: Advances and Applications" is a comprehensive guide that demystifies the complex world of embedded technology. The book journeys through a wide range of topics from healthcare to energy management, autonomous robotics, and wireless communication, showcasing the transformative potential of intelligent embedded systems in these fields. This concise volume introduces readers to innovative techniques and their practical applications, offers a comparative analysis of wireless protocols, and provides efficient resource allocation strategies in IoT-based ecosystems. With real-world examples and in-depth case studies, it serves as an invaluable resource for students and professionals seeking to harness the power of embedded technology to shape our digital future. Salient Features: The book provides a comprehensive coverage of various aspects of smart embedded systems, exploring their design, implementation, optimization, and a range of applications. This is further enhanced by in-depth discussions on hardware and software optimizations aimed at improving overall system performance. A detailed examination of machine learning techniques specifically tailored for data analysis and prediction within embedded systems. This complements the exploration of cutting-edge research on the use of AI to enhance wireless communications. Real-world applications of these technologies are extensively discussed, with a focus on areas such as seizure detection, noise reduction, health monitoring, diabetic care, autonomous vehicles, and communication systems. This includes a deep-dive into different wireless protocols utilized for data transfer in IoT systems. This book highlights key IoT technologies and their myriad applications, extending from environmental data collection to health monitoring. This is underscored by case studies on the integration of AI and IoT in healthcare, spanning topics from anomaly detection to informed clinical decision-making. Also featured is a detailed evaluation and comparison of different system implementations and methodologies This book is an essential read for anyone interested in the field of embedded systems. Whether you're a student looking to broaden your knowledge base, researchers looking in-depth insights, or professionals planning to use this cutting-edge technology in real-world applications, this book offers a thorough grounding in the subject.

Table of Contents:
Chapter 1 A reconfigurable FPGA based epileptic seizures detection system with 144 µs detection time Swetha Annangi and Arun Kumar Sinha Chapter 2 Hardware architecture for denoising of EOG signal using differential evolution algorithm V. H. Prasad Reddy, Gundugonti Kishore Kumar and Puli Kishore Kumar Chapter 3 Implementation considerations for an intelligent embedded e-Health system and experimental results for EEG-based activity recognition Stefan Oniga, Iuliu Alexandru Pap and Tamas Majoros Chapter 4 Embedded and computational intelligence for diabetic healthcare: An overview Anupama Namburu Aravapalli Rama Satish Bhanu Teja Veeramachaneni, Sneha Edupuganti Kothamasu Venkata Naga Durga Sai Harshith Chapter 5 A semi-definite programming based design of a robust depth control for a submersible autonomous robot through state feedback control Vadapalli Siddhartha and Subhasish Mahapatra Chapter 6 Embedded system with in-memory compute neuromorphic accelerator for multiple applications Afroz Fatima and Abhijit Pethe Chapter 7 Artificial intelligence driven radio channel capacity in 5G, 6G wireless communication system in the presence of vegetation: Prospect and challenges Sachin Kumar, T. Senthil Siva Subramanian and Kapil Sharma Chapter 8 Smart cabin for office using embedded systems and sensors Anirban Dasgupta, Abhranil Das, parishmita Deka and Soham Das Chapter 9 Wireless protocols for swarm of sensors: Sigfox, Lorawan, and Nb-IoT Luiz Alberto Pasini Melek Chapter 10 Design and test of thermal energy harvester for self-powered autonomous electronic load Arun Kumar Sinha Chapter 11 Managing concept drift in IoT health data streams: A dynamic adaptive weighted ensemble approach M. Geetha Pratyusha and Arun Kumar Sinha Chapter 12 GraLSTM: A distributed learning model for efficient IoT resource allocation in healthcare M. Geetha Pratyusha and Arun Kumar Sinha


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Product Details
  • ISBN-13: 9781032404172
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: CRC Press
  • Height: 234 mm
  • No of Pages: 284
  • Weight: 648 gr
  • ISBN-10: 1032404175
  • Publisher Date: 01 Dec 2023
  • Binding: Hardback
  • Language: English
  • Sub Title: Advances and Applications
  • Width: 156 mm


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