bluuebunny/crossref_metadata_2025 huggingface dataset:
Transformational Leadership
Authors: Mudd-Fegett Kimberly , Mudd Helen K.
Published: July 2024

Transformational leadership is the process in which leaders play an idealized role model, stimulate and encourage innovative work behavior, provide inspirational motivation, engage in supporting and mentoring followers to achieve the organization's shared vision and goals, and create a connection that raises the level of motivation and morality in both the leader and the follower. This type of leader is attentive to the needs and motives of followers and supports each follower in reaching their fullest potential. The authors' experiences and success as transformational leaders and educators provide evidence of the truth of these findings. The authors will highlight personality characteristics, behaviors, and effects on practitioners, professors, and students of transformational leadership. The authors will show how transformational leaders and educators move followers from unquestioningly accepting provided information and directives to reflective, goal-oriented, critical thinkers.
International Field Education Through the Lens of Cultural Humility
Authors: Tokpa Lisa M. B.
Published: July 2024

With the challenges facing our society today, it is critical that opportunities be provided for social work students to learn about difference, and how to work effectively with diverse populations. International field education is one important way to provide these opportunities to students in an immersive setting. The Uganda Studies Program provides experiential knowledge in this through a framework of cultural humility. Grounded in educational standards, the author presents considerations, challenges, and learning opportunities within cross-cultural exchanges. Power dynamics embedded in such exchanges are explored, and a challenge is presented to move towards active participation in redressing inequalities through mutually beneficial partnerships. A case is made, and a guide provided for American social work programs to adhere to its ethical mandate and responsibility to decolonize international field education in ways that support indigenous social work, local supervisors, and academicians, while simultaneously providing quality, competency-based student learning outcomes.
Affectagogy
Authors: Chee Ken Nee
Published: July 2024

This chapter unveils Affectagogy, a transformative pedagogical approach that bridges the emotional and cognitive realms of learning. Recognizing the undeniable influence of emotions on knowledge acquisition, Affectagogy emphasizes the concept of learning with the heart to nurture knowledge through emotional bonds. It explores the synergistic relationship between affect (emotions and feelings) and pedagogy (teaching methods). The chapter introduces “human-touch learning,” highlighting the significance of empathy, social interaction, and resilience-building in fostering deeper student engagement, motivation, and well-being. Practical guidelines are provided for implementing Affectagogy across educational levels, encompassing the thoughtful integration of educational technology. Ultimately, this chapter advocates for a holistic approach to education, emphasizing the cultivation of both emotional and intellectual intelligence. This balanced approach aims to prepare learners for success in an emotionally intelligent world, fostering resilience, empathy, and a lifelong love of learning.
Experiential Learning in the Digital Classroom to Improve Outcomes Related to Diversity, Equity, and Inclusion
Authors: Lunsford Lauren , Nelms Amanda , Barton-Arwood Sally
Published: July 2024

The purpose of this chapter is to explore the utility and process for integrating an experiential service-learning experience that promotes diversity and inclusion into an online learning environment. Experiential education and service-learning opportunities have been found to be a successful means for students to interact with individuals from different backgrounds and improve their cultural awareness. Given the promise for experiential education to address and improve outcomes related to DEI, it is worthwhile to investigate ways to integrate these activities into online courses. This chapter aims to: (1) introduce the benefits of experiential education and rationale for its inclusion as a practice to improve outcomes related to diversity and inclusion, (2) provide an overview of the potential of e-service learning as a means to do this, (3) share an example e-service-learning project
Enhancing Business Value Creation in Software Projects Through Analytic Hierarchy Process (AHP)
Authors: T. Praveen Kumar , A. Mansurali
Published: July 2024

Effective methodologies for optimizing business value creation in software projects are needed in the dynamic landscape of the software sector. The use of the AHP as a powerful decision-making tool to improve business value from software projects is explored in this chapter. A complete overview of the challenges faced by organizations in software development shall be given at the start of this chapter. AHP emerges as a viable solution, offering a structured framework to evaluate and prioritize criteria that contribute to business value creation. The chapter introduces the basic principles of AHP, explains its hierarchical structure and pairwise comparison methodology in an effort to set the stage. The practical application of AHP in the software project lifecycle is the next section of the chapter. Critical aspects in which AHP could have a significant impact on value creation are assessed as stakeholder involvement, priority for requests, and allocation of resources. Finally, the chapter underlines the transformative impact of AHP on creating business value from software projects.
Envisioning Decent Work and Sustainability in Enterprises
Authors: DasGupta Manidipa , Shaw Sandhya Kri , Majumder Sumanta
Published: July 2024

