This Taylor & Francis, CRC Press volume contains the papers presented at the International Conference on Emerging Trends in Intelligent Computing Techniques (ICETICT – 2024) held during 27th and 28th December 2024 organized by DRIEMS University, Tangi, Cuttack, Odisha, India. A lot of challenges at us and no words of appreciation is enough for the organizing committee who could still pull it off successfully. The conference draws the excellent technical keynote talk and many papers. The keynote talks by Prof. Sanjeevikumar Padmanaban, University of South-Eastern Norway and Prof. Bidyadhar Subudhi, Director, NIT, Warangal are worth mentioning. We are grateful to all the speakers for accepting our invitation and sparing their time to deliver the talks.
This Taylor & Francis, CRC Press volume contains the papers presented at the International Conference on Emerging Trends in Intelligent Computing Techniques.
List of Figures, List of Tables, Preface, Editors Biography, Reviewers,
Committee Members,
1. An SRR metamaterial for focusing enhancement of W-band
lens antenna for microwave imaging,
2. Development of a visitor tracking
system for tourist areas to monitor crowd density, peak hours and visitor
demographics,
3. A study on extending IoT applications in multiprocessing
agricultural systems,
4. A novel approach for mask face detection using
convolutional neural network,
5. Enhancing 5G network management through
association rule mining: Uncovering network traffic patterns,
6. A
binarization method for Odia palm leaf manuscripts by using the Odia language
accelerator model,
7. FRMM-LSTM multimodal fusion based caption recurrent
network for vision analysis,
8. Convolutional neural network-based
classification of potato leaf diseases,
9. Content-based deep neural image
retrieval system for remote sensing images,
10. Modelling non-linear time
series data using deep learning techniques,
11. Intelligent strategies for
the techno-economic evaluation of large-scale energy storage integrated
hybrid power systems,
12. Revolutionizing cancer diagnosis using machine
learning techniques,
13. An ensemble approach for heart disease prediction,
14. Hierarchically vectorized algorithmic paradigm for probabilistic node
localization and pervasive threat detection in synthetically optimized
WSN-assisted IoT architectures,
15. A six element antenna array for 5G
application,
16. Experimental investigation on semantic communication system
for speech signal based on deep learning approach,
17. Enhanced convolutional
block attention decision Transnet for efficient IoT-driven patient monitoring
and heart disease detection,
18. Enhancing healthcare accessibility: An
AI-powered chatbot for symptom analysis and precautionary guidance,
19. Flood
prediction model using LSTM and SVM,
20. Real time face mask detection in
nuclear power plants: A deep learning framework using hybrid CNN-mobileNetV2
architecture,
21. Object detection and trajectory prediction using faster
RCNN and Kalman filter,
22. A genetic algorithm-optimized hybrid CNN-LSTM for
robust EEG seizure detection and adversarial defense,
23. Utilization of deep
learning and machine learning models to approach high glucose and low glucose
prediction with type 1 diabetes mellitus in adult patients,
24. Asthma risk
prediction through stacking-based ensemble learning,
25. Predicting diabetic
patients coronary artery calcium score, deep learning using retinal images,
26. Modelling and performance analysis of a dexterous linkage-driven
three-fingered under-actuated robotic hand,
27. Intelligent agriculture
system using soft computing techniques,
28. Synthesis, structural and Raman
study of Zn doped CuO nanoparticles,
29. Immersive Learning in Ayurveda:
Revolutionizing Dhatu Poshan Nyaya education through AR/VR technologies,
30.
Combating food insecurity through remote sensing and machine learning for
enhanced crop yield prediction,
31. PQ improvement with TLBO FOPID based
SHAF,
32. GWO fuzzy PID controlled cuk and SEPIC converter based PFR,
33.
