Enhancing the Operational Efficiency of FPOs by Using Predictive Model Building in Machine Learning Through Feature Selection Method
subject: feature selection method; FPO operational efficiency; FPO policy inputs; FPO shortcomings; predictive power
description: This study employs a machine learningbased feature selection approach to identify key factors that significantly enhance the predictive accuracy of models assessing farmer producer organization (FPO) performance. It focused on an FPO in the Anantapur and Kadapa districts of Andhra Pradesh, India; the research investigated the operational effectiveness of small and marginal farmers who are members by the end of 2022. The study reviewed existing shortcomings and proposed necessary policy amendments to ensure the sustainability of FPOs. The study utilized a survey design method, with the exploratory questionnaire through the field study. A sample of 73 small-scale producer farmers from the region was selected for the analysis. The result indicated that a) the reason for the operational efficiency of FPOs, b) the gradient boosting regressor achieved the highest testing accuracy of 0.78 to predict the best feature for FPO performance, and c) FPO insights for policy guidelines. 2025 Scrivener Publishing LLC.
creator: Sreelakshmi, P.; Basavaraj, Santosh; Josephine, V. L. Helen
source: Green Innovations in Computational Intelligence: Sustainable Strategies and Emerging Technologies;pp.159-187
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139438365-8; 978-139438361-0;
format: online
language: English
type: Book chapter
coverage: Sreelakshmi P., School of Business and Management (SBM), Christ University, Bangalore, India; Basavaraj S., School of Business and Management (SBM), Christ University, Bangalore, India; Josephine V.L.H., School of Business and Management (SBM), Christ University, Bangalore, India

Role of Graph Convolutional Neural Networks (GCNN) in Computer Vision Applications
subject: computer vision; Graph convolutional neural networks (GCNNs); graph-structured data; visual data analysis; visual information analysis
description: Graph Convolution Neural Networks (GCNNs) are an important concept in advancing computer vision by transforming the understanding and modeling of graph-structured data. They have a unique capability to capture intricate relations along with the visual content that goes beyond the traditional and usual convolutional neural networks, it also empowers computers to observe and interpret the complex interconnection between the elements in images, which enhances the depth and nuance of visual dentata analysis. As a revolutionary study in computer vision, GCNNs are poised to transform various industries by unleashing new frontiers in the visual information domains analysis and interpretation. Their multifaceted applications promise to reshape the landscape of computer vision. 2026 Scrivener Publishing LLC.
creator: Malini, A.; Sharma, Vandana; Felicia Lilian, J.; Dhanaraj, Rajesh Kumar; Sharangapriyan, S.; Shrinivas, S.
source: Graph Convolutional Neural Networks for Computer Vision;pp.1-20
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139435636-2; 978-139435633-1;
format: online
language: English
type: Book chapter
coverage: Malini A., School of Computer Science and Engineering, Vellore Institute of Technology, Tamil Nadu, Chennai, India; Sharma V., Christ University, Bengaluru, India; Felicia Lilian J., Department of Computer Science and Business Systems, Thiagarajar College of Engineering, Tamil Nadu, India; Dhanaraj R.K., Symbiosis Institute of Computer Studies and Research (SICSR), Symbiosis International (Deemed University), Pune, India; Sharangapriyan S., Department of Computer Science and Business Systems, Thiagarajar College of Engineering, Tamil Nadu, India; Shrinivas S., Department of Computer Science and Business Systems, Thiagarajar College of Engineering, Tamil Nadu, India

Generative AI for Next-Generation Recommender Systems: Architectures, Applications, and Future Directions
subject: Data sparsity; Explainable AI; Federated learning; Generative adversarial networks; Generative AI; Personalization; Recommender systems; Transformers; Variational autoencoders
description: The recommender systems have become a must in delivering personalized experiences across digital platforms. Still, traditional approaches, such as collaborative and content-based filtering, suffer from some inherent limitations: data sparsity, scalability, and dynamic user adaptation. In this context, generative AI emerges as a game-changing solution empowered by state-of-the-art models like variational autoencoders (VAEs), generative adversarial networks (GANs), and transformers to overcome the above-mentioned limitations. These models make possible the synthesis of user-item interaction data, uncovering latent patterns and providing context-aware recommendations, thereby redefining personalization in recommender systems. This chapter provides a detailed survey on the role of generative AI in recommender systems, their components, architectures, and applications. Case studies in e-commerce, entertainment, and education provide insights into how generative models help drive personalization, tackle the cold-start problem, and adapt dynamically to the evolution of user behaviors. Nevertheless, open issues regarding computational complexity, privacy protection, and ethical considerations remain. To address these, the chapter outlines the future enhancements in the areas of federated learning for privacy-preserving collaboration, multimodal data integration for holistic user profiling, and explainable AI frameworks to foster transparency and trust. Bridging these gaps would let generative AI-driven recommenders further revolutionize personalization, scalability, and inclusiveness, opening up a way to innovative solutions across the board in various industries. 2026 by John Wiley & Sons Inc. All rights reserved.
creator: Haseena, Shaik Valli; Jaswani, Neha
source: Next-Generation Recommendation Systems: A Comprehensive Guide to Enabling Technologies and Tools and their Business Benefits;pp.201-223
publisher: wiley
date: 01-01-2026
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139435157-2; 978-139435154-1;
format: online
language: English
type: Book chapter
coverage: Haseena S.V., Presidency College, Christ University, Bengaluru, India; Jaswani N., Presidency College, Bengaluru, India