The key role of decent work for all in achieving sustainability is to create a balance between economic, environmental, and social needs. The present study, henceforth, takes its aims at envisioning a bibliometric analysis on the domain of decent work in the sustainability scenario during the 21st century where productivity, citation, and trends in publication along with author's keyword trends are considered based on Scopus e-database and Web of Science e-database with R-Packages. The findings of this bibliometric study demonstrate that decent work in sustainability gradually started attracting the attention of researchers from 2016 where both developed and developing countries were found to dominate. Amongst the countries, Spain, Australia, and the United Kingdom were detected as the promising ones with their productivity of publication in this domain. Furthermore, the study notices that up to 2015 literature mainly focused on the human rights dimension of decent work in sustainability with different themes. Hence, the study is considered a source of knowledge to know the existing literature trends and future research directions which would help marketers, entrepreneurs, academicians, and scholars to build up interest and to explore research aptitude in this emerging area.
Strategic Green Accounting and CSR Analytics
Authors: Juneja Gopika , Saraswat Pranav , Kautish Sandeep Kumar
Published: July 2024

Green accounting is a system that integrates the costs and the benefits attached with the environment. It shows the inclusion of such costs and benefits in the traditional accounting strategies and their methodology. Including the advantages and disadvantages, it becomes of vital impact to discuss the effect of green accounting on financial statements and its analysis. Green accounting strategies come of great benefit to the customers, public, investors, as they get a complete image of the company. The investors are informed of the reaped advantage, policies followed, reduction in risk, and optimum resource allocation. Many firms strategize in such alignments to increase their customer base and attract more customers on the basis of analytics. Other stakeholders like NGOs and other promotional firms get complete access to such information which leads to increase in the disclosure requirement of the companies. Hence, many investors, having rights in the shareholding, compel the management to follow such steps for the betterment of the society.
The Impact of ESG Investments on Global Economies for Corporate Success
Authors: Saraswat Pranav , Juneja Gopika , Kautish Sandeep
Published: July 2024

ESG investments have been very impactful on the financial markets, global economies, and have been one of the emerging reasons of corporate success. The increased demand in such investments shows a strategic shift or a potential change in the investor priorities and showcases the changing portfolio analytics. The new investment portfolio strategies are aligned with ethical and green investments analysis. Ethical and society friendly approaches by the investors have led to increases in the ESG investment funds, marking a substantial increase in the ESG assets. The European Fund Management shows 60% adoption of ESG integration over the past decades. The past trends of investing strategy included more return or profit-based approach, but now more focus is on the overall development of the company. This shows a positive move not only in the investment and portfolio planning but it also provides a broader analysis of societal consciousness and the will to reshape the traditional market in a better way.
A Combinatorial Predictive Method for Fraud Identification to Uphold Security and Data Integrity
Authors: Anitha A. , Nair Anjana , Kamaraj Balakrishnan
Published: July 2024

With the prevalence of digital transactions and customer interactions in today's industry, there has been a significant increase in demand for systems that can detect fraud. Fraud detection is the process of finding and stopping illegal or dishonest activities, usually related to money. Identifying fraudulent behavior accurately and quickly is one of the biggest issues facing the retail industry. This study focuses on the relationship between fraud detection and retail optimization in order to protect profits and improve efficiency. The study suggests a predictive analytics strategy specific to the industry by fusing contextual data, past transaction data, and customer behavior patterns in an innovative way by utilizing machine learning techniques. Retailers can improve inventory management, pricing strategies, and resource allocation by applying the insights gleaned from these models. Because of ethical concerns, this study emphasizes the use of customer data to identify fraudulent activity while maintaining confidentiality and integrity.
Juncture of Data Analytics and Data Governance
Authors: Singh Bhupinder , Kaunert Christian , Malviya Rishabha , Gautam Ritu
Published: July 2024

Organizations aim to adopt data-driven approaches due to the potential for deeper insights and more informed decision-making. This is particularly evident in the realm of big data, which encompasses vast and intricate datasets exceeding the capacities of conventional data processing software. Despite the transformative potential of insights derived from big data, many businesses struggle with processing, analyzing, and effectively utilizing this resource, even amidst the widespread acknowledgment of big data analytics in the context of digital transformation. Big data analytics revolutionizes marketing strategies by offering profound insights into market segments, customer behaviors, and preferences. It facilitates experimentation with new products, marketing approaches, and pricing strategies, enhancing the user experience and optimizing campaign effectiveness. Through individualized targeting and personalized marketing initiatives driven by analytics, organizations can tailor their offerings to specific customer preferences, maximizing engagement and conversion rates. This chapter comprehensively explores the big data analytics transforms organizational processes across IT infrastructure management and marketing strategies, enabling data-driven decision-making and providing a competitive advantage in dynamic business landscape.
Data-Driven Excellence
Authors: V. Harish , A. Mansurali
Published: July 2024

