Emerging Trends and Future Directions in Artificial Intelligence, Machine Learning, and Internet of Things Innovations

Name: Emerging Trends and Future Directions in Artificial Intelligence, Machine Learning, and Internet of Things Innovations
Brand: CRC Press
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Khumukcham Robindro Singh Nazrul Hoque Arnab Kumar Maji Sabyasachi Mondal Jyoti Sekhar Banerjee Siddhartha Bhattacharyya Panagiotis Sarigiannidis(Herausgeber*in)

CRC Press

Erscheint ca. am 29. September 2025

288 Seiten

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Dr. Khumukcham Robindro Singh received his Master's degree in Computer Application from Manipur University, Imphal, in 2007, and was awarded his Ph.D. from Gauhati University, Guwahati, Assam, in 2013. With approximately 12 years of professional experience, he is currently serving as Assistant Professor and Head of the Department of Computer Science at Manipur University, Imphal-a Central University of India. Dr. Singh is also the Chairman of the eOffice Implementation Committee, where he is actively spearheading the university's digital transformation initiatives. Additionally, he has frequently served on the College Inspection Team of the university and has been appointed as the Nodal Officer of the Ek Bharat Shreshtha Bharat (EBSB) Cell, Manipur University. A sought-after speaker, Dr. Singh has been invited by several departments within and outside the university to deliver expert talks on Artificial Intelligence and its applications. He has published around 15 research articles in reputed SCIE/Scopus indexed international journals, over 10 book chapters, and 12 papers in conference proceedings. Under his guidance, three Ph.D. scholars have successfully completed their research, and he has mentored 30 MCA major project theses. Dr. Singh has completed a major research project in collaboration with IIT Guwahati and Tezpur University, funded by the Ministry of Electronics and Information Technology (MeitY), Government of India. He has also organised two National Workshops on High Performance Computing in collaboration with CDAC Pune and IIT Kharagpur under the National Supercomputing Mission. He serves as a reviewer for several reputed international journals, and his primary research interests include Artificial Intelligence, Machine Learning, and Deep Learning.

Dr. Nazrul Hoque received his Ph.D. degree in Computer Science and Engineering from Tezpur University, Tezpur, India, in 2017. He is currently working as an Assistant Professor in the Department of Computer Science, Manipur University, Canchipur, Imphal, India. He has published more than 40 papers in international journals and referred to conference proceedings. Dr. Hoque has published papers in IEEE Communication Surveys and Tutorials, IEEE Access, Expert Systems with Applications, Computer Communications, Complex and Intelligent Systems, Security and Privacy, and Cybersecurity. He is a member of the editorial team of the Journal Scientific Reports. His research interests include Machine Learning, Network Security, and the Internet of Things.

Dr. Arnab Kumar Maji received his B.E. degree in Information Science and Engineering from Visvesvaraya Technological University (VTU) in 2003 and M.Tech in Information Technology from Bengal Engineering and Science University, Shibpur (currently IIEST, Shibpur) in 2006. He received his Ph.D. from Assam University, Silchar (a Central University of India) in 2016. He has approximately 20 years of professional experience. He is currently working as Associate Professor in the Department of Information Technology, North-Eastern Hill University, Shillong (a Central University of India). He has published around 40 articles in different reputed SCIE/SCOPUS-Indexed International Journals, more than 12 articles as book chapter, 30 papers as conference proceedings, and authored 03 books with several international Publishers like Elsevier, Springer, IEEE, MDPI, IGI Global, and McMilan International. 08 PhD scholars are successfully guided by him. He has also guided successfully 18 M.Tech theses. He is also reviewer of several reputed international journals and a guest editor for a Springer journal. 02 patents and 01 copyright are granted in his name. His Research interests include Computer Vision and Natural Language Processing.