Graph Neural Networks in Recommendation Systems for Superior User Experiences
subject: Graph Attention Networks (GATs); Graph Convolutional Networks (GCNs); Graph Neural Networks (GNNs); GraphSAGE; Recommendation systems
description: Recommender systems are now an essential tool for traversing huge amounts of online information, especially as user tastes change in dynamic settings. They can be classified into different types based on their use, such as collaborative filtering and content-based recommendation. Graph Neural Networks (GNNs), however, are best suited to learn from graph-structured data and have become a revolutionary technology in building recommendation systems based on their capacity to capture intricate relationships and dependencies in graph-structured data. Unlike traditional methods, GNN-based recommendation systems capture both local and global connectivity patterns in user-item interaction graphs, enhancing prediction accuracy and robustness. This study looks at key types of Graph Neural Networks, known as GNNs, and includes Graph Convolutional Networks (GCNs), Graph Attention Networks (GATs), and GraphSAGE. Each type is good at tackling specific challenges like making personalized recommendations, handling cold-start problems, and managing large-scale data effectively. Big companies across different industries are using GNNs to enhance their services. For example, e-commerce giants like Amazon and Alibaba, and streaming platforms like Netflix and Spotify, use these networks to boost user engagement and satisfaction. The study also covers strategies for applying GNNs. This includes constructing user-item bipartite graphs, including domain-specific features, and employing contrastive learning methods to improve functionality. By combining theoretical concepts with real-world usage, we hope to offer an informed view of GNNs in recommendation systems. In addition, metrics like Precision, Recall, and Normalized Discounted Cumulative Gain (nDCG), providing implementable recommendations for future development in this fast-moving field, will be addressed. 2026 by John Wiley & Sons Inc. All rights reserved.
creator: Upadhyay, Priyansha; Banu, P.K. Nizar
source: Next-Generation Recommendation Systems: A Comprehensive Guide to Enabling Technologies and Tools and their Business Benefits;pp.121-150
publisher: wiley
date: 01-01-2026
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139435157-2; 978-139435154-1;
format: online
language: English
type: Book chapter
coverage: Upadhyay P., Department of Computer Science, Christ University, Bangalore, India; Banu P.K.N., Department of Computer Science, Christ University, Bangalore, India

Market Trends in Quantum-Inspired Soft Computing for Intelligent Data Processing
subject: Hybrid computing models; Intelligent data processing; Market trends in QISC; Quantum-inspired soft computing (QISC)
description: Quantum-Inspired Soft Computing (QISC) is an advanced concept in computational intelligence in the current era of hi-technology, which has been adapted to principles underpinning quantum mechanics, including superposition and entanglement in the conven tional computing systems. The current chapter aims to identify the growing trends in the market environment concerning QISC for intelligence data processing, specifying the aspects of its applicability, costuse ratio, and adaptability among different industries. The increased need for the utilization of enhanced methods of data handling arising from big data and AI progress has made QISC viable for handling optimization problems, machine learning, and predictive modeling in addition to quantum computing. Major business sectors, such as finance, health care, supply chain, and energy sectors, have benefited from the use of QISC to enhance operational management, decision making, and system reliability. This chapter also discusses how leading players such as Microsoft, IBM, and DWave are in the course of incorporating QISC in cloud environments as well as in hybrid computing systems. Advancements in hardware, such as GPUs and quantum-inspired processors, and in algorithms, such as tensor networks and reinforcement learning, have further extended the usage of QISC. However, there are issues such as standardization, interdisciplinary qualified staff, and computational complexity, which remain important unsolved tasks for further investigation and cooperation. This chapter ends by briefly pointing out new directions for how QISC can work with AI for NLP and real-time analysis. Understanding QISC in terms of its current market and its positive impact on the future of computational intelligence is the focus of this chapter, which focuses on current market trends. Analyzing key trends and the degree of industry adoption, the research findings provide useful perspectives for academic, practical, and policy purposes. 2026 Scrive…
creator: Kapoor, Shubh; Garg, Vikas
source: Quantum-Inspired Approaches for Intelligent Data Processing;pp.173-200
publisher: wiley
date: 01-01-2026
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139433644-9; 978-139433641-8;
format: online
language: English
type: Book chapter
coverage: Kapoor S., School of Business and Management, Christ University, Bengaluru, India; Garg V., Symbiosis Institute of Business Management, Noida, Symbiosis International (Deemed University), Pune, India

