Table Of ContentLecture Notes in Electrical Engineering 947
Amit Kumar
Sabrina Senatore
Vinit Kumar Gunjan Editors
ICDSMLA
2021
Proceedings of the 3rd International
Conference on Data Science, Machine
Learning and Applications
Lecture Notes in Electrical Engineering
Volume 947
Series Editors
Leopoldo Angrisani, Department of Electrical and Information Technologies Engineering, University of Napoli
Federico II, Naples, Italy
Marco Arteaga, Departament de Control y Robótica, Universidad Nacional Autónoma de México, Coyoacán,
Mexico
Bijaya Ketan Panigrahi, Department of Electrical Engineering, Indian Institute of Technology Delhi, New
Delhi, Delhi, India
Samarjit Chakraborty, Fakultät für Elektrotechnik und Informationstechnik, TU München, Munich, Germany
Jiming Chen, Zhejiang University, Hangzhou, Zhejiang, China
Shanben Chen, Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Tan Kay Chen, Department of Electrical and Computer Engineering, National University of Singapore,
Singapore, Singapore
Rüdiger Dillmann, Humanoids and Intelligent Systems Laboratory, Karlsruhe Institute for Technology,
Karlsruhe, Germany
Haibin Duan, Beijing University of Aeronautics and Astronautics, Beijing, China
Gianluigi Ferrari, Università di Parma, Parma, Italy
Manuel Ferre, Centre for Automation and Robotics CAR (UPM-CSIC), Universidad Politécnica de Madrid,
Madrid, Spain
Sandra Hirche, Department of Electrical Engineering and Information Science, Technische Universität
München, Munich, Germany
Faryar Jabbari, Department of Mechanical and Aerospace Engineering, University of California, Irvine, CA,
USA
Limin Jia, State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland
Alaa Khamis, German University in Egypt El Tagamoa El Khames, New Cairo City, Egypt
Torsten Kroeger, Stanford University, Stanford, CA, USA
Yong Li, Hunan University, Changsha, Hunan, China
Qilian Liang, Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA
Ferran Martín, Departament d’Enginyeria Electrònica, Universitat Autònoma de Barcelona, Bellaterra,
Barcelona, Spain
Tan Cher Ming, College of Engineering, Nanyang Technological University, Singapore, Singapore
Wolfgang Minker, Institute of Information Technology, University of Ulm, Ulm, Germany
Pradeep Misra, Department of Electrical Engineering, Wright State University, Dayton, OH, USA
Sebastian Möller, Quality and Usability Laboratory, TU Berlin, Berlin, Germany
Subhas Mukhopadhyay, School of Engineering and Advanced Technology, Massey University,
Palmerston North, Manawatu-Wanganui, New Zealand
Cun-Zheng Ning, Department of Electrical Engineering, Arizona State University, Tempe, AZ, USA
Toyoaki Nishida, Graduate School of Informatics, Kyoto University, Kyoto, Japan
Luca Oneto, Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of
Genova, Genova, Genova, Italy
Federica Pascucci, Dipartimento di Ingegneria, Università degli Studi “Roma Tre”, Rome, Italy
Yong Qin, State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
Gan Woon Seng, School of Electrical and Electronic Engineering, Nanyang Technological University,
Singapore, Singapore
Joachim Speidel, Institute of Telecommunications, Universität Stuttgart, Stuttgart, Germany
Germano Veiga, Campus da FEUP, INESC Porto, Porto, Portugal
Haitao Wu, Academy of Opto-electronics, Chinese Academy of Sciences, Beijing, China
Walter Zamboni, DIEM—Università degli studi di Salerno, Fisciano, Salerno, Italy
Junjie James Zhang, Charlotte, NC, USA
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· ·
Amit Kumar Sabrina Senatore
Vinit Kumar Gunjan
Editors
ICDSMLA 2021
Proceedings of the 3rd International
Conference on Data Science, Machine
Learning and Applications
Editors
Amit Kumar Sabrina Senatore
BioAxis DNA Research Centre Private Ltd. Department of Computer Engineering,
Hyderabad, Telangana, India Electrical Engineering and Applied
Mathematics
Vinit Kumar Gunjan University of Salerno
Department of Computer Science Fisciano, Salerno, Italy
and Engineering
CMR Institute of Technology
Hyderabad, Telangana, India
ISSN 1876-1100 ISSN 1876-1119 (electronic)
Lecture Notes in Electrical Engineering
ISBN 978-981-19-5935-6 ISBN 978-981-19-5936-3 (eBook)
https://doi.org/10.1007/978-981-19-5936-3
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Preface
The rising technologies of artificial intelligence (AI), data science, and machine
learning (ML) are advancing businesses more quickly than ever. Success in this era
of digital transformation depends on leveraging analytics to uncover vast amount
of data with detailed insights. In the past, these insights were uncovered manually
through extensive data analysis and data complexity which continue to rise. The most
recent technologies for data scientists are AI and ML, which allow them to quickly
customize the data to verify its usefulness.
