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.
Preface xvii
Part I: Foundations and Frameworks in IoT and Data Aggregation 1
1 Enhancing Privacy and Efficiency in IoTEnabled Business Information
Analytics and BlockchainBased Contingency 3
P. Kumaresan and R. Ramprashath
2 Supporting Authorized Duplicate Check in Hybrid Cloud Architecture Using
IoT 17
Balaji B. and Ram Prashath
3 Design and Analysis of Multiband Microstrip Patch Antenna for IoT
Applications 31
R. 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 47
V. Magesh, T. Solai Mithelesh, S. Ponmaniselvan and P. Praveen Kumar
5 Comparison of the Design and Implementation of Smartphone Charging
Controllers Using Arduino Mega and Raspberry Pi 61
Yuvaraj D. and N. P. G. Bhavani
6 Enhancing the Accuracy in Designing an Image with Style Transfer Learning
Method Using Visual Geometry Group (VGG16) over InceptionV3 73
Boobathy A. and Rashmita Khilar
Part II: IoT in Smart Cities and Infrastructure 83
7 Efficient Traffic Detection and Localization in 5G Networks Using
IoTEnhanced Dynamic Ad-Hoc Clusters 85
Nirmalkumar K. and Ramprashath R.
8 RFIDBased Smart Parking Management System Using IoT 99
Anil Kumar C. S., Shailendra Kumar Mishra, Ali Baig Mohammad and Vishnu
Kumar. S.
9 IoTBased Animal Watch Safety Using Green Technology with Deep Learning
Approach 113
Vineet Saxena, Prashant Dhage, Ghouse Basha M. A., Trupti Patil, Mritunjay
Rai and Vishal Sharma
10 Detection of Barcode for Automatic Fastai and EDA Considering Big Data
for Green Cities 139
Santosh S. Chowhan, Vivek Veeraiah, Sukhvinder Singh Dari, Sovers Singh
Bisht, Rohit Anand, Ritu Shree and M. Niranjanamurthy
11 Number Plate Detection to Automatic Ticket Repeat Offenders in Traffic
Violation Using Green Technology 163
Anishkumar Dhablia, Bharti Sharma, Alka Singh, Jayaprakash B., Rajendra P.
Pandey and Adapa Gopi
12 IoTBased Object Detection in Green Cities by Making Use of Data Center
Based on YOLOv3 Model 189
Jayant S. Rohankar, Shaziya Islam, Priyanka Chandani, Aditee Godbole, Neeraj
Kumari and Dharmesh Dhabliya
13 Facemask Detection for Passengers' Safety Using Green Technology by Fine
Tuning on Object Detection Model in IoT 215
Mohd. Asif Iqbal, Panduranga Rao M. V., Anisha Soni, Priyank Singhal, Ankur
Gupta and Sharayu Ikhar
Part III: Industrial Applications and Predictive Maintenance
14 Enhancing Error Prediction in Machineries through CNN and Random Forest
Models Using IoT with Sensor Data Fusion 243
Thishan S. and Senthil Kumar K.
15 RealTime Flight Delay Prediction with Live Data from IoT and Airline
Operations Optimization Using the KNN Algorithm 259
B. Praveen Kumar and R. Ramprashath
16 Flight Delay Analysis Using XGBoost on Industrial Internet of Things and
Advanced Techniques for Sensor Data Aggregation and Fusion 277
Gayathri 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 287
Madhan Kumar Reddy and A. Selva Kumar
18 Comparison of Discrete Wavelet Transforms and Stationary Wavelets for the
Accurate Diagnosis of Server Issues Using Thermal Images 297
Madhan Kumar Reddy and A. Selva Kumar
Part IV: Health, Safety, and Security Applications 307
19 Diagnosis of Diseases Using Machine Learning 309
Sujita Godishala, Vakalapudi Sumavi, M. Saravanan and P.S. Maya Gopal
20 Client Attrition Prediction in Multiple Sectors with Customized Machine
Learning Models Using IoT 319
R. Balaji and R. Ramprashath
21 Blood Transfusion System Using Data Mining Techniques and Grey Relational
Analysis (GRA) Using Decision Tree Compared with Naive Bayes 335
K. Manimaran and T. Poovizhi
22 IoTIntegrated Detection and Classification of Deepfake Images and Videos
Using Custom Deep Learning Models 345
K. Praveen Kumar and R. Ramprashath
23 Reducing the False Rejection Using Novel Iris Recognition by Comparing
with Elastic Bunch Graph Matching for Smartphones 359
Kamalesh S. and V. Nagaraju
24 Intelligent IoTEnabled PrivacyPreserving Course Recommendation System:
Leveraging NLP Chatbot and Federated Learning with Federated Linear
Regression 371
Dhivyaprabha G. and Ram Prashath R.
25 Harnessing YOLOPowered Drones for CloudBased Weed Density Mapping
Focusing Agri 4.0 385
S. Vishnu Kumar, G. Aloy Anuja Mary, B. Sathyasri, Murali Kalipindi and
Chivon Choeung
References 399
About the Editors 401
Index 403
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.