AI Avatars in Immersive Environments for Communication Skill Training
subject: AI avatar interaction; AI avatars; AI technology; Artificial intelligence; Communication skill training; Virtual reality environments
description: In the contemporary landscape, communication skills are essential across different spheres, from professional spaces to personal engagements. AI-generated content is gaining popularity in education, which assists students in their assignments and other activities. With the advent and development of technology, AI avatars incorporated with virtual reality environments present a novel and promising pathway for cultivating communication abilities. VR environments are experimenting with AI technology that can create a more realistic environment and provide users with interactive characters around them. The education sector is widely using AI technology for interactive classrooms and presentations, which can improve students' creative communication skills. It is assumed that the AI sector is expected to grow by 48% in the future. The promising potentials of the technology attract more users into the medium as it allows for customization, dynamic assessment patterns, a hybrid learning mode with meaningful interactions, and blended learning experiences. This chapter delves into the potential of AI avatars in virtual reality environments, especially communication skill training applications that help improve communication skills. AI avatars create an interactive space for the users in VR environments that creates an engaged space for the users to be involved in conversations and activities without the fear of being judged. The present study takes an experimental approach with the social learning theory to test whether these AI avatars help users improve communication skills, mainly interpersonal communication skills and public speaking. A mixed methodology is adopted for the research, where data collected from the training and questionnaire data will undergo triangulation to get the appropriate results. The research also addresses ethical considerations like privacy and inclusivity in AI avatar interactions. Overall, the study highlights the effectiveness of incorporating A…
creator: Joseph, Twinkle Sara; Kunnumpurath, Biju; Bhojan, Anand; Mahalakshmi, J.
source: Virtual Reality and Augmented Reality with 6G Communication;pp.291-327
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139433608-1; 978-139433605-0;
format: online
language: English
type: Book chapter
coverage: Joseph T.S., Department of Media Studies, Christ University, Bengaluru, Karnataka, India; Kunnumpurath B., Department of Media Studies, Christ University, Bengaluru, Karnataka, India; Bhojan A., Department of Computer Science (School of Computing), National University of Singapore, Singapore; Mahalakshmi J., School of Sciences, Christ University, Bengaluru, Karnataka, India

Enhancing Heritage and Cultural Education through Immersive Audio-Visual Techniques
subject: Augmented reality, 3D soundscapes; Cultural heritage; Immersive media; Interactive learning, 6G technology; Virtual reality
description: Growth in immersive media technologies offers unique opportunities for improved learning experiences. This is important in understanding and preserving heritage and cultural elements. The establishment of hybrid classrooms and the adoption of technologies like virtual reality (VR), augmented reality (AR), and artificial intelligence (AI) make the learning experience more immersive and interactive. These experiences can lessen the differences between theoretical and emotional connections which also help learning to be more impactful and effective. This chapter examines how immersive technologies such as audio-visual technology can change the heritage and cultural education of people across diverse ages. The chapter discussed both 3D soundscapes and visual imagery in relation to VR/AR applications and how well these elements are integrated into a unified whole, which provides some interesting immersive cultural heritage education experiences. This study also analyzes use cases such as virtual museum tours with immersive audio-embedded recreations of historical environments, AR-enhanced archaeological site visits supported by ambient sounds, and interactive cultural heritage simulations guided by spatial audio. It further explores successful research integrating 3D soundscapes into AR/VR use cases. These applications highlight potential VR/AR educational contexts where audio-visual enhancement provides multisensory learning that encourages engagement and cognition surrounding heritage and cultural elements. The study also covers the benefits of this approach like increased public engagement with cultural sites and artifacts, improved retention of historical information, and enhanced accessibility to cultural experiences. Ultra-low latency, higher connectivity, and high-speed data transfer would mean that the quality and accessibility offered by 6G will be on another level altogether. On the other hand, AI can bring immersive experiences along with customization, immedi…
creator: Paul, Ajith; Kunnumpurath, Biju; Balakrishnan, C.; Ramachandran, Selvakumar; Suseelan, Anitha
source: Virtual Reality and Augmented Reality with 6G Communication;pp.245-269
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139433608-1; 978-139433605-0;
format: online
language: English
type: Book chapter
coverage: Paul A., Department of Media Studies, Christ University, Bengaluru, India; Kunnumpurath B., Department of Media Studies, Christ University, Bengaluru, India; Balakrishnan C., Department of Computer Science, Christ University, Bengaluru, India; Ramachandran S., Department of Continuing Education, University of Oxford, Oxford, Oxfordshire, United Kingdom; Suseelan A., School of Architecture, Christ University, Bengaluru, India

