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      1. Data och IT
      2. Hårdvara
      • Nyhet

      Intelligent Embedded Systems 1

      Applications in Automation, Autonomous Navigation, AI, IoT and Industrial Systems

      AvAbhishek Kumar,Priya Batta

      Inbunden, Engelska, 2026

      Del i serien ISTE Invoiced

      1 787 kr

      Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

      Beskrivning

      The rapid evolution of embedded technologies has transformed modern automation, intelligent devices and connected infrastructures.Intelligent Embedded Systems 1 provides a comprehensive introduction to the principles, architectures and real-world applications of intelligent embedded systems across diverse domains. This book explores the integration of artificial intelligence (AI), the Internet of Things (IoT), autonomous navigation, robotics, industrial automation, healthcare and smart manufacturing, highlighting how embedded intelligence enables efficient, reliable and adaptive systems. Through theoretical foundations, practical implementations and application-driven case studies, the book bridges the gap between academic concepts and industrial practice.Designed for undergraduate and postgraduate students, researchers, engineers and professionals, this book offers valuable insights into emerging technologies, while establishing the foundational knowledge required to develop next-generation intelligent embedded solutions.

      Produktinformation

      • Utgivningsdatum:2026-08-14
      • Format:Inbunden
      • Språk:Engelska
      • Serie:ISTE Invoiced
      • Antal sidor:336
      • Förlag:ISTE Ltd
      • ISBN:9781836690894

      Utforska kategorier

      • Hårdvara inom Data och IT
      • Artificiell intelligens inom Data och IT

      Mer om författaren

      Abhishek Kumar is a senior IEEE member and Professor at Chandigarh University, Mohali, India. His expertise spans AI, renewable energy and image processing.Priya Batta is an Associate Professor at Amity School of Engineering and Technology, Amity University Punjab, Mohali, India. Her research specializes in AI, blockchain and the IoT.S. Ravi is a Professor at Pondicherry University, India. His research focuses on multi-biometrics, medical imaging, computer vision and digital image processing.R. Mohan is an Associate Professor at NIT Tiruchirappalli, India. His research specializes in computer vision, cybersecurity, distributed systems, high performance computing, machine learning, and software engineering.