Enhancing web application security: A machine learning approach to firewall
implementation,
34. Combination of transition metal oxide into carbon
nanofiber matrix for enhancement in electrochemical performance of
supercapacitor,
35. Experimental investigation on detection of medical image
edges using radial basis fuzzy-neural network technique: A comparative
analysis,
36. Hybrid vision transformer and CNN-based model for efficient
cotton leaf disease detection,
37. Sensitivity analysis based performance
assessment of a MGWO based PID control approach for regulating frequency in
an interconnected power system,
38. Real time garbage detection using CNN and
YOLO algorithms,
39. A novel modified SCA-PID based load frequency control,
40. Challenges and innovations in EV charging infrastructure: A focus on
Indias path to electrified transportation,
41. Utilization of areca fibre
and bottom ash on geotechnical properties of expansive soil,
42.
Nature-inspired metaheuristic algorithm optimized TIDN controller for
frequency management in networked power system with storage device and HVDC
link,
43. Effect of compression on floating ice-floe with an irregular porous
seabed,
44. Smart hotel automation system,
45. A novel hybridized method for
moving object detection based on optical flow and edge detection technique in
a dynamic scene environment,
46. YOLO & ML based crack detection and strength
prediction for structural health monitoring of bridges,
47. Real-time vehicle
accident detection using computer vision and deep learning,
48. Heuristic
traffic management and load balancing techniques for wireless body area
networks,
49. Deep learning based optimized diagnostic model for diabetic
retinopathy detection,
50. Analyzing PM2.5 levels across diverse zones in
Cuttack, Odisha,
51. Smart fitness tracker for exercise monitoring integrated
with voice assistant,
52. A systematic literature review of public sentiments
on health initiatives: A case study of COVID-19,
53. High-quality image
generation from text descriptions using stable diffusion: A machine learning
approach,
54. Test scenario generation and optimization from UML behavioural
diagrams,
55. Hybrid CNN-LSTM approach for sentiment analysis on IMDB movie
reviews,
56. An Internet of Things system application for monitoring and
control of underground mine environment,
57. A novel U-Net with fine tuned
VGG16 backbone model for ulcer detection and classification using 2-D
endoscopy images,
58. A literature review of mental health assessment using
social media post for depression,
59. Convolutional neural network approach
to emotion recognition in speech,
60. Review of solar power generation
forecasting using deep learning techniques,
61. A comparative analysis of
breast cancer predictive intelligent model using machine learning techniques,
62. An efficient CNN based hybrid model for cataract classification on ODIR
dataset,
63. An assessment of vibration in non-prismatic Timoshenko beams
with multiple transverse splits,
64. Predictive analytics in healthcare
systems,
65. Electromagnetic interference shielding of Zn-50%-Al alloy-coated
polypropylene flexible conducting film,
66. Robust digital image watermarking
using hybrid optimization technique
Dr. Tusharkanta Samal holds a Bachelor of Technology in In received MTech and Ph.D. degree in Computer Science and engineering from Veer Surendra Sai University of Technology, Burla, Odisha, India. Currently he is working as an associate Professor in Department of Computer Science and engineering, DRIEMS University, Odisha, India. He has more than 12 years of teaching and research experience in different Engineering colleges and Universities. Dr. Samal has authored over 30 scientific papers published in SCI, Scopus Indexed Journals and Conferences.
Dr. Ambarish Panda holds a Bachelor of Engineering in Electrical Engineering and Master of Technology in Power System Engineering from Sambalpur University and V.S.S University of Technology. He completed his Ph.D. in Electrical Engineering from V.S.S University of Technology since April, 2016. He has more than 14 years of teaching and research experience in different Engineering colleges and Universities. To his credit, he has published multiple research articles in SCI/SCIE indexed journals with high repute. Besides his research activities he serves as reviewer and Editor in SCI/SCIE Indexed Journal.
Manas Ranjan Kabat is currently working as the principal of IMIT, a constituent college of BPUT. He has received his M.E. degree in Information Technology and Computer Engineering from Bengal Engineering College, India, and the Ph.D. degree in Computer Science and Engineering from Sambalpur University He has more than two decade of teaching experience both at undergraduate and postgraduate level. He has published more than 75 research paper in various referred international journals and conferences. He has guided more than 20 M.Tech and 9 Ph.D. students. Chaired and organized many international and national conferences. Contributed as editor and reviewer of many peer-reviewed international journals His research interests include QoS in internet, Wireless Sensor Network, Body Area Network, Cloud Computing etc.
