Browse Items (11809 total)
Sort by:
-
Artificial Intelligence in Healthcare Supply Chain Management: A Bibliometric Analysis: Subtitle as needed (AI in Healthcare Supply Chain)
The presented paper discussed the review of Healthcare Supply Chain Management (HSCM) using Artificial Intelligence (AI). The implementation of artificial intelligence (AI) in HSCM has numerous benefits, including accurate demand forecasting of medical supplies, cost reduction, increased transparency, visibility, data-driven decision-making, enhanced supply chain resilience, streamlined healthcare operations, optimized transportation, and many more. Our approach to using AI in HSCM involved a thorough examination of the literature and bibliometric analysis. Research was started by exploring the Scopus database using suitable keywords. After the inclusion and exclusion criteria have been applied, the relevant papers were gone through full-text readings. Using Vos-viewer, the research papers were further analyzed for bibliometric analysis. 2024 IEEE. -
Artificial Intelligence Influence on Accounting Methods
Due to its benefits in terms of enhancing and redefining the actual manner of performing activities in this field, artificial intelligence is swiftly changing the reality of the accounting business. Accounting has seen a significant transformation over the years as computers, first and foremost, and more importantly, developers ready to spend less time on laborious work that minimises the amount of errors, have replaced the job done with paper and pencil. Although there has always been a fascination with artificial intelligence systems in this field, attention has recently shifted more toward it. Although technology has advanced, it seems that there aren't enough facts to back up businesses' readiness to include artificial intelligence systems into their accounting procedures. A crucial element of this reality is also the ability of professionals to quickly adjust to the new business climate, get the skills required to work with AI systems, and overcome their fear of losing their jobs. The requirements of the financial society, the quick development of data innovation, and artificial intelligence have brought about the modern era. Implementing artificial intelligence innovation is an unavoidable trend that will result in substantial changes and advancements in the accounting sector. In this essay, the usage of AI in the accounting industry is examined, its effects on the sector's expansion are examined, and significant solutions to current issues are suggested. 2022 IEEE. -
Artificial Intelligence Influence on Leadership Styles in Human Resource Management for Employee Engagement
In this work, we investigate how the revolutionary effects of AI on leadership styles in the field of human resource management (HRM) have impacted employee motivation. To investigate the intricate relationship between AI adoption, HR management, and employee morale, we use a mixed-method approach, combining quantitative survey data with qualitative interview results. Both Leadership Style Change (LS-Change) and Employee Engagement (EE) show a statistically significant positive correlation with AI adoption. In the new AI-enabled HRM environment, HR executives are shifting their methods of leadership, adopting more flexible styles, giving workers more autonomy, and improving lines of communication. This research links theory and practice by providing actionable advice to HR managers and business owners. In order to further develop the topic of AI-enhanced HRM, future studies should investigate longitudinal dynamics, cross-industry variances, cultural and ethical issues, cutting-edge AI applications, and employee perspectives. 2024 IEEE. -
Artificial Intelligence Involvement in Graphic Game Development
Games have always been a popular form of entertainment and with the advancements in technology, the integration of Artificial Intelligence (AI) in gaming has revolutionized the gaming industry. This research article aims to explore the various applications of AI in gaming and its impact on the industry and player experience. Unlike the typical straightforward nature of AI, this research paper takes a more human approach to discussing the topic. It delves into the evolution of AI in games and the various types of AI used in game development. These include rule-based AI, learning- based AI, and evolutionary AI, which have all contributed to the development of increasingly immersive gaming experiences. The benefits and challenges of using AI in games are also explored, considering the impact on player experience. While AI-powered opponents can provide a greater challenge, balancing the difficulty level is critical to ensuring the game remains enjoyable. The potential ethical concerns of using AI in games are also discussed, such as data privacy, bias, and fairness. Furthermore, this research paper looks into the future of AI in games and how it may shape the gaming industry and player experience in the years to come. With the continued development of AI techniques such as reinforcement learning and GANs, the possibilities for more immersive and engaging gaming experiences are endless. 2023 IEEE. -
Artificial intelligence its growing role in human resource management
In this competitive era, the impact of artificial intelligence in human resource management is increasing quickly. Collecting the relevant data and then analyzing it accurately can accelerate the efficient working process of the organization. Artificial intelligence has paved its way in the working of various departments like IT, finance, marketing, and HRM. In this research, the researcher focused on the emerging role of artificial intelligence in HR department and how it is acting as a stimulator in enhancing the efficiency and accuracy of various HR functions like recruitment, hiring, work- life balance, performance appraisal, etc. The chapter is based on descriptive research, in which the researcher has collected secondary data from various research papers, articles, blogs, and websites. The chapter focuses on the growing role of artificial intelligence in the human resource function of the organization. 2024, IGI Global. All rights reserved. -
Artificial Intelligence Revolution in Supply Chain Management