With the advancements in computing power, organizations are now interested in
analyzing both internal and external data to identify previously unknown insights that
will drive operational efficiency, boost sales, and provide a competitive marketplace
advantage.
AI is a technology that continues to advance rapidly, and the discourse on AI
ethics and governance is also evolving. Globally, a number of different sets of ‘AI
ethics principles’ have been put forward by multilateral organizations, private sector
entities, and several nation states. The future of AI is determined by a diverse group
of stakeholders, including researchers, private organizations, government, standard-
setting bodies, regulators, and general citizens. Around the world, many countries
and organizations have defined principles to guide responsible management of AI for
stakeholders. Though automated solutions are expected to introduce objectivity to
decision making, recent cases globally have shown that AI solutions have the potential
to be ‘biased’ against specific sections of society. This can lead to inconsistent output
across a diverse demography.
Selected papers from the International Conference on Data Science, Machine
Learning and Applications, 2021 are placed in this volume. The chapters in this
book provide an overview of the key concepts and theories underlying the technolo-
gies and applications deliberated during the 2021 ICDSMLA Conference, with a
focus on data science, machine learning, face recognition, evolutionary algorithms,
like genetic algorithms, automotive applications, automation devices using artificial
neural networks, business management systems, the Internet of Things (IoT), and
contemporary speech processing systems. Additionally, the topics covered in this
book are contemporary developments in sensor networks, VLSI systems, precision
v
vi Preface
agriculture, and medical diagnostic systems. Wherever appropriate, a discussion of
learning and software modules in artificial intelligence, soft computing, and deep
learning algorithms is included. In a nutshell, this book sheds light on the data
science and ML-based societal innovations that are useful for the social good.
Hyderabad, India Amit Kumar
Fisciano, Italy Sabrina Senatore
Hyderabad, India Vinit Kumar Gunjan
Contents
Road Accident Detection and Indication System ...................... 1
Y. Lavanya, P. BhagyaSri, P. BhuvanaSri, and K. Noha Namratha
Attendance System Based on Face Recognition Using Haar
Cascade and LBPH Algorithm ...................................... 9
Akshat Kumar Rai, A. Akash, G. Kavyashree, and Thaseen Taj
Different Thresholding Techniques in Image Processing : A Review .... 23
Radha Seelaboyina and Rajeev Vishwakarma
Dynamic Weighting Selection for Predictive Torque and Flux
Control of Industrial Drives ........................................ 31
Vishnu Prasad Muddineni, Anil Kumar Bonala, and Thanuja Penthala
Population Index and Analysis Based on Different Geographies;
Using Distance Measurement, Social Distancing, and Deep
Learning ......................................................... 45
Bhushan Chougule, Samiksha Baral, Minal Tayde, and Kaustubh Sakhare
On the Discriminability of Samples Using Binarized ReLU
Activations ........................................................ 65
Michał Lewandowski, Werner Zellinger, Hamid Eghbal-zadeh,
Natalia Shepeleva, and Bernhard A. Moser
Supervised and Unsupervised Machine Learning
Approaches—A Survey ............................................ 73
C. Esther Varma and Puja S. Prasad
Skin Cancer Classification Using Deep Learning ..................... 83
D. K. Yashaswini, Pratheeksha C. Dhanpal, and S. A. Bhoomika
Crop Yield Prediction Using Deep Learning .......................... 93
K. Mamatha, Shantideepa Samantha, and Kundan Kumar Prasad
vii
viii Contents
Real-Time Tweets Streaming and Comparison Using Naïve Bayes
Classifier ......................................................... 103
S. R. Shankara Gowda, Rose King, and M. R. Pavan Kumar