In the challenging world of complex projects, the influx of “data analytics” has offered project managers a game-changing asset, assisting them in various aspects from reporting to taking decisions, reducing cost, optimized resources utilization, effective risk management, and has ushered an era of unprecedented possibilities and opportunities. This chapter begins by elucidating the compelling need for DA adoption among project managers. The next part investigates into the application of DA across diverse project domains. The next section highlights the benefits of leveraging DA in projects and the barriers to DA adoption in projects. Furthermore, the chapter introduces a data analytics project management (DAPM) maturity model tailored to assess organizations' readiness and maturity levels in embracing DA within project management frameworks. In its final section, the chapter presents a practical roadmap for firms to navigate the complexities of DA adoption in projects.
AIoT-Powered Intelligent Remote Patient Activity Tracking and Comprehensive Vital Sign Analysis System for Enhanced Healthcare
Authors: Manimegalai D. , Gunasekari R. , Sujatha S. , Karthikeyan M. , Umasankar A.
Published: July 2024

This chapter explores the integration of artificial intelligence of things (AIoT) with tele-health monitoring, presenting an intelligent remote patient activity tracking system. Using interconnected sensors and machine learning models, the system monitors various patient activities and vital signs, providing real-time insights. The proposed AIoT-enabled health monitoring device tracks activities such as running, sleeping, walking, and exercising, while observing vital signs like heart rate and breathing patterns. The chapter delves into the system's architecture, functionalities, and technical intricacies, emphasizing its potential to transform healthcare delivery. It highlights the role of AIoT-driven solutions in enhancing patient care and fostering personalized treatment approaches, offering a glimpse into the promising future of intelligent healthcare delivery.
Women and Tourism
Authors: Srivastava Ambar , Pathania Ankit , Kumari Geeta
Published: July 2024

To achieve the sustainable development goals (SDGs) of the 2030 Agenda, which include the goals of gender equality, social inclusion, and women's empowerment, tourism is an essential industry. Gender disparity is a major development barrier in the majority of developing nations. The study aims to explore the challenges women face and gender inequality in tourism industry. The inter-linkage between tourism and SDGs will also be explored. A qualitative research technique was applied, and systematic literature review was based on articles in national and international journals, working papers, etc. explored. The study concluded that restricted opportunities for education, healthcare disparities, economic inequality are among the challenges faced by the women in tourism industry. It is also found that gender inequality in terms of dual presence, discrimination in wages, glass ceiling, sticky floors, etc. are also there. There is a definite linkage between the tourism industry and SDGs.
From Temples to Tranquillity
Authors: Natasha  , Indapurkar Kavita
Published: July 2024

Global tourism is becoming progressively acknowledged for its link to the sustainable development goals (SDGs). This study aims to explore how India can meet its sustainable development objectives through religious and wellness tourism. The study explores the effect of push and pull factors on travelers' motivation to travel. The study uses a quantitative and exploratory design, incorporating data gathered from 142 questionnaire responses. Results indicate that independent variables accounted for 38% of the variance in travel motivation, with a R Square value of 0.331. While gender and the cultural significance of the destination are important determinants, other factors may not have as much of an impact on motivation. The study emphasizes how tourism can support sustainable development, especially when it comes to promoting social inclusion, economic growth, and environmental preservation. The research's insights can help location managers, tourist authorities, and legislators create sustainable tourism experiences and regulations that support all-encompassing growth.
Blockchain-Empowered Business Realities
Authors: Rathod Seema Babusing , Vyawahare Harsha , Mahajan Rupali A. , Ponnusamy Sivaram
Published: July 2024

This research explores the synergies among blockchain, artificial intelligence (AI), and digital twins, showcasing their collective impact on reshaping contemporary business dynamics. The study examines practical applications across various industries, emphasizing transparency, cognitive capabilities, and virtual representations. The integration of these technologies optimizes operational efficiency, fosters innovation, and opens avenues for collaborative business models. Through real-world use cases, the research highlights the transformative potential of this convergence, urging businesses to adapt and innovate in the face of evolving digital landscapes for sustained competitiveness.
Digital Health Records in Paving the Way for Paperless and Green Practices
Authors: Midha Shuchi , P. Swathi , Shukla Vinod Kumar , Verma Shanti , K. Baskar
Published: July 2024

The transformational influence of digital health records (DHRs) on healthcare systems, with a focus on their significance in encouraging paperless and ecologically friendly practices. As technology advances, DHR usage gains traction, revolutionizing the old paper-based approach to health record administration. It also emphasizes the beneficial environmental benefit of moving to paperless systems, which reduces the carbon footprint related to paper manufacturing, storage, and disposal. The chapter intends to highlight the important role that DHR systems play in developing sustainable medical procedures as well as contributing to the larger global movement for environmental conservation by giving case studies and examples of effective DHR deployments. The research results imply that integrating DHRs not just contributes to more effective healthcare delivery but it additionally coincides with an increasing demand in the healthcare sector for environmentally aware solutions.
Digital Twins and Reinforcement Learning for Autonomous Systems in Industry 4.0
Authors: M. Nithya , Gurujukota Ramesh Babu , Gautam Anju , Bakliwal Chandresh , S. Sangeetha , Thangavel Karthikeyan
Published: July 2024