Artificial Intelligence (AI) is a buzzword everywhere in every domain, as it is an emerging technology in all business sectors. It is essential for achieving productivity, business benefits, less human efforts in the required business sectors instead of a large workforce and many more artificial intelligence applications that are scaling up with large scale business sectors. AI capacity to identify the trade patterns, the study's business occurrence, and analyze the information. AI is necessary for today's life and as well as for upcoming generations. Artificial intelligence helps to resolve the most complex problems and difficult situations where humans have not achieved so far, as it is the artificial brainpower of humans. We have seen technological changes happening faster and progressively by AI. The supply chain vastly gained from interest and investments in AI. The digital supply chain initiation, a shift in manufacturing is up and running. Advantageous supply chain management is essential in business sectors, customers, and governments. A combination of Artificial intelligence and supply chain management is put together in making decisions. This article will discuss the overview of AI advancements in supply chain management end-to-end processes. We also reviewed the supply chain operations using AI. 2023 American Institute of Physics Inc.. All rights reserved. -
Artificial intelligence service agents: a silver lining in rural India
Purpose: The study aims to examine the impact of an artificial intelligent service agent (AISA) on customer services to the rural population provided by KAYA, Kotak Life's AI-enabled insurance chatbot avatar that offers quality insurance services. Design/methodology/approach: Multi-stage cluster sampling method was adopted to collect the responses from the 707 customers across the rural population of southern states of India. SPSS V.2 and Smart PLS 4 were used to apply simple percentage analysis, multiple linear regression analysis, and structural equation modeling (SEM) to validate the hypothesis. The dependent variables are economic performance and market performance based on the independent variables: efficiency, security, availability, enjoyment and contact. Findings: The study revealed that efficiency and security are the highest predictors and the most influencing variables in predicting the economic and market performance of the insurance companies in determining the quality of service when rendered through AISA among the customers. Efficiency, security, availability, contact and enjoyment are the critical dimensions of AISA. It has a more significant impact on quality service (claim processing) to the rural population. It improves the economic and market performance among the insurance companies and the rural population. Originality/value: Customers need convenience when making claims. Even little challenges might lead to stress and unhappiness, depending on the situation. Restrictions on where customers can file claims may not be the most outstanding service insurance firms can offer, given rising travel and commuting costs and widening geographical borders. Customers value proactive communication from service providers about the status of their insurance claims. 2023, Emerald Publishing Limited. -
Artificial Intelligence Technique Based Effective Disaster Recovery Framework to Provide Longer Time Connectivity in Mobile Ad-hoc Networks
Communication plays a vital role for effective management and for the execution of disaster response and emergency recovery efforts must be able to exchange information with each other from anywhere, at any time to successfully fulfill their missions. Therefore, it is important to configure emergency communications networks in disaster conditions using ad-hoc networks. This proposed framework collects the information and communication before or after a disaster. The aim of this research work is to propose a possible practical communication model by using ad-hoc network configuration technologies using Greedy Randomized Adaptive Search Procedure (GRASP) with the proposed algorithm. The development of this research work is to improve information exchange and facilitate coordination among emergency services and disaster field offices, state/level entities and private industry. This is accomplished by the integration of existing information systems, implementation of new efficient technologies and interconnection of established networks with artificial based techniques. IJCESEN. -
Artificial Intelligence Technological Revolution in Education and Space for Next Generation
The goal of this research is to discover the various potential for the educational system using artificial intelligence (AI). The world today is dealing with AI in different sectors. This study specifically looked into the prospects for acquiring efficient and high-quality education for each student, automating administrative tasks, including regulating adaptive student support systems. AI has been leveraged and used in the education sector in various formations. AI initially took in the form of computers with the cognitive model, transformed to online learning, together with other technologies, the use of AI provides chatbots to perform instructors. Imagine you can access your classroom from anywhere at any time through an online learning system. These functionalities enable the education system to deal with the curriculum effectively. Using these facilities, teachers instruct the students to desire to achieve their goals efficiently. The primary aim of this article addresses the concepts in AI that serve to regulate and improve the overall quality of academic performance. The secondary aim of this article is to discuss AI involvement in the space domain. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Artificial intelligence towards smart green transportation: A path towards sustainability