Dr. Sabyasachi Mondal is an Associate Professor in the Department of Mathematics at North-Eastern Hill University, Shillong, Meghalaya, India. He obtained his B.Sc. (Hons.) in Mathematics, M.Sc. in Applied Mathematics, and Ph.D. in Computational Fluid Dynamics from Visva-Bharati Santiniketan, West Bengal, India. He worked as a 'Postdoctoral Research Fellow' at the University of KwaZulu-Natal, South Africa. His areas of research interest include Computational Fluid Dynamics, Heat and Mass Transport, and Nanofluid flow. With 13 years of teaching experience, he has more than 95 (SCOPUS 78) International Publications in different reputed journals, books, and conferences in his credit. Also, Dr. Mondal has published 01 Indian patent and filed 01 Indian patent recently. Dr. Mondal delivered 06 invited talks in different universities and colleges. He is an editorial board member in 06 international journals and is a reviewer for more than 50 reputed journals which include Elsevier, Springer, Wiley, and Taylor & Fransis. Dr. Mondal has received various prestigious funds and fellowships like UKZN PDF fellowship, Claude Leone Postdoctoral fellowship, and NRF travel grants. Dr. Mondal has research collaborations with various eminent scientists in India and abroad, like South Africa, Botswana, Malaysia, and Iran. His research has led to him being selected as 'Top 2% Most Influential Scientists' list published by 'Standford University and SCOPUS for the year 2022-2023 in the domain of 'Mechanical Engineering and Transports' and 'Applied Mathematics'.

Dr. Jyoti Sekhar Banerjee is currently serving as the Head of the Department of the Computer Science and Engineering (AI & ML) at the Bengal Institute of Technology, Kolkata, India. He also serves as the Professor-in-Charge, R&D and Consultancy Cell, and as the Nodal Officer of the IPR Cell at BIT. Since 2024, he also works as a Remote Researcher in the Internet of THings & AppliCAtions Lab (ITHACA) at the Department of Electrical and Computer Engineering, University of Western Macedonia, Greece. He is the former Remote Research Fellow of the Cognitive Computing and Brain Informatics Research Group (CCBI) at Nottingham Trent University (NTU), UK. Dr. Banerjee holds his Post>Doctoral Fellowship at Nottingham Trent University, UK, in the Department of Computer Science. He also completed the Post Graduate Diploma in IPR & TBM from MAKAUT, WB. He has teaching and research experience spanning 20 years and completed one IEI funded project. He is a member of the CSI, IEEE, ISTE, IEI, ISOC, IAENG, and a fellow of IETE. He presently serves as Secretary-cum-Treasurer of the ISTE WB Section and Secretary of the IETE, Kolkata Centre. He is the Immediate Past Secretary of the Computer Society of India, Kolkata Chapter. Dr. Banerjee is also elected as the Vice Chairman Cum Chairman Elect in Computer Society of India, Kolkata Chapter, for 2025-2027.

Dr. Siddhartha Bhattacharyya [FRSA, FIET (UK), FIEI, FIETE, FSCRS, LFOSI, SMIEEE, SMACM, SMAAIA, SMIETI, LMCSI, LMISTE] is currently a senior researcher at VSB - Technical University of Ostrava, Ostrava, Czech Republic. He is also a Scientific Advisor at Algebra University, Zagreb, Croatia. Prior to this, he was the Principal of Rajnagar Mahavidyalaya, Birbhum, India. Before this, he was a professor at CHRIST (Deemed to be University), Bangalore, India. He also served as the Principal of RCC Institute of Information Technology, Kolkata, India. He has also served as a Senior Research Scientist at VSB Technical University of Ostrava, Czech Republic. He is the recipient of several coveted national and international awards. He has received the Honorary Doctorate Award (D. Litt.) from the University of South America and the SEARCC International Digital Award ICT Educator in 2017. He was appointed as the ACM Distinguished Speaker for the tenure of 2018-2020. He has been appointed as the IEEE Computer Society Distinguished Visitor for 2021-2024. He is a co-author of 6 books and the co-editor of 106 books and has more than 400 research publications in international journals and conference proceedings to his credit.

Dr. Panagiotis Sarigiannidis is the Director of the ITHACA lab, co-founder of the first spin-off of the University of Western Macedonia: MetaMind Innovations P.C., and a Full Professor in the Department of Electrical and Computer Engineering at the University of Western Macedonia, Kozani, Greece. He received his B.Sc. and Ph.D. degrees in Computer Science from Aristotle University of Thessaloniki, Thessaloniki, Greece in 2001 and 2007, respectively. He has published over 360 papers in international journals, conferences, and book chapters, including IEEE Communications Surveys and Tutorials, IEEE Transactions on Communications, IEEE Internet of Things, IEEE Transactions on Broadcasting, IEEE Systems Journal, IEEE Wireless Communications Magazine, IEEE Open Journal of the Communications Society, IEEE/OSA Journal of Lightwave Technology, IEEE Transactions on Industrial Informatics, and IEEE Access and Computer Networks. He has received 6 best paper awards and the IEEE SMC TCHS Research and Innovation Award in 2023. He has been involved in several national, European and international projects, coordinating and technically leading numerous national and European projects including H2020, Horizon Europe, Erasmus+, and operational programs. His research interests include Telecommunication Networks, Internet of Things, and Network Security. He is an IEEE member and participates in the Editorial Boards of various journals, including IEEE Transactions on Communications, IET Networks, International Journal of Communication Systems, and International Journal of Information Security.