In this chapter, the authors delve into the compelling intersection of digital twins and reinforcement learning, aiming to propel the autonomy of systems within the Industry 4.0 paradigm. This investigation centers on uncovering the synergistic relationship between these two cutting-edge technologies and their profound implications for industrial settings. By seamlessly integrating digital twins and reinforcement learning, the authors seek to unlock new frontiers in efficiency, adaptability, and decision-making processes. Through an in-depth exploration of this integration, they anticipate shedding light on how these technologies collaboratively contribute to the evolution of smart, autonomous systems in industries. The study not only examines the theoretical framework but also delves into practical applications, aiming to discern the tangible impact on operational efficiency, adaptability to dynamic environments, and the overall decision-making prowess of autonomous systems in the context of Industry 4.0.
Elevating Precision Medicine
Authors: Ghotekar Pranoti Madhukar , Dhande Prajesh Rajesh , Ughade Pranay Ganpat , Waghmare Pratik Vijay , Jaronde Pravin
Published: July 2024

In the era of healthcare digitization, the paradigm of precision medicine has emerged as a groundbreaking approach to tailor medical treatments to individual patients. However, its impact extends far beyond healthcare, encompassing the broader domain of business transformation. This chapter presents an in-depth exploration of the design, implementation, and significance of a precision medicine web-service platform (PMWSP) that not only underpins precision medicine, but also serves as a catalyst for business innovation through the synergy of digital twins and artificial intelligence (AI). The first part of this chapter delves into the core principles of precision medicine, emphasizing its pivotal role in both healthcare advancement and broader business contexts. It highlights the imperative of harnessing diverse biomedical data sources, including genomics, clinical records, and wearable sensor data, to construct a comprehensive patient profile that transcends healthcare boundaries.
Enhancing Electric Vehicle Battery Management With the Integration of IoT and AI
Authors: Kasiviswanathan Harish Ravali , Ponnusamy Sivaram , Swaminathan K. , Thenthiruppathi T. , Sangeetha S. , Sankar K.
Published: July 2024

The performance of electric vehicles (EVs) is influenced by various factors such as battery life, cell voltage, health, safety, and charging/discharging speeds. Battery management is a critical task in EVs, ensuring the effective functioning of the battery. This study proposes an enhanced monitoring system for battery state-of-charge (SOC) using internet of things (IoT) and artificial intelligence (AI). The primary focus is on addressing a significant concern for researchers to ensure the safety of vehicle by accurately estimating SOC, monitoring, and promptly identifying breakdowns in the rechargeable batteries of electric vehicles. The voltage obtained from the Photovoltaic (PV) system is enhanced through the Boost integrated fly back rectifier energy DC-DC (BIFRED) converter, controlled by a cascaded adaptive neuro-fuzzy inference system (ANFIS) controller. The battery's SOC is monitored using recurrent neural networks (RNN), and the data is stored in the IoT system.
Exploring the Applications and Significance of Digital Twin Technology in Everyday Life
Authors: Uluiburotu Jiuliasi Veiwilitamata , Rabuka Salaseini Ligamamada
Published: July 2024

A digital twin refers to a virtual copy of an entity, which can be a system, process, or product. It is updated using current data and helps bridge the gap between the real and digital worlds. By creating an identical replica of an object, such as a locomotive, chair, or skyscraper, sensors are attached to collect real-time data which is then translated into a virtual representation. The digital twin is created, examined, and built in a virtual environment. This technology has been advanced by the development of the internet of things (IoT), which allows for constant connectivity and real-time data transmission. The digital twin is used to anticipate the future as well as comprehend the present. This chapter discusses and explains several digital twin applications as well as the value of digital twins.
Exploring the Role of Digital Twin in Power System Applications
Authors: Kasiviswanathan Harish Ravali , Karthikeyan M. , Vairamuthu S. , Ponnusamy Sivaram , Swaminathan K.
Published: July 2024

This chapter presents digital twinning technology, integrating multi-disciplinary, multi-physical, multi-scale, and multi-probability simulation processes through physical models and sensors. It achieves complete mapping in virtual space, capturing the entire life cycle of corresponding entities. The study analyzes existing models in related fields, examining their uses and implementation methods. Applying digital twin technology to the power system, the chapter explores optimization design for the power grid, simulation of power grid faults, virtual power plants, intelligent equipment monitoring, and other services. The application scenario of power system digital twin (PSDT) is detailed. The chapter also explains the model structure of PSDT and the method of model reduction.
Harnessing Logistic Industries and Warehouses With Autonomous Carebot for Security and Protection
Authors: Shaikh Mohammad Shahnawaz , Chandrawat Uday Bhanu Singh , Choudhary Swapna Madhusudan , Ali Syed Ibad , Ponnusamy Sivaram , Khan Rais Abdul Hamid , Sheikh Akilahmad Gulamzamir
Published: July 2024