Emerging technological advancements and sustainability concerns have initiated the integration of smart technologies into the transportation infrastructure at major cities and tourist hubs. The rising environmental concerns have called for a shift in focus from conventional methods to innovative green transport initiatives being formulated by DMOs and destination planners. The use of data analytics and artificial intelligence in transportation has been proven to be a reasonable method for sustainable transportation. This study focuses on assessing the value propositions of smart transportation systems in enriching the tourist experience by providing convenient travel solutions. The chapter focuses on understanding the value proposition of smart transport designs at destinations and the long-term prospects of installing such sustainable infrastructure at major tourist hubs. The study also aims to evaluate the tourist experience in using smart transportation services and the potential benefits and challenges involved in the practical implementation of such systems. 2023, IGI Global. All rights reserved. -
Artificial Intelligence-Based Approaches for Anticipating Financial Market Index Trends
The stock market is an essential component of the world economy and significantly impacts how different countries handle their finances. Predicting stock prices has gained popularity recently since it can offer traders, investors, and policymakers useful information. Making informed financial decisions, lowering risk, and maximizing returns can all be facilitated by accurate stock price projections. Stock price prediction is a current research subject due to improvements in machine learning (ML) techniques, and several methodologies have been put forth in the literature. To increase the accuracy of stock price prediction, one method combines the feature extraction ability of convolutional neural networks (CNNs) with the classification strength of support vector machines (SVMs). CNNs are a subclass of neural networks that have excelled in voice and picture recognition. They can be taught to extract valuable features from the supplied data automatically. Contrarily, SVMs are a well-liked machine learning (ML) technique that has been applied for regression and classification tasks. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Artificial Intelligence-Based L&E-Refiner forBlind Learners
An Artificial Intelligence (AI)-based scribe known as L &E Refiner for blind learners is a technology that utilizes natural language processing and machine learning techniques to automatically transcribe lectures, books, and other written materials into audio format. This system is designed to provide an accessible learning experience for blind students, allowing them to easily access and interact with educational content. The AI scribe is able to recognize and understand various forms of text, including handwriting, printed text, and digital documents, and convert them into speech output that blind learners easily comprehend. This technology has the potential to significantly improve the accessibility and inclusion of education for blind individuals. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Artificial intelligence-based reverse logistics for improving circular economy performance: adeveloping country perspective
Purpose: Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance. Design/methodology/approach: In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis. Findings: Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation. Practical implications: The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals. Originality/value: Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs CE performance. 2024, Emerald Publishing Limited. -
Artificial Intelligence-Enabled Digital Twin for Smart Manufacturing
An essential book on the applications of AI and digital twin technology in the smart manufacturing sector. In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these technologies, Artificial Intelligence (AI) stands out as a transformative force, revolutionizing traditional manufacturing processes and making the way for the era of smart manufacturing. At the heart of this technological revolution lies the concept of the Digital Twin-an innovative approach that bridges the physical and digital realms of manufacturing. By creating a virtual representation of physical assets, processes, and systems, organizations can gain unprecedented insights, optimize operations, and enhance decision-making capabilities. This timely book explores the convergence of AI and Digital Twin technologies to empower smart manufacturing initiatives. Through a comprehensive examination of principles, methodologies, and practical applications, it explains the transformative potential of AI-enabled Digital Twins across various facets of the manufacturing lifecycle. From design and prototyping to production and maintenance, AI-enabled Digital Twins offer multifaceted advantages that redefine traditional paradigms. By leveraging AI algorithms for data analysis, predictive modeling, and autonomous optimization, manufacturers can achieve unparalleled levels of efficiency, quality, and agility. This book explains how AI enhances the capabilities of Digital Twins by creating a powerful tool that can optimize production processes, improve product quality, and streamline operations. Note that the Digital Twin in this context is a virtual representation of a physical manufacturing system, including machines, processes, and products. It continuously collects real-time data from sensors and other sources, allowing it to mirror the physical systems behavior and performance. What sets this Digital Twin apart is the incorporation of AI algorithms and machine learning techniques that enable it to analyze and predict outcomes, recommend improvements, and autonomously make adjustments to enhance manufacturing efficiency. This book outlines essential elements, like real-time monitoring of machines, predictive analytics of machines and data, optimization of the resources, quality control of the product, resource management, decision support (timely or quickly accurate decisions). Moreover, this book elucidates the symbiotic relationship between AI and Digital Twins, highlighting how AI augments the capabilities of Digital Twins by infusing them with intelligence, adaptability, and autonomy. Hence, this book promises to enhance competitiveness, reduce operational costs, and facilitate innovation in the manufacturing industry. By harnessing AIs capabilities in conjunction with Digital Twins, manufacturers can achieve a more agile and responsive production environment, ultimately driving the evolution of smart factories and Industry 4.0/5.0. Audience: This book has a wide audience in computer science, artificial intelligence, and manufacturing engineering, as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals. 2024 Scrivener Publishing LLC. -
