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    1. Data och IT
    2. Informationsteknik: allmänt

    Industrial Internet of Things and Advanced Techniques for Sensor Data Aggregation and Fusion

    AvKanak Kalita,S. Vishnu Kumar

    Inbunden, Engelska, 2026

    346 kr

    Beställningsvara. Skickas inom 3-6 vardagar. Fri frakt över 249 kr.

    Beskrivning

    Master the complexity of modern networks with this essential guide, which provides the state-of-the-art AI and machine learning techniques needed to execute seamless sensor data fusion and energy-efficient aggregation across Industrial IoT and smart city environments. The use of artificial intelligence and machine learning techniques for data aggregation and fusion is becoming increasingly important, as these technologies can help extract important features and knowledge from data. Sensor data aggregation and fusion are essential components of IoT and Industrial IoT systems, as they enable the combination of data from multiple sources to provide a more comprehensive view of the system being monitored. This book is a comprehensive guide to the state-of-the-art techniques and methods used for sensor data aggregation and fusion in IoT and Industrial IoT environments, covering the fundamental principles of data aggregation and fusion, as well as the latest advancements and applications in the field. The book takes a practical approach to the subject matter, providing a deeper understanding of the challenges and opportunities associated with sensor data aggregation and fusion in IoT and Industrial IoT environments. It covers topics such as machine learning-based data aggregation, intelligent multi-sensor fusion, data aggregation and fusion in smart cities, and energy-efficient data aggregation and fusion. Written by leading experts in the field, the book will provide a comprehensive overview of the latest advancements in sensor data aggregation and fusion in IoT and Industrial IoT environments.

    Produktinformation

    • Utgivningsdatum:2026-03-09
    • Mått:159 x 237 x 29 mm
    • Vikt:812 g
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:432
    • Förlag:John Wiley & Sons Inc
    • ISBN:9781394275489

    Utforska kategorier

    • Informationsteknik: allmänt inom Data och IT

    Mer om författaren

    Kanak Kalita, PhD is an accomplished professor and researcher in the field of Computational Engineering with more than ten years of experience. He has published more than 190 articles and five edited book volumes. His research interests include machine learning, fuzzy decision making, metamodeling, process optimization, the finite element method, and composites. S. Vishnu Kumar, PhD is an Assistant Professor in the Department of Electronics and Communication Engineering at the Vel Tech Rangarajan Dr. Sagunthala Research and Development Institute of Science and Technology. He has proven his expertise through publication and industrial consultancy projects, including the publication of five scientific research articles, two book chapters, and six research papers presented at international conferences. His research areas include embedded machine learning, Internet of Things, networking, and embedded system design. M. Niranjanamurthy, PhD is an Assistant Professor in the Department of Artificial Intelligence and Machine Learning at the Bhusanayana Mukundadas Sreenivasaiah Institute of Technology and Management. He has published 25 books and 95 articles in various national and international conferences and journals and filed 30 patents, six of which were granted. His areas of interest are data science, machine learning, e-commerce, and m-commerce.