In today's rapidly evolving world of logistics and supply chain management, the need for efficient and automated solutions has never been more pressing. Enter the smart autonomous warehouse Carebot, a cutting-edge technology designed to revolutionize the way warehouses operate. This innovative robotics system is poised to bring unprecedented levels of productivity, safety, and efficiency to the warehouse environment. This proposed work is a prototype model exhibiting a smart surveillance system equipped with various sensors to feature the system by automatic temperature control, gas detection, moisture detection, pest repulsion, flame detection with auto guided movement with protection to obstacle and pits on the surface. The smart autonomous warehouse Carebot would be a game changer in the logistics industry, revolutionizing the way warehouses operate and enhancing overall productivity and efficiency. Integration of autonomous Carebot with machine learning will open the door of advance approach for protection and security of logistic industry business.
Machine Learning Application for Virtual Replicas (Digital Twins) in Cybersecurity
Authors: Desai Jaynesh H. , Patel Sneha , Verma Shanti , Subramaniam Sangeetha
Published: July 2024

In the swiftly evolving realm of technology and cybersecurity, safeguarding our digital assets is paramount. This study explores the integration of machine learning techniques with virtual replicas, or digital twins, under the proposed system name CyberGuard, aiming to fortify cybersecurity measures and proactively prevent potential threats. Digital twins serve as virtual counterparts to real-world systems, providing a comprehensive understanding of their behavior. The research specifically concentrates on leveraging machine learning algorithms within CyberGuard to enhance the capabilities of digital twins in identifying and mitigating cyber threats. Through advanced analytics, this intelligent system can adapt to evolving cyber risks, identify unusual activities, and predict potential security breaches. The results highlight that the synergy between machine learning and Virtual Replicas not only improves threat detection and response times but also continuously strengthens the overall resilience of our cybersecurity infrastructure.
Social Media Optimisation for Retailers
Authors: Ersoy Ayse Begum
Published: July 2024

Retail business has been growing fast particularly during the last decade. High penetration rates of mobile communication devices such as smart phones and high usage of social media make the retailers especially in food across the world with Fee WIFI access, very attractive off-line and on-line social venues. The growth of the internet is continuous and offers many e-commerce opportunities for retail businesses to penetrate, grow and achieve loyalty also supported by globalisation. This chapter aims to identify how retail businesses can optimize social media usage in order to increase their customer base, reach a higher level of customer satisfaction and hence increase the rate of customer loyalty in the long run. The literature review focuses on social media engagement by small businesses and retailers.
The AI-Enhanced Transformation
Authors: Chaudhary Anita , Gill Satinderjit Kaur
Published: July 2024

This book chapter explains the transformational synergy between digital twins and artificial intelligence (AI) and how they work together in symbiotic ways across various industries. It explains how artificial intelligence (AI) transforms digital twins from static replicas to dynamic, intelligent systems, transforming sectors like manufacturing, healthcare, and transportation with its machine learning, advanced analytics, and predictive modelling capabilities. This chapter illustrates how this convergence propels creativity, improves efficiency, and streamlines operations using case studies and real-world situations. A comprehensive grasp of the significant implications and prudent application of AI in the context of digital twins is ensured by addressing other important factors, such as data management and ethical reservations. This chapter offers insights on leveraging this powerful combination for sustainable, flexible, and intelligent operations, making it a comprehensive resource for scholars, practitioners, and business executives.
Revolutionizing Supply Chain Management
Authors: Muqeem Mohammad , Rajawat Anand Singh , Goyal S. B. , Bhaladhare Pawan R. , Kumar Meesala Sudhir
Published: July 2024

In this paper to present a new and innovative use of blockchain technology and digital twins to greatly revolutionise the supply chain management industry. It acknowledges the urgent requirement for improved security and full disclosure in intricate supply chains within the framework of increasing digitalization and global interconnectivity. Supply chain management is currently grappling with several challenges. The study commences by acknowledging and discussing these problems. Subsequently, we will go into the core principles of blockchain technology and digital twins. In this paper, we introduce a system that safely and transparently saves data in an unchangeable ledger using blockchain technology. However, digital twins provide dynamic and real-time depictions of physical assets or processes. We illustrate the worth of this method by showcasing case studies from several industries .The study's last portion examines the possible enduring impacts of this convergence on supply chain management.
Blockchain and Cybersecurity Revolutionizing Healthcare in the Digital Era
Authors: Chavan Dipeeka Suresh , Kanade Tarun Madan
Published: July 2024