Study of Optimization Techniques in Agriculture
subject: AI advancements; Data exchange; Deep learning; Efficiency; Innovation; Integration; IoT; Transformative change
description: In agriculture, optimization strategies are essential for raising production, sustainability, and resource efficiency. This abstract explores several agricultural optimization approaches and highlights their importance in contemporary farming operations. Obstacles to traditional agricultural operations include climate change, resource constraint, and shifting consumer preferences. Through the application of cutting-edge technologies and rigorous scientific methods, optimization strategies provide answers to these problems. Precision agriculture, which uses data-driven techniques like remote sensing, Geographic Information System (GIS), and Global Positioning System (GPS) to customize farming procedures to particular field conditions, is one important area of optimization. This helps farmers to maximize yields while minimizing waste and the environmental effect of inputs like water, fertilizer, and pesticides. In addition, optimization methods include selective breeding for genetic advancements and biotechnology, with the goal of creating crops with increased nutritional value, disease resistance, and production potential. Under the category of optimization approaches are integrated pest management solutions, which efficiently control pests and illnesses while using less chemical pesticides by applying ecological principles. In summary, agricultural optimization approaches offer a comprehensive strategy to tackle the issues that contemporary farming faces, encouraging resilience, productivity, and sustainability in food production systems. Given the changing global agricultural dynamics, it is imperative that these strategies be further researched and used in order to ensure environmental stewardship and food security. 2026 Scrivener Publishing LLC. All rights reserved.
creator: Nanjundan, Preethi; Indu, P.V.; Thomas, Lijo
source: Driving Innovation by Dynamic Optimization: The Challenges of Reshaping Industry;pp.485-508
publisher: wiley
date: 01-01-2026
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139431572-7; 978-139431569-7;
format: online
language: English
type: Book chapter
coverage: Nanjundan P., Department of Data Science, CHRIST University, Pune Lavasa Campus, Pune, India; Indu P.V., Department of Data Science, CHRIST University, Pune Lavasa Campus, Pune, India; Thomas L., Department of Data Science, CHRIST University, Pune Lavasa Campus, Pune, India

Integration of Industrial Robots to Enhance Warehouse Efficiency in an Industry 4.0 Environment Using Digital Twin Technology
subject: CODESYS; digital twin; factory IO; industrial robots; Industry 4.0; sequential function chart; sustainable manufacturing; warehouse automation
description: An automated warehouse serves as a facility designed for the storage of materials with a comprehensive inventory management system. This system meticulously monitors the loading and unloading of materials with minimal human intervention. The core operations within an automated warehouse are executed through the utilization of sophisticated software tools. This specific system falls within the purview of Manufacturing Execution Systems (MES). The integration of industrial robots is a pivotal aspect of warehouse automation, serving to meet the demands of efficiency while simultaneously reducing space requirements and overall operational costs within the warehouse management system. Industrial robots excel in executing processes swiftly and with precision, enhancing overall operational efficiency. This paper outlines the authors approach, which involves the programming of an industrial controller and the utilization of an Industry 4.0 Application Programming Interface (API) to facilitate communication with a 3D warehouse in Factory IO for loading materials. The programming of the industrial controller is carried out using the Sequential Function Chart (SFC) language, adhering to the IEC61131-3 standard. 2026 Scrivener Publishing LLC.
creator: Pounraj, Manikandan; James Periyanayagam, L.; Lobo, Jennifer Pearline; Ashwitha, P.
source: Integrated Systems: Embedded, Signal Processing, and Communication;pp.1-11
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139431176-7; 978-139431173-6;
format: online
language: English
type: Book chapter
coverage: Pounraj M., Centre of Excellence in Automation, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India; James Periyanayagam L., Centre of Excellence in Automation, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India; Lobo J.P., Centre of Excellence in Automation, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India; Ashwitha P., Centre of Excellence in Automation, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India