Smart Shopping Trolley for Billing System ........................... 111
R. Kishor Kumar, V. Ashwitha, S. Jeevitha, P. Pranusri, and D. Rakshitha
A Survey on IoT Protocol in Real-Time Applications and Its
Architectures ..................................................... 119
M. L. Umashankar, S. Mallikarjunaswamy, N. Sharmila,
D. Mahesh Kumar, and K. R. Nataraj
Safe Characteristic Signature Systems with Different Jurisdiction
Using Blockchain in E-Health Records .............................. 131
Shivakumar Dalali, B. K. Pramod, Ranjith Kumar, and M. J. Thejas Jain
Web-Based Trash Segregation Using Deep Learning Algorithm ........ 139
S. Sheeba, Akshay Mohan, Ashish Kumar Jha, Bikash Agarwal,
and Priya Singh
Home Automation Using Face Recognition for Wireless Security ....... 149
B. S. Umashankar, Mandalia Vishal Shailesh, Md Shaghil Z. Ansari,
and Rahul Markandey
Hybrid-Network Intrusion Detection (H-NID) Model Using
Machine Learning Techniques (MLTs) .............................. 161
K. R. Pradeep, Arjun S. Gowda, and M. Dakshayini
Impact of Using Partial Gait Energy Images for Human
Recognition by Gait Analysis ....................................... 175
Devanshi Singh and K. T. Thomas
Several Routing Protocols, Features and Limitations for Wireless
Mesh Network (WMN): A Review ................................... 187
Jasleen Kaur and Hardeep Singh
A Deep Meta-model for Environmental Sound Recognition ............ 201
K. S. Arun
Spatial Computing: Next Big Thing of Physical and Digital World ..... 211
Dweepna Garg, Bhavika Patel, Radhika Patel, and Ritika Jani
Cloud Accessing Based on IOT Oriented WSNs for Optimal Water
Conservation in Farming ........................................... 221
K. Raju, Y. Lavanya, J. Prasanth Kumar, and Jagan Mohan Rao
S-Extension Patch: A Simple and Efficient Way to Extend
an Object Detection Model ......................................... 231
Dishant Parikh
Contents ix
Roles and Impact of ASHA Workers in Combating COVID-19:
Case Study Bhubaneswar .......................................... 243
Manjusha Pandey, S. N. Misra, Abhipsa Ray, and S. S. Rautaray
Challenges and Requirements for Integrating Renewable Energy
Systems with the Grid ............................................. 257
Komal Bai, Vikas Sindhu, Ahteshamul Haque,
and V. S. Bharath Kurukuru
Design of Progressive Monitoring Overhead Water Tank .............. 267
N. Alivelu Manga, Surya Teja Manupati, N. S. C. Viswanadh,
P. Sriram, and D. V. S. G. Varun
An Anchor-Based Fuzzy Rough Feature Selection for Text
Categorization .................................................... 281
Ananya Gupta and Shahin Ara Begum
Fabric Variation and Visualization Using Light Dependent Factor ..... 293
Gorsa Lakshmi Niharika, Shahana Bano, Kondapaneni Charan Sai,
Kavuri Rohith, and Dasaradh Gutta
Pulse Rate Estimation with a Smartphone Camera Using Image
Processing Algorithm .............................................. 303
E. C. Sowmiya, K. Nirmala, and L. Suganthi
Multilayer Perceptron Based Early On-Site Estimation of PGA
During an Earthquake ............................................. 313
Siddhartha Sarkar, Satish Kumar, Anubrata Roy, and Bhargab Das
IoT-Equipped Smart Campus Using LoRa Technology ................ 327
D. Annapurna, D. Tejus, Girish Narayan, Shrushti Hegde,
and Parth PratimMishra
A Novel Approach for Visualizing Medical Big Data Using
Variational Autoencoders .......................................... 337
G. Madhukar Rao and Dharavath Ramesh
An Efficient Cybersecurity Framework for Detecting Network
Attacks Using Deep Learning ....................................... 347
K. R. Nataraj, Manasa, and M. Chandana
Evaluation of Network Parameters in Cloud Environment ............. 355
S. R. Ahrthi, G. Sinchana, A. Trisha, and B. Sahana
Multiple DG Placement in Distribution Network
with Reconfiguration Process for Active Power Loss
Minimization ..................................................... 363
B. Devulal, M. Siva, D. Ravi Kumar, A. Supriya, and P. Sushma Devi