In the contemporary healthcare landscape, the integration of digital technologies has reached unprecedented levels, revolutionizing the way patient care is delivered and managed. This paradigm shift brings with it a multitude of opportunities for improved efficiency, accessibility, and quality of care. However, it also introduces a host of challenges, chief among them being the imperative need for robust security measures to safeguard sensitive patient data and fortify the healthcare infrastructure against the ever-looming threat of cyber attacks. “Healthcare in the Digital Era” serves as a comprehensive exploration of the intricacies involved in navigating this complex terrain. At its core, the chapter meticulously examines the interplay between technology and healthcare systems, shedding light on the vulnerabilities inherent in the digital advancements that have become integral to modern healthcare delivery.
Integrating AI, Machine Learning, and IoT Technologies for Enhanced Communication and Medical Applications
Authors: Aware Mrunal Swapnil , Dongre Nita Ganesh , Zanjat Shraddha N. , Karmore Bhavana S.
Published: July 2024

The growth of the Internet of Things has ushered in a wealth of information and a variety of uses, bringing the vision of a smarter world into reality. With the integration of cutting-edge technologies like cloud computing, interconnected devices, and intelligent multiple-sensor media systems, the concept of “smart healthcare” has garnered significant attention from various stakeholders, including medical specialists, businesspeople, governmental agencies, and educational establishments. This study aims to examine the Privacy and security issues posed by the AIIoT and provide recommendations for solutions. Qualitative study techniques were employed to gather pertinent information from numerous additional sources. The findings suggest that the fusion of artificial intelligence with the IoT has led to an abundance of new web-connected sensors and gadgets, raising myriad security and privacy concerns for consumers. Therefore, it is imperative for AI-driven IoT systems to adhere to well-defined architectural standards encompassing platforms and information patterns to guarantee consumers' improved safety and confidentiality. In simpler terms, the proliferation of IoT, combined with AI, has introduced numerous new gadgets and sensors connected to the web, raising serious concerns about user security and privacy. To address these issues, AI-driven IoT systems must follow clear architectural standards prioritizing user privacy and security.
Integrating Blockchain and Digital Twins for Enhanced Security and Transparency in Digital Ecosystems
Authors: Wankhede Neha , Patil Sarika , Kanade Tarun , Aurangabadkar Harshada
Published: July 2024

This chapter explores the integration of blockchain technology and digital twins as a revolutionary approach to enhancing security and ensuring end-to-end visibility in various sectors, including manufacturing, supply chain management, and the Internet of Things (IoT). The convergence of these technologies offers a unique opportunity to create a transparent, immutable, and real-time digital representation of physical assets, processes, or systems. We begin by introducing the concept of digital twins, virtual models designed to accurately reflect physical counterparts, and blockchain, a decentralized ledger technology known for its security, transparency, and immutability. The chapter delves into how the synergy between digital twins and blockchain can address common challenges such as data silos, security vulnerabilities, and lack of real-time data access, which are prevalent in traditional systems. Furthermore, we examine case studies and applications demonstrating the successful implementation of these technologies across different industries. This includes how blockchain-enabled digital twins can provide a secure, tamper-proof environment for data exchange, enhance traceability and accountability in supply chains, and facilitate predictive maintenance in manufacturing. The technical architecture required to integrate blockchain with digital twins is discussed, highlighting key considerations such as scalability, privacy, and interoperability. We also explore the potential of smart contracts in automating transactions and ensuring compliance within the digital twin ecosystem. The chapter concludes by addressing the challenges and future prospects of combining blockchain and digital twins. It discusses the importance of standardization, ethical considerations, and the need for collaborative efforts to overcome technical and regulatory hurdles. The aim is to provide readers with a comprehensive understanding of how these technologies can be leveraged to foster innovation, improve operational efficiencies, and build trust in digital and physical worlds. By offering insights into the integration of blockchain and digital twins, this chapter contributes to the body of knowledge on digital transformation strategies and presents a forward-looking perspective on building resilient, transparent, and efficient systems for the future.
Privacy Preservation Using Blockchain and Machine Learning
Authors: Solunke Hiralal Bhaskar , Bhaladhare Pawan , Potgantwar Amol
Published: July 2024

The increasing concerns over data breaches and privacy invasions highlight the critical need for enhanced privacy protections in the digital world. Since traditional privacy management techniques are rigid and cannot easily adjust to changing cyber threats, they frequently fail to meet these difficulties. The fusion of Blockchain and Technologies such as Federated Learning (FL) has come to light as a viable means of guaranteeing secure, open, and confidential interactions. While the individual merits of Blockchain in ensuring data integrity and FL in deriving insights are well-established, their synergistic effects particularly in the era of privacy preservation are yet to be fully explored. This fusion has the potential to revolutionize sectors like healthcare, finance, and supply chain by offering unprecedented levels of data privacy without compromising on system performance. This research described a review of existing models that employ machine learning techniques for privacy preservation operations within blockchain frameworks. Utilizing a set of predetermined metrics delay, throughput, energy efficiency, privacy levels, deployment cost, and scalability the paper compares these models to provide a nuanced understanding of their capabilities and limitations. Our in-depth comparison elucidates the trade-offs involved in selecting specific blockchain-ML models for diverse applications.
Enhancing Maternal Health
Authors: Shedge Prachi Pramod , Mehta Pradnya , Vyavahare Sakshi , Rupnar Vandana
Published: July 2024