Green Finance and Sustainability: Landscape of Indian Financial Institutions
subject: Climate risk management; Corporate sustainability; ESG; Green Climate Fund; Green finance; Renewable energy; Sustainability
description: Today, green finance and sustainability have become integral parts of the global financial landscape, and it is the Indian financial institutions that are leading the way. This chapter delves into the intricate landscape of green finance and sustainability in Indian financial institutions. It focuses on regulation, green bonds, sustainable banking, public and private sector initiatives, and the challenges and opportunities they present. The Reserve Bank of India (RBI) and the Securities and Exchange Board of India (SEBI) are at the forefront of these initiatives. The RBI, for instance, is already taking significant steps, such as incorporating sustainability into its policy framework, by considering renewable energy in its priority sector lending norms. SEBI, conversely, has made it mandatory for all listed companies to disclose their ESG practices under the Business Responsibility and Sustainability Reporting (BRSR) framework, a move that promotes transparency and sustainable practices. Green bonds are a potent financial instrument for directing capital toward environmentally sustainable projects. In India, the Indian Renewable Energy Development Agency and several banks have proactively issued green bonds to finance renewable energy, energy efficiency, and clean transportation projects. The State Bank of Indias issuance of its first green bond in 2018, raising USD 650 million for a green project, is a testament to SBIs dedication to sustainable finance and a model for other financial institutions. Indian banks are increasingly integrating environmental, social, and governance (ESG) criteria, a set of standards for a companys operations that socially conscious investors use to screen potential investments in their lending and investment decisions fostering longterm green banking practices. They also provide green loans for projects with positive environmental impacts and incorporate climate risk assessment into their risk management frameworks driven by regulatory …
creator: Hridhya, P.K.; Desai, Kavitha; Ananthan, Sriram; Manickam, Thirupathi; Devaraja Nayaka, K.; Joel Jebadurai, D.
source: Financial Innovation for Global Sustainability;pp.359-383
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139431168-2; 978-139431165-1;
format: online
language: English
type: Book chapter
coverage: Hridhya P.K., Department of Professional Studies, Christ University, Karnataka, Bangalore, India; Desai K., SVKMs Narsee Monjee Institute of Management Studies, Karnataka, Bangalore, India; Ananthan S., Department of Business Management, Western Community College, Vancouver, BC, Canada; Manickam T., College of Business, University of Buraimi, Al Buraimi Governorate, AI Buraimi, Northern part of Oman, Oman; Devaraja Nayaka K., College of Business, University of Buraimi, Al Buraimi Governorate, AI Buraimi, Northern part of Oman, Oman; Joel Jebadurai D., Department of MBA, St. Josephs College of Engineering, Tamil Nadu, Chennai, India

Customer Acceptance of Sustainable Fintech Innovation: A Study from an Indian Customer Perspective
subject: And customer acceptance; FinTech; Perceived relief; Perceived usefulness; Sustainable development
description: Financial technology, or FinTech, aims to simplify and enhance financial services. FinTech is frequently referred to as financial technology. The customers day-today financial operations, processes, and existence are all significantly impacted by the financial transactions that they engage in. Although there has been a notable rise in the literacy rate among Indian consumers in the last 20 years, financial literacy seems to still be in its nascent phase. Hence, the research investigates the determinants that impact the adoption of FinTech services, which include a range of societal, ecological, and environmental advantages. This research presents a comprehensive model that expands on the TAM model by including reported relief as a mediator and perceived ease of use as an independent variable. The study also takes into account consumer acceptance as the dependent variable. Through quantitative approaches, a total of 253 responses have been collected from Indian citizens from online chatrooms and financial education sites. A Google Form link has been shared with the students and participants in these online chatrooms. After some time had passed, the quantitative data were evaluated using SmartPLS by employing the approach of partial least squares. The research findings indicate that consumers perception of the usefulness and alleviation provided by sustainable fintech services greatly influence their overall adoption of these services. The research conducted a moderation analysis utilizing the PLS-MGA technique to determine whether generation, Gen Z or Gen Y, had a significant moderating impact and shown more willingness to use FinTech services. Eventually, the research offered practical recommendations for managers to provide suitable, dependable, and enduring services to clients at a fair price that aligns with their needs and eventually enhances their psychological well-being. 2025 Scrivener Publishing LLC.
creator: Yadav, Pinnika Syam; Kiran, P.B. Narendra; Sharma, Abhishek; Vemula, Rajesh; Shrama, Ankitha
source: Financial Innovation for Global Sustainability;pp.337-357
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139431168-2; 978-139431165-1;
format: online
language: English
type: Book chapter
coverage: Yadav P.S., School of Business and Management, Christ University, Bengaluru, India; Kiran P.B.N., School of Business and Management, Christ University, Bengaluru, India; Sharma A., Mittal School of Business, Lovely Professional University, Punjab, Jalandhar, India; Vemula R., School of Business and Management, Christ University, Bengaluru, India; Shrama A., Mittal School of Business, Lovely Professional University, Punjab, Jalandhar, India