Ali Ismail Awad (Ph.D., SMIEEE, MACM) is an Associate Professor at the College of Information Technology, United Arab Emirates University (UAEU), Al Ain, United Arab Emirates, where he has been coordinating the masters program in Information Security since 2022. He is also an Honorary Associate Professor at the University of Nottingham, Nottingham, U.K. From 2018 to 2023, he served as a Visiting Researcher at the University of Plymouth, Plymouth, U.K. Dr. Awad joined the Department of Computer Science, Electrical and Space Engineering at Luleå University of Technology (LTU), Luleå, Sweden, in 2013. In 2017, he was promoted to Associate Professor (Docent) and served as the coordinator of the masters program in Information Security from 2017 to 2020. In recognition of his teaching merits and pedagogical achievements, he was promoted to the rank of Recognized University Teacher at LTU in 2021. His research interests include cybersecurity, network security, Internet of Things (IoT) security, and image analysis with biometrics and medical imaging applications. He has edited or co-edited several books and authored or co-authored numerous journal articles and conference papers in these areas of interest. From 2021 to 2024, he was recognized among the top 2% of influential scientists worldwide. Dr. Awad serves on the Editorial Boards of Future Generation Computer Systems, Computers & Security, Internet of Things; Engineering Cyber-Physical Human Systems, Health Information Science and Systems, and Security, Privacy and Authentication (Frontiers). Dr. Awad is an IEEE Senior Member and an ACM Professional Member.
Dr. Suvendra Kumar Jayasingh is working as Associate Professor and HOD in the Department of Computer Science & Engineering, Institute of Management and Information Technology (IMIT), Cuttack (A Constituent College of BPUT, Govt. of Odisha) after being selected in OPSC (Orissa Public Service Commission) in 2005. He has obtained his Bachelor of Engineering the year 2003 from University College of Engineering (UCE), Burla (Now VSSUT). He got his M. Tech. in Computer Science & Engineering in 2007 from RVU, Udaipur and Ph. D. in Computer Science & Engineering in 2020 from North Orissa University, Baripada (Now Maharaja Sriram Chandra Bhanja Deo University). He is having 20 years of teaching experience in Computer Science & Engineering and MCA. He has published several articles, book chapters in reputed National and International journals and periodicals including Springer and Taylor & Francis and has presented research papers in National and International Seminars and Conferences. He has also participated in many National and International Workshops, FDPs, Industrial Training Programs organized by IITs, NITs and NITTTRs. His research interests include Artificial Intelligence, Data Mining, Soft Computing, Machine Learning, Computational Intelligence, Database Management System and Algorithm Analysis and Design. He has published a book on Introduction to Machine Learning and a UK patent on Smart Home Air Quality Monitoring Device.He is a life member of Indian Society for Technical Education (ISTE).
Dr. Deepak K Tosh is an assistant professor in Computer Science at the University of Texas at El Paso. Before that he was a Cybersecurity Researcher at the DoD Sponsored Center of Excellence in Cybersecurity, Norfolk State University (NSU), Norfolk, Virginia. During that time, he has closely collaborated with researchers from Air Force Research Lab and Army Research Lab to establish data provenance mechanisms in cloud computing in addition to addressing research challenges in the arena of distributed system security, Blockchain, cyber>threat information sharing, cyber-insurance, and Internet of Battlefield Things (IoBT). He was appointed shortly as a postdoctoral researcher at the Tennessee State Univerity, where he worked with Dr. Sachin Shetty in the CyberViz Laboratory. He has been collaborating with Dr. Shetty since then focusing on research topics such as: distributed consensus models in Blockchain technology, cyber-resiliency in battlefield environment, and various practical issues in cloud computing security. He has received my Ph.D. in Computer Science and Engineering from University of Nevada, Reno, under the supervision of Dr. Shamik Sengupta. His dissertation was focused on designing market based models to enable cybersecurity information sharing among organizations. He received my masters in Computer Science from University of Hyderabad, India in 2012. His master thesis addressed the issue of cognitive radio transmission parameter adaptation problem using multi-objective optimization techniques.