Enhancing maternal health is a crucial pursuit in modern healthcare, especially when it comes to managing the risks associated with pregnancy. This chapter presents an innovative strategy that utilizes soft computing techniques to enhance the evaluation and handling of pregnancy-related risks. Soft computing, known for its ability to deal with imprecise and uncertain information, provides a promising framework for addressing the complexities involved in maternal health. By drawing upon various soft computing methodologies like fuzzy logic, neural networks, and genetic algorithms, this research aims to develop a comprehensive system for assessing pregnancy risks. The proposed approach integrates data from diverse sources, including medical records, maternal history, and environmental factors, to improve the accuracy and reliability of risk assessment during pregnancy. Through the soft computing techniques, this study strives to contribute to the early detection and proactive management of potential complications, ultimately leading to better outcomes for both the mother and the fetus.
Genetic Screening and Soft Computing Algorithms for Risk Prediction
Authors: Janrao Surekha , Phadke Madhura , Koli Reshma , Sarwade Jayesh
Published: July 2024

Genetic screening, along with improvements in soft computing methods, is a powerful way to figure out a person's risk factors for getting different diseases and conditions. The idea in this study is to use genetic screening methods and soft computing algorithms together in a structure that makes risk forecast more accurate. Genetic screening lets doctors find specific genetic markers and differences that are linked to a higher risk of getting diseases. By looking at a person's genes, possible risk factors can be found early on, which lets people take proactive steps to reduce or control these risks successfully. However, it is very hard to find useful trends and relationships in genetic data because it is so big and complicated. Soft computing methods are a hopeful way to deal with these problems because they provide adaptable and flexible computing tools that can handle the uncertainty and missing information that come with genetic data.
AI-Powered Vigilance in Neonatal Vital Signs Monitoring for Optimal Health Care
Authors: S. Gandhimathi Alias Usha , Bharathi K.
Published: July 2024

In neonatal care, continuous monitoring of vital signs plays a critical role in early detection of complications and ensuring timely interventions to optimize outcomes. Traditional monitoring methods often lack real-time analysis capabilities and may lead to delayed responses to deteriorating conditions. It then delves into the application of AI-powered systems for real-time analysis of vital signs such as heart rate, respiratory rate, oxygen saturation, and temperature in neonates. Through sophisticated algorithms, these systems can detect subtle changes and patterns indicative of distress or deterioration, enabling early intervention by healthcare providers. The chapter highlights the benefits of AI-powered monitoring systems, such as reduced false alarms, improved predictive capabilities, and enhanced workflow efficiency in Neonatal Intensive Care Units (NICUs).
Impact of Digitalization in Maternal Healthcare
Authors: Gupta Meena , Mishra Aniket , Kumar Prakash
Published: July 2024

The integration of digital technologies into maternal healthcare has revolutionized the landscape of prenatal, perinatal, and postpartum support. Telemedicine platforms, such as Amwell and Teladoc, facilitate remote consultations between expectant mothers and healthcare providers, ensuring convenient access to prenatal care and expert advice. Maternal health apps, including Ovia Pregnancy and Glow Nurture, have emerged as invaluable tools for pregnant women, providing features such as pregnancy tracking, nutritional guidance, and tailored exercise routines. These, equipped with sensors for monitoring vital signs, fetal movements, and maternal health parameters have become indispensable in maternal care. These technologies provide real-time data on fetal well-being and maternal health status, enabling proactive intervention. The integration of these digital technologies represents a paradigm shift in healthcare delivery, empowering expectant mothers with knowledge, support, and access to personalized care, ultimately enhancing maternal and neonatal healthcare.
Machine Learning Techniques for the Prediction of Preterm Birth Using Electrohysterography Signals
Authors: Namadurai Punitha
Published: July 2024