Efficient Load Balancing and Resource Allocation in Networked Sensing SystemsAn Algorithmic Study
subject: AI algorithms; energy efficiency; Load balancing; machine learning; performance optimization; resource allocation
description: In the current environment, data generation and data transmission are increasing exponentially in day-to-day life. These exponentially growing data might create heavy traffic when transmitted between systems. Also, this affects many functionalities like configuration of networked systems, system and routing configuration parameters, load managing factors of network devices, etc. A dynamic traffic control mechanism needs to be adopted with the help of load-balancing algorithms and efficient resource allocation mechanisms to deal with heavy data traffic. Load balancing algorithms in networked sensing systems aim to distribute the workload evenly among sensor nodes to optimize network performance and energy efficiency and prolong the network lifetime. Resource allocation mechanisms in a networked sensing system involve allocating and distributing network resources efficiently, such as energy, bandwidth, processing power, etc., to optimize performance and increase the networks lifetime. To achieve efficient resource allocation with a balanced load, notable works have been done in optimization and machine learning. The work gives a scientific analysis of traditional and Artificial Intelligence algorithms from a centralized and distributed perspective. Researchers can take this analysis forward when deciding on algorithms based on their application and infrastructural needs. 2025 Scrivener Publishing LLC.
creator: Krishnasamy, Lalitha; Vetriveeran, Divya; Sambandam, Rakoth Kandan; Jenefa, J.
source: Networked Sensing Systems;pp.145-171
publisher: wiley
date: 01-01-2025
rights: All Open Access; Gold Open Access
relation: ISBN: 978-139431089-0; 978-139431086-9;
format: online
language: English
type: Book chapter
coverage: Krishnasamy L., Department of Artificial Intelligence & Data Science, Nandha Engineering College, Tamil Nadu, Erode, India; Vetriveeran D., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Kengeri Campus, Bengaluru, India; Sambandam R.K., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Kengeri Campus, Bengaluru, India; Jenefa J., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Kengeri Campus, Bengaluru, India

Artificial Intelligence and Machine Learning Applications in Threat Detection
subject: Artificial intelligence (AI); Banking; Education; Finance; Healthcare; Machine learning (ML); Self-driving cars; Threat detection
description: Artificial intelligence (AI) and machine mastering (ML) have emerged as progressive breakthroughs in medical prognosis, especially in the area of early most cancers diagnosis. These trendy gadgets significantly enhance the accuracy and performance of tumor detection. By analyzing huge records units, synthetic intelligence structures can identify small styles and anomalies in medical imaging, which lets in malignant tumors to be recognized earlier and greater appropriately than traditional methods. AI and ML are needed to accelerate tumor analysis and category in the context of most cancers remedy. These technologies assist doctors quickly perceive any abnormalities in radiological pictures inclusive of X-rays, MRIs and CT scans. Artificial intelligence reduces the workload of clinical specialists through automating this manner, enabling faster and greater correct analysis. In addition, AI can assist tailor remedy packages contemplating a patient's specific records, maximizing treatments and predicting remedy outcomes. In addition to improving the performance and speed of diagnosis, the aggregate of AI and ML in tumor detection suggests the capability to boom the general effectiveness of cancer treatment and in the end enhance affected person consequences. 2025 Scrivener Publishing LLC.
creator: Indu, P.V.; Nanjundan, Preethi; Thomas, Lijo
source: Protecting and Mitigating Against Cyber Threats: Deploying Artificial Intelligence and Machine Learning;pp.41-56
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139430521-6; 978-139430522-3;
format: online
language: English
type: Book chapter
coverage: Indu P.V., Department of Economics and Analytics, Christ University, Pune, India; Nanjundan P., Department of Data Science, Christ University, Pune, India; Thomas L., Department of Psychology, Christ University, Pune, India

Blockchain for Enhancing Security and Privacy in the Smart Healthcare
subject: Blockchain; privacy; security; smart healthcare
description: The rapid digitalization of healthcare systems and the growing integration of smart technologies have made robust security and patient privacy protection critical concerns. Traditional healthcare systems struggle with maintaining the confidentiality, integrity, and accessibility of sensitive patient data. This section explores how blockchain technology can serve as a transformative solution to address these challenges and elevate security and privacy standards in smart healthcare environments. Blockchain, a decentralized and tamper-resistant distributed ledger technology, offers a novel approach to secure data sharing and storage. In the realm of smart healthcare, blockchain can establish a transparent and immutable record of patient information, medical history, and treatment plans, ensuring data integrity by thwarting unauthorized modifications and tampering. The cryptographic features inherent in blockchain provide a strong basis for safeguarding patient privacy. Smart contracts, which are programmable and self-executing scripts on the blockchain, enable precise access control, permitting only authorized entities to access specific patient data. Additionally, the utilization of decentralized identifiers (DIDs) and verifiable credentials enhances patient identity management, mitigating the risks of identity theft and unauthorized access. This section also delves into case studies and ongoing initiatives leveraging blockchain in smart healthcare applications. From electronic health records (EHRs) and interoperability to medical supply chain management, the adoption of blockchain technology showcases promising outcomes in enhancing security, transparency, and privacy. Various challenges and potential drawbacks of implementing blockchain in healthcare are also explored in this section. In conclusion, the integration of blockchain technology in smart healthcare holds significant potential for transforming data security and privacy practices. As the healthcare sector e…
creator: Tyagi, Amit Kumar; Seranmadevi, R.
source: Digital Twin and Blockchain for Smart Cities;pp.343-370
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139430356-4; 978-139430353-3;
format: online
language: English
type: Book chapter
coverage: Tyagi A.K., Department of Fashion Technology, National Institute of Fashion Technology, New Delhi, Delhi, India; Seranmadevi R., Department of Professional Studies, Christ University, Karnataka, Bangalore, India

