Discover detailed insights into the methods, algorithms, and techniques for deep learning in sensor data analysis

Sensor Data Analysis and Management: The Role of Deep Learning delivers an insightful and practical overview of the applications of deep learning techniques to the analysis of sensor data. The book collects cutting-edge resources into a single collection designed to enlighten the reader on topics as varied as recent techniques for fault detection and classification in sensor data, the application of deep learning to Internet of Things sensors, and a case study on high-performance computer gathering and processing of sensor data.

The editors have curated a distinguished group of perceptive and concise papers that show the potential of deep learning as a powerful tool for solving complex modelling problems across a broad range of industries, including predictive maintenance, health monitoring, financial portfolio forecasting, and driver assistance.

The book contains real-time examples of analyzing sensor data using deep learning algorithms and a step-by-step approach for installing and training deep learning using the Python keras library. Readers will also benefit from the inclusion of:

A. Suresh, PhD is an Associate Professor in the Department of Computer Science and Engineering in SRM Institute of Science & Technology, Kattankulathur, Chengalpattu Dist., Tamil Nadu, India. With nearly two decades of experience in teaching, his areas of specializations include Data Mining, Artificial Intelligence, Image Processing, Multimedia and System Software. He has two patents and has published approximately 90 papers in International journals. He has authored Industrial IoT Application Architectures and Use Cases published in CRC press and edited Deep Neural Networks for Multimodal Imaging and Biomedical Application published in IGI Global. He has published more than 40 papers in National and International Conferences and has served as editor / reviewer for Springer, Elsevier, Wiley, IGI Global, IoS Press, Inderscience journals, and many more. He is a Senior Member of IEEE, ISTE, MCSI, IACSIT, IAENG, MCSTA and a Global Member of Internet Society (ISOC). He has organized several National Workshops, Conferences and Technical Events. He is regularly invited to deliver lectures in various programs for imparting skills in research methodology to students and research scholars. He has published four books by Indian publishers, in the name of Hospital Management, Data Structures & Algorithms, Computer Programming, Problem Solving and Python Programming and Programming in C. He has hosted two special sessions for IEEE sponsored conferences in Osaka, Japan and Thailand. .

R. Udendhran is a deep learning Researcher affiliated with Bharathidasan University (A+ grade government university) in India. He has published five research papers and is indexed in the Web of Science and Scopus databases on the subject of deep learning. He has also presented his research work in an international conference held at University of Cambridge, United Kingdom on the subject of deep learning. He is serving as a manuscript reviewer for ELSEVIER, WILEY, IEEE access, IEEE sensors conferences, Springer, SciPub, and Manning publishers.

M. S. Irfan Ahmed is Associate Professor in the Department of Computer Science and Information, Faculty of Science and Literature at Taibah University. He is a member of ISTE, MCSI, IACSIT, and IAENG.

About the Editors vii

List of Contributors ix

Preface xiii

1 Efficient Resource Allocation Using Multilayer Neural Network in Cloud Environment 1
N. Vijayaraj, G. Uganya, M. Balasaraswathi, V. Sivasankaran, Radhika Baskar, and A.S. Syed Fiaz

2 Internet of Things for Human-Activity Recognition Based on Wearable Sensor Data 19
Dr. Vikram Rajpoot, Sudeep Ray Gaur, Aditya Patel, and Dr. Akash Saxena

3 Evaluation of Feature Selection Techniques in Intrusion Detection Systems Using Machine Learning Models in Wireless Ad Hoc Networks 33
T.J. Nagalakshmi, M. Balasaraswathi, V. Sivasankaran, D. Ravikumar, S. Joseph Gladwin, and S. Pravin Kumar

4 Neuro-Fuzzy-Based Bidirectional and Biobjective Reactive Routing Schema for Critical Wireless Sensor Networks 73
K.M. Karthick Raghunath and G.R. Anantha Raman

5 Feature Detection and Extraction Techniques for Real-Time Student Monitoring in Sensor Data Environments 97
Dr. V. Saravanan and Dr (Ms). N. Shanmuga Priya

6 Deep Learning Analysis of Location Sensor Data for Human-Activity Recognition 103
Hariprasath Manoharan, Ganesan Sivarajan, and Subramanian Srikrishna

7 A Quantum-Behaved Particle-Swarm-Optimization-Based KNN Classifier for Improving WSN Lifetime 117
Ajmi Nader, Helali Abdelhamid, and Mghaieth Ridha

8 Feature Detection and Extraction Techniques for Sensor Data 131
Dr. L. Priya, Ms. A. Sathya, and Dr. S. Thanga Revathi

9 Object Detection in Satellite Images Using Modified Pyramid Scene Parsing Networks 147
Akhilesh Vikas Kakade, S Rajkumar (Corresponding Author), K Suganthi, and L Ramanathan

10 Coronary Illness Prediction Using the AdaBoost Algorithm 161
G. Deivendran, S. Vishal Balaji, B. Paramasivan, S. Vimal (Corresponding Author)

11 Geographic Information Systems and Confidence Interval with Deep Learning Techniques for Traffic Management Systems in Smart Cities 173
Prisilla Jayanthi

Index 199