Preterm birth (PTB) is one of the dangerous pregnancy complications where the delivery occurs prior to 37 weeks of gestation. Prediction of PTB has been challenging since there are no objective measures to determine the uterine contractility. Electrohysterography (EHG) is a promising non-invasive approach which is currently being considered for improvement of external uterine monitoring. Automated analysis of EHG signals is a prospective method for monitoring pregnancy, detecting labor, and predicting PTB. This chapter focuses on the analysis of EHG signals and its application for the early diagnosis of PTB using machine learning techniques. Various public datasets and the techniques to extract appropriate information from the EHG signals are discussed. Analysis is done on the issue of class imbalance brought on by the relatively limited amount of PTB data as well as the efficacy of machine learning methods for early diagnosis of PTB. Further, potential research directions for EHG analysis and its application to PTB prediction are identified.
Empowering Individual Self-Care in Primary Menstruation Periods and Role of Physiotherapy Concerning Health Aspects
Authors: Verma Anshika , Chandni Kumari , Sharma Yamini , Sharma Jyoti , Singh Bhupinder
Published: July 2024

During women's reproductive years, many women experience primary dysmenorrhea (PD), a prevalent gynaecological disorder. While pharmacological treatments are used to address the symptoms of primary dysmenorrhea, interest in non-pharmacological methods, notably physiotherapy techniques, has developed. The purpose of this narrative review is to determine whether physical therapy techniques are useful in treating primary dysmenorrhea. To find pertinent papers, a thorough literature search in several databases was performed. Exercises for therapeutic purposes, physical activity, acupuncture, and complementary medical techniques were among the therapies studied in the literature. To determine the genuine efficacy and optimise the application of PT approaches in controlling PD, research with larger sample numbers and rigorous methodologies is required. This chapter as a whole emphasizes the potential advantages of non-pharmacological therapies, providing safer substitutes and a comprehensive strategy to enhance the wellbeing of people with primary dysmenorrhea.
Artificial Intelligence in Healthcare
Authors: Sharma Aruna
Published: July 2024

Artificial intelligence (AI) has experienced fast enlargement in current years. The term AI refers to the intelligence exhibited by machines, contrasting with that of humans or other living organisms. Utilizing AI expertise in healthcare has led to significant advancements in disease diagnosis, organization, and prediction; benefit both patients and healthcare professional. This book chapter aims to delve into the conceptual framework of confidence in AI concerning health, grounded not only in expert opinion but also in rigorous conceptual research and solid empirical evidence. It specifically focuses on clinical decision-manufacture, patient data investigation and diagnostics, analytical medication, physical condition services organization, and clinical making decisions, providing enhanced analysis and conduct decision help in healthcare settings.
Revolutionizing Healthcare
Authors: Govindaraj Manoj , D. Anitha Kumari , Khan Parvez , Krishnan Ravishankar , Gnanasekaran Chandramowleeswaran , Lawrence Jenifer
Published: July 2024

Artificial Intelligence (AI) is currently revolutionizing different aspects of the healthcare industry, making it a transformative force in the modern healthcare setting. This book chapter thoroughly analyses the significant influence of artificial intelligence (AI) on healthcare systems, carefully examining important applications and their consequences. A comprehensive investigation is carried out on the incorporation of diagnostic algorithms, predictive analytics, and personalized medicine, revealing their capacity to redefine the established level of medical treatment. The chapter specifically examines the impact of machine learning and deep learning techniques on medical imaging, highlighting their ability to improve diagnostic accuracy and efficiency. Moreover, the study explores AI-powered predictive models that not only transform preventive care but also enhance disease management and patient outcomes. The chapter examines the ethical implications of using AI in healthcare, while also discussing the importance of responsible and transparent methods.
Generative AI in Healthcare
Authors: D. Helen , Suresh N. V.
Published: July 2024

In recent years, the rapid development of AI technology Generative AI, has restructured the healthcare industry. Generative AI is a collection of algorithms that uses a large volume of medical data to generate new data in various formats, including medical images, data augmentation, and medicine development. A variety of techniques are employed in Generative AI in the healthcare industry, which includes Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), AutoRegressive Models, Flow-Based Models, and Probabilistic Graphical Models. Generative AI can applied in various domains in the healthcare sector including drug discovery, medical imaging enhancement, data augmentation, anomaly detection, simulation and training, and predictive modelling. The integration of Generative AI faces some challenges, such as addressing ethical and legal issues related to the use of Artificial Intelligence (AI) in healthcare and synthetic data in clinical decision-making, and ensuring the reliability and interpretability of AI-generated outputs.
Navigating the Promise and Perils of Generative AI in Healthcare
Authors: Joseph Shenson , Ul-Ain Qurat , Nosheen Sidra , Ahmad Munir , Fatima Rida
Published: July 2024

Generative AI offers transformative potential in healthcare, enabling advancements from data augmentation to drug discovery. However, its adoption poses ethical, technical, and regulatory hurdles. Issues like bias, data privacy, and ethical use necessitate responsible implementation. Stakeholders must collaborate to navigate these challenges, prioritizing ethical guidelines, robust security measures, and regulatory compliance. Education is crucial to ensure awareness and equip stakeholders to make informed decisions. By fostering trust and accountability, generative AI can revolutionize healthcare responsibly.