Study of State-of-the-Art Performance Metrics in NLP: Specifically for Text Summarization in the Medical Domain Using the SumPubMed Dataset
subject: BERT scores; Metrics; NLP; SUPERT; Text summarization
description: Text summarization is becoming very important given the number of documents produced each year across domains. In this paper we explore the various traditional metrics for text summarization, such as ROUGE, BLEU, METEOR, etc., and look at improving the performance of the existing metric by taking the stateof-the-art untrained metric SUPERT, and clubbing it with a readability score and a penalty for long summaries. The SUMPUBMED dataset was used for this research and a BERT extractive summarizer was used for generating the summaries. It was found that using a readability score with an unsupervised metric such as SUPERT helped in assessing the quality of the summary more accurately than earlier metrics. We compared the metrics such as SUPERT scores and BERT scores with and without involving the human annotated summaries in the SUMPUBMED dataset and found that untrained metrics perform better than when involving a reference annotated summary. 2025 Scrivener Publishing LLC.
creator: Sridhar, M.; Irfan, Mohammad; Kathirmani, Sukumar
source: Generative AI: Disruptive Technologies for Innovative Applications;pp.91-106
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139430293-2; 978-139430290-1;
format: online
language: English
type: Book chapter
coverage: Sridhar M., NSB Academy, Business School, Bangalore, India; Irfan M., Christ University, Bangalore, India; Kathirmani S., Quelit Innovations Pvt Ltd, Chennai, India

Smart Wound Guard
subject: automatic drug delivery; chronic wounds; faster wound healing; flexible plaster; real-time monitoring; Wearable electronics
description: Traditional wound healing processes suffer from a lack of real-time monitoring, often relying on subjective assessments, leading to missed opportunities for timely treatment adjustments. This idea proposal is particularly concerning for patients with chronic wounds, as traditional dressings fail to provide essential information on wound conditions. To address this gap, wearable electronics are emerging as a promising solution. This context proposes the development of a flexible plaster embedded with electronics capable of sensing various wound-related factors such as pH, temperature, glucose, uric acid, moisture, oxygen, and protein levels in both the wound and its surrounding environment. By continuously monitoring these factors and providing alerts, this innovative solution aims to facilitate faster wound healing. Moreover, it enables automatic drug delivery, enhancing treatment efficacy and patient outcomes. This approach represents a significant advancement in wound care, offering real-time insights and interventions that can revolutionize how wounds are managed, ultimately improving patient care and reducing healthcare costs.
creator: Nagaraj, S.
source: Smart Textiles and Wearables for Health and Fitness;pp.121-136
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139430289-5; 978-139430294-9;
format: online
language: English
type: Book chapter
coverage: Nagaraj S., Christ University, Karnataka, Bangalore, India

Leveraging Deep Learning for Early Detection of Autism Spectrum Disorder in Augmented and Virtual Reality Mental Healthcare Environments
subject: augmented reality; Autism spectrum disorder; deep learning; early detection; mental healthcare; virtual reality
description: The advent of digital health interventions offers new vistas for the early detection and management of autism spectrum disorder (ASD). This paper explores the innovative application of deep learning algorithms within augmented reality (AR) and virtual reality (VR) environments to enhance the early detection of ASD. Integrating AR and VR in mental healthcare provides immersive, controlled settings in which individuals behaviors and responses can be observed and analyzed in real time. We propose a novel framework that utilizes deep learning techniques to process and analyze the data collected from these digital environments. Our approach leverages facial expression analysis, eye tracking, and behavioral pattern recognition to identify early signs of ASD. By capturing subtle nuances in behavior often overlooked in traditional diagnostic settings, our method offers a non-invasive, engaging, and efficient alternative for early ASD detection. The potential of this technology extends beyond diagnosis, offering possibilities for personalized intervention strategies that can be adapted to each individual's unique needs. Our findings indicate that deep learning in AR and VR environments could significantly enhance the accuracy and timeliness of ASD diagnosis, paving the way for earlier and more effective interventions. This study underscores the importance of interdisciplinary collaboration in developing innovative healthcare solutions, combining the fields of artificial intelligence, psychology, and digital media to improve outcomes for individuals with ASD. 2026 Scrivener Publishing LLC.
creator: Lamani, Manjunath Ramanna; Asha, V.; Padmaja, K.
source: Augmented and Virtual Reality in Immersive Healthcare;pp.151-173
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139430286-4; 978-139430284-0;
format: online
language: English
type: Book chapter
coverage: Lamani M.R., Department of CSE, CHRIST University, Kanmanike, Kumbalgudu, Karnataka, Bangalore, India; Asha V., Dept of CSE, RNS Institute of Technology, Karnataka, Bengaluru, India; Padmaja K., Dept of ISE, GSSSIETW, Karnataka, Mysore, India