Inhalt

1 Leveraging machine learning techniques to analyse soil organic carbon dynamics in the Eastern
Himalayan Region
2 Investigation into a suitable voice pathology detection and classification using glottal inverse filtering
3 A hybrid approach for accurate fish segmentation: integrating Vision Transformer and MobileNetV2
Pradumn Kumar and Praveen Kumar Shukla
4 Predictive efficacy assessment of deep learning models for apple leaf disease detection and
classification
5 An investigation of machine learning algorithms for lung disease detection
6 Beyond characters: a machine learning approach to password strength analysis
7 Comparative analysis of machine learning-based specific capacitance prediction and experimental
validation of supercapacitive performance in cerium-based electrodes
8 Incremental learning using CART and Genetic Programming for handling dynamic training data
9 Exploring deep learning approaches for hate speech detection in Assamese social media text
10 Using sentiment analysis to enhance digital forensic evidence identification
11 Machine learning methods for improving stock price prediction accuracy
12 Effect of stop words in Assamese language for identifying toxic comments
13 Optimising low-resource Khasi NER through transfer learning
14 Localised detection of rice disease using YOLO 11: an advanced approach for precision agriculture
15 Assamese handwritten script segmentation using deep learning approach
16 Clustering of foods based on nutritional profile using principal component analysis and k-nearest
neighbor classification
17 Estimating crop yields using machine learning
18 Detection of sensitive information using CRF in unstructured text
19 A home-based skill improvement tool utilising smartphone sensors
20 Offline handwritten character recognition of Manipuri Script using convolutional neural
network (CNN) and vision transformer (ViT)
21 Denoising in Terahertz images
22 A novel ensemble rank aggregation feature selection algorithm for classification
23 Analysing the impact of Word2Vec on stance detection in low-resource languages:
a case study on Manipuri editorial articles
24 Robust MRI brain tumour segmentation using integrated mean shift clustering and
adaptive thresholding
25 Feature-driven classification of AI and human text: insights from traditional and neural models
26 A novel stacking ensemble machine learning approach for landslide susceptibility mapping
27 Advancements in network security threat detection systems for wireless sensor networks:
a review of machine learning and deep learning techniques
28 Comparison of machine learning, ensemble learning, and deep learning model for predicting
ovarian cancer: a data-driven study
29 Efficient crack classification through transfer learning with pre-trained convolutional
neural networks
30 Enhancing medical imaging diagnostics with federated learning: overcoming data heterogeneity
31 A hybrid deep learning model for accurate brain tumour segmentation and classification
using ResNet101 and U-Net
32 Evaluating machine learning models for precision disease prediction
33 Modelling stock prices using XGBoost, Prophet, and ARIMA: a comprehensive evaluation
34 Advancements in Sugarcane Disease Detection and Prediction
35 Impact of machine translation evaluation metrics on low resource languages
36 Artificial intelligence and entrepreneurship in the context of current socioeconomic
growth in India - an examination of the literature
37 An extended SMOTE-based class balancing technique to improve classification
accuracy on imbalanced datasets
38 AI-powered personalised learning and intelligent recommendation systems
39 Detection of diabetic retinopathy using deep-learning based image classification
40 In depth comparative analysis of the combine effect of ML models and feature selection
methods in crop yield prediction
41 Evaluating LLMs and pre-trained models for text summarisation across diverse datasets
42 Breast cancer classification using machine learning and deep learning: a systematic review
of WBCD-based research and future directions
43 Sentiment analysis on code-mixed data: a comprehensive, qualitative and quantitative
literature survey
44 Advanced fraud detection in financial transaction using machine learning
45 Efficient detection of offensive social media comments in Assamese language using LSTM

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