    Innehållsförteckning

    • Preface xviiPart I: Foundations and Frameworks in IoT and Data Aggregation 11 Enhancing Privacy and Efficiency in IoT‑Enabled Business Information Analytics and Blockchain‑Based Contingency 3P. Kumaresan and R. Ramprashath2 Supporting Authorized Duplicate Check in Hybrid Cloud Architecture Using IoT 17Balaji B. and Ram Prashath3 Design and Analysis of Multiband Microstrip Patch Antenna for IoT Applications 31R. Ramasamy, Arunachala Perumal C., Bharathi C. Ramachandra, Srikusan A. and Vijayan S.4 Simulation and Implementation of Advanced Adder and Hybrid Multiplier for FIR Filter 47V. Magesh, T. Solai Mithelesh, S. Ponmaniselvan and P. Praveen Kumar5 Comparison of the Design and Implementation of Smartphone Charging Controllers Using Arduino Mega and Raspberry Pi 61Yuvaraj D. and N. P. G. Bhavani6 Enhancing the Accuracy in Designing an Image with Style Transfer Learning Method Using Visual Geometry Group (VGG16) over InceptionV3 73Boobathy A. and Rashmita KhilarPart II: IoT in Smart Cities and Infrastructure 837 Efficient Traffic Detection and Localization in 5G Networks Using IoT‑Enhanced Dynamic Ad-Hoc Clusters 85Nirmalkumar K. and Ramprashath R.8 RFID‑Based Smart Parking Management System Using IoT 99Anil Kumar C. S., Shailendra Kumar Mishra, Ali Baig Mohammad and Vishnu Kumar. S.9 IoT‑Based Animal Watch Safety Using Green Technology with Deep Learning Approach 113Vineet Saxena, Prashant Dhage, Ghouse Basha M. A., Trupti Patil, Mritunjay Rai and Vishal Sharma10 Detection of Barcode for Automatic Fastai and EDA Considering Big Data for Green Cities 139Santosh S. Chowhan, Vivek Veeraiah, Sukhvinder Singh Dari, Sovers Singh Bisht, Rohit Anand, Ritu Shree and M. Niranjanamurthy11 Number Plate Detection to Automatic Ticket Repeat Offenders in Traffic Violation Using Green Technology 163Anishkumar Dhablia, Bharti Sharma, Alka Singh, Jayaprakash B., Rajendra P. Pandey and Adapa Gopi12 IoT‑Based Object Detection in Green Cities by Making Use of Data Center Based on YOLOv3 Model 189Jayant S. Rohankar, Shaziya Islam, Priyanka Chandani, Aditee Godbole, Neeraj Kumari and Dharmesh Dhabliya13 Facemask Detection for Passengers' Safety Using Green Technology by Fine Tuning on Object Detection Model in IoT 215Mohd. Asif Iqbal, Panduranga Rao M. V., Anisha Soni, Priyank Singhal, Ankur Gupta and Sharayu IkharPart III: Industrial Applications and Predictive Maintenance14 Enhancing Error Prediction in Machineries through CNN and Random Forest Models Using IoT with Sensor Data Fusion 243Thishan S. and Senthil Kumar K.15 Real‑Time Flight Delay Prediction with Live Data from IoT and Airline Operations Optimization Using the KNN Algorithm 259B. Praveen Kumar and R. Ramprashath16 Flight Delay Analysis Using XGBoost on Industrial Internet of Things and Advanced Techniques for Sensor Data Aggregation and Fusion 277Gayathri S., Venkata Veerendra Naveen Guthurthi, Varri Venkata Jyothi, Abirami R. and Priyadharshini S.17 An Analysis of the Traffic Loads in the Servers Using Thermal Images Utilizing Empirical Wavelet Transform with Dyadic Wavelet Transform 287Madhan Kumar Reddy and A. Selva Kumar18 Comparison of Discrete Wavelet Transforms and Stationary Wavelets for the Accurate Diagnosis of Server Issues Using Thermal Images 297Madhan Kumar Reddy and A. Selva KumarPart IV: Health, Safety, and Security Applications 30719 Diagnosis of Diseases Using Machine Learning 309Sujita Godishala, Vakalapudi Sumavi, M. Saravanan and P.S. Maya Gopal20 Client Attrition Prediction in Multiple Sectors with Customized Machine Learning Models Using IoT 319R. Balaji and R. Ramprashath21 Blood Transfusion System Using Data Mining Techniques and Grey Relational Analysis (GRA) Using Decision Tree Compared with Naive Bayes 335K. Manimaran and T. Poovizhi22 IoT‑Integrated Detection and Classification of Deepfake Images and Videos Using Custom Deep Learning Models 345K. Praveen Kumar and R. Ramprashath23 Reducing the False Rejection Using Novel Iris Recognition by Comparing with Elastic Bunch Graph Matching for Smartphones 359Kamalesh S. and V. Nagaraju24 Intelligent IoT‑Enabled Privacy‑Preserving Course Recommendation System: Leveraging NLP Chatbot and Federated Learning with Federated Linear Regression 371Dhivyaprabha G. and Ram Prashath R.25 Harnessing YOLO‑Powered Drones for Cloud‑Based Weed Density Mapping Focusing Agri 4.0 385S. Vishnu Kumar, G. Aloy Anuja Mary, B. Sathyasri, Murali Kalipindi and Chivon ChoeungReferences 399About the Editors 401Index 403