Healthcare Metaverse
subject: artificial intelligence; augmented reality; blockchain; digital twins; immersive technologies; IoT; Metaverse
description: Discussions regarding metaverse technologies are happening all over the place, from universities to business tycoons. A lot of people are thinking about how to make their apps work better in the metaverse. To better serve their patients, more and more healthcare firms are embracing the metaverse. In this research, healthcare metaverses are examined. We show how to improve healthcare services in the metaverse and increase patient use cases by using safer approaches to managing chronic diseases, mental health, and fitness. With the advent of digital twins, artificial intelligence (AI), immersive technologies, the Internet of Things (IoT), and blockchain (BC), new possibilities in healthcare are emerging in the metaverse. These innovations have the potential to change the way people perceive healthcare, save costs, and enhance patient outcomes. Healthcare may be revolutionized by using AI and BC technology to sift through massive amounts of data and develop individualized treatment regimens. But IoT devices gather vital data for patient therapy instantly. The healthcare system and people's lives throughout the globe may both benefit from these concepts coming together. The recommendations made in this article should be adhered to ensure that digital procedures continue to benefit customers. 2026 Scrivener Publishing LLC.
creator: Sivadevuni, Sreeparnesh Sharma; Naveen, J.
source: Augmented and Virtual Reality in Immersive Healthcare;pp.499-512
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139430286-4; 978-139430284-0;
format: online
language: English
type: Book chapter
coverage: Sivadevuni S.S., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, Bangalore, India; Naveen J., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, Bangalore, India

Meditating in VR
subject: immersion; Meditation; perceived interactivity; positive thinking; psychological well-being; VR; young adults
description: This chapter examines how immersion in virtual reality (VR) affects the psychological well-being, perceived interactivity, and positive thinking of young adults. Using a questionnaire adapted from Katy Tcha-Tokey's VR survey and established scales by Sally J. McMillan, Jang-Sun Hwang, and Diener, data was collected from 224 students at Christ University. Participants engaged in a VR meditation session using Meta Quest 2 headsets. Results indicated stronger correlations between immersion and psychological well-being (r = 0.511) and positive thinking (r = 0.485) compared to perceived interactivity (r = 0.319). Regression analyses confirmed immersion's predictive power for psychological well-being (? = 0.511, R2 = 0.261) and perceived interactivity (? = 0.485, R2 = 0.236), with lesser impact on positive thinking (R2 = 0.101). The study suggests that VR immersion notably influences psychological well-being and perceived interactivity among young adults. 2026 Scrivener Publishing LLC.
creator: Kunnumpurath, Biju; Paul, Ajith; Menon, Vishnu Achutha
source: Augmented and Virtual Reality in Immersive Healthcare;pp.475-497
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139430286-4; 978-139430284-0;
format: online
language: English
type: Book chapter
coverage: Kunnumpurath B., Department of Media Studies, CHRIST (Deemed to be University), Bengaluru, India; Paul A., Department of Media Studies, CHRIST (Deemed to be University), Bengaluru, India; Menon V.A., Department of Education, Institute for Educational and Developmental Studies (IEDS), Uttar Pradesh, Noida, India

From Concept to Clinic
subject: augmented reality; Autism; autism devices; autism diagnosis; autism spectrum disorder; virtual reality
description: Virtual reality (VR) is an innovative technology with various applications in fields such as simulation, gaming, sports, and entertainment. VR technology has extended its reach into the medical industry, leveraging computer-generated information and visuals to simulate real-world sensory experiences. Augmented reality (AR) is an expertise that covers computer-generated virtual objects onto the real world when it is seen through mobile phones, tablets, or AR glasses. VR and AR have started popular in 2016. Autism spectrum disorder (ASD) is a many-sided neurodevelopmental condition and is caused because of difficulties in social interaction, communication, and iterative behavior. ASD is increasingly predominant globally, touching roughly 2 in 100. If there is timely diagnosis and intervention, then there will be fewer problems. In recent years, AR and VR technologies have become one best option and novel means in the analysis and treatment of autism. Controlled environments that can imitate real-life social situations, contribution clinician's critical insights into the perceptions, and interactions of individuals with ASD in relation to their surroundings will be provided by AR and VR. These technologies assist customized intermediations, rendering them extremely adaptable to the distinct requirements of each individual. 2026 Scrivener Publishing LLC.
creator: Prasad, Smrity; Senthil Vadivu, M.
source: Augmented and Virtual Reality in Immersive Healthcare;pp.381-392
publisher: wiley
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 978-139430286-4; 978-139430284-0;
format: online
language: English
type: Book chapter
coverage: Prasad S., Department of Statistics and Data Science, CHRIST University, Karnataka, Bengaluru, India; Senthil Vadivu M., Department of Statistics and Data Science, CHRIST University, Karnataka, Bengaluru, India