      Innehållsförteckning

      • Preface xvAbhishek KUMAR, Priya BATTA, S. RAVI and R. MOHANIntroduction xviiAbhishek KUMAR, Priya BATTA, S. RAVI and R. MOHANPart 1. Embedded Graph Intelligence and IoT Analytics 1Chapter 1. Topology-Aware Spectral Graph Learning for Unsupervised IoT Device Clustering and Anomaly Detection 3M. SHANMUGHAM, A. KAMESWARAN, M. PRAKASH, K. SIVAPRAKASH, C. NANDAGOPAL and M. ANITHAChapter 2. Graph Intelligence–Driven Deep Reinforcement Learning Framework for Adaptive Control and Predictive Maintenance of Coupled-Inductor DC–DC Converters in Hybrid Electric Vehicles 15Elankurisil S.A. and N. Dhivya DEVIChapter 3. Apache Kafka Streams and Time-Series ARIMA Modeling for IoT-Enabled SME Supply Chain Visibility 31Manam Vamsi KRISHNA, Bobbiti Jyothika REDDY, Bandaru RUCHITHA, Adla JAHNAVI, B. PAVITHRA and A. CHATHURYAChapter 4. Ensemble XGBoost and LSTM-Based Predictive Analytics for Real-Time Industry 4.0 Decision Support Systems 45Narendhar MULUGU, Fariha NAAZ, Chakilela SRIVIDHYA, B. ANJALI, Aduri SMILEY and Bommadeni Sanjana SRIChapter 5. Isolation Forests with Local Outlier Factor and Mahalanobis Distance for Real-Time Fraud Detection 61Lahari MEKALA, Kammalapally VARSHA, Kapuganti NIHARIKA, Karne NAMITHA, Kuchur AKSHARA and Mothewar SRIJAPart 2. Embedded AI Optimization and Learning Architectures 77Chapter 6. Optimized Variational Autoencoder–Reinforcement Learning Architectures for Autonomous IoT Resource Allocation and Load Balancing 79Iyappan MURUGESAN, S. PRAKASH, Maheswaran THANGASAMY, Kokilavani THANGARAJ, R. MUTHUKUMAR and Brindha G.Chapter 7. Proximal Gradient Methods and Federated Learning: Distributed Optimization for Edge Computing Environments 95Ch. Sandeep REDDY, Mallaiahgari KAMALINI, K. MOUNIKA, Lingam KAVYANJALI, M. DIVYA and Gundeboina SUSHMITHAChapter 8. Convex Relaxation with ADMM and Second-Order Cone Programming for Renewable Energy Microgrids 113D. Vemana CHARY, Bodi TEJASWINI, Dharavath SNEHA, Donda AKSHITHA, E. VYSHNAVI and D. SANJANAChapter 9. Deep Q-Networks with Prioritized Experience Replay for Autonomous Vehicle Decision-Making 127L. Srinivasa REDDY, Neha KASANAGOTTU, Maloth Sai VAISHNAVI, Mosali ASHRITHA, Kuntala SREEJA and K. TEJASWIChapter 10. Cold Start Optimization Techniques for Function-as-a-Service Using Lambda@Edge and Container Reuse 141S. SPANDANA, Singirikonda SAMHITHA, Suguru SIREESHA, Ramanolla ASHWITHA, Talasila HARSHITHA and Vaddadhi THANUSHAPart 3. Embedded Security, DevOps and Cyber-Physical Systems 157Chapter 11. Adversarial Deep Neural Networks for Intrusion Prevention in Heterogeneous IoT Ecosystems: A Robustness Analysis 159Jaikumar R., Ravikumar S., K. TAMILSELVI, Iyappan MURUGESAN, B. SUGANTHI and Brindha G.Chapter 12. Adaptive Threat-Aware Clustering for Enhanced Security in IoT-Enabled Smart Cities: A Machine Learning Enhanced Approach 171C. NANDINI and Priyadarsini K.Chapter 13. Graph Intelligence-Enabled Multi-Layered Framework for Revolutionizing Industrial Cyber-Physical System Security 187K. SELVI and Golda DILIPChapter 14. Intelligent DevOps Monitoring and Automated Incident Response using Anomaly Detection and Self-Healing Pipelines 201Amrutha Varshini MANNAVA, Kakumanu Venkata Sai Keerthi PRIYANKA, Vegesna Kumar Durga Abhirama RAJU, Penumala LAVENIA and B. Prameela RANIChapter 15. Multi-Cloud Load Balancing with Application Performance Monitoring (APM) and Chaos Engineering Practices 213Kammara Venkatarangaiah ACHARI, Oruganti NIKHILA, Nangunoori SRIJA, Nimmanagoti SARASWATHI, Mekala KAVYA and Sunkari MAMATHAPart 4. Embedded Communication, Edge and Cloud Integration 229Chapter 16. MQTT Protocol Stack Optimization with Edge–Fog–Cloud Hierarchical Architecture and CoAP Lightweight Alternatives for Graph-Based IoT Network Communication 231Vijayalakshmi CHINTAMANENI, Bathini VIGNANI, Gande SANNIHITHA, A. HAARIKA, B. HARSHITHA and G. PRIYANKAChapter 17. 5G Edge Computing with MEC and RAN Slicing for Ultra-Low Latency IoT Applications 249B. Vijaya DURGA, Sarampelly ANANYA, Thadisetty VAISHNAVI, V. Chandra KEERTHI, Vuppu SHRIYA and Mamidi GAYATHRIChapter 18. IoT-Based ESG Metrics Integration with Edge Computing and Cloud Orchestration: A Sustainable Digital Infrastructure Approach 265Narendhar MULUGU, Aramati Poojani REDDY, Adepu NEHA, Dodda MEGHANA, Bazar PRIYANSHU and Bommena Sri KEERTHANAList of Authors 279Index 289
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