Artificial intelligence-internet of things integration for smart marketing: Challenges and opportunities
The convergence of AI and the internet of things (IoT) has revolutionized various industries, including marketing. This integration offers immense potential for enhancing marketing strategies through real-time data analysis, personalized customer experiences, and predictive analytics. However, it also presents several challenges that need to be addressed for successful implementation. This abstract explores the challenges and opportunities associated with integrating AI and IoT in smart marketing initiatives. It discusses the potential benefits such as improved targeting, increased efficiency, and enhanced customer engagement. Additionally, it examines the challenges such as data privacy concerns, interoperability issues, and the need for skilled personnel. Furthermore, the abstract delves into case studies and examples illustrating successful AI-IoT integration in marketing campaigns. It also highlights emerging trends and future directions in this domain, emphasizing the importance of addressing challenges to unlock the full potential of smart marketing. 2024, IGI Global. All rights reserved. -
Artificial Intelligence-Monitored Procedure for Personal Ethical Standard Development Framework in the E-Learning Environment
The changes in the lifestyle of human beings due to the pandemic COVID-19 have affected all walks of human life. As a pillar of human development, the arena of education has a vital role to play in this changing world. The humongous and disruptive technologies that had made inroads into the educational scene as E-learning paved the way for ethical concerns in an unimaginable manner. Artificial intelligence is prudently incorporated for developing an ethical lifestyle for students all over the world. The Personal Ethical Standard Framework would work as a vaccine for the pandemic of the cancerous growth of the unethical habits of learners. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Artificial Intelligence, Smart Contracts, and the Groundbreaking Potential of Blockchain technology: Unlock the Next Generation of Innovation
The blockchain technology consists of blocks and is a decentralized network of nodes (miners). Each block is made up of three parts: the data, the hash, and the hash from the previous block. After data has been stored, it is extremely difficult to temper the data. Transactions are verified by miners, who are compensated with a commission for their labor. Readers will gain a comprehensive understanding of blockchain technology from this review article, including how it may be used in a variety of industries including supply chains, healthcare, and banking. Most individuals were already familiar with Bitcoin as one of the well-known blockchain applications. In this section, we'll discuss a few of the countless research publications on the cutting-edge applications of this technology. We'll talk about the challenges that come with actually using these applications as well. Blockchain is an industry that is growing thanks to its more recent applications in a number of fields, such as hospital administration, cryptocurrency use, and other places. Only the manner that blockchain works and runs makes it possible for these applications. 2023 IEEE. -
Artificial intelligence: A new model for online proctoring in education
As a result of technological advancements, society is becoming increasingly computerized. Massive open online courses and other forms of remote instruction continue to grow in popularity and reach. COVID-19's global impact has boosted the demand for similar courses by a factor of ten. The ability to successfully assign distant online examinations is a crucial limiting factor in this next stage of education's adaptability. Human proctoring is now the most frequent method of evaluation, which involves either forcing test takers to visit an examination centre or watching them visually and audibly throughout tests via a webcam. However, such approaches are time-consuming and expensive. In this paper, we provide a multimedia solution for semi-automated proctoring that does not require any extra gear other than the student's computer's webcam and microphone. The system continuously monitors and analyses the user based on gaze detection, lip movement, the number of individuals in the room, and mobile phone detection, and captures audio in real time through the microphone and transforms it to text for assessment using speech recognition. Access the words gathered by speech recognition and match them for keywords with the questions being asked for higher accuracy using Natural Language Processing. If any inconsistencies are discovered, they are reported to the proctor, who can investigate and take appropriate action. Extensive experimental findings illustrate the correctness, resilience, and efficiency of our online exam proctoring system, as well as how it allows a single proctor to simultaneously monitor several test takers. 2023 Author(s). -
Artificial intelligence: Blockchain integration for modern business
In the rapidly evolving landscape of modern business, the integration of artificial intelligence (AI) and blockchain technologies has emerged as a potent strategy to address various challenges and unlock new opportunities. This chapter presents a comprehensive overview of the integration of AI and blockchain, highlighting its significance and potential implications for businesses across diverse sectors. The synergy between AI and blockchain offers novel solutions for enhancing transparency, security, and efficiency in business operations. AI algorithms enable the automation of complex tasks, data analysis, and decisionmaking processes, while blockchain provides a decentralized, immutable ledger for secure and transparent data management. By combining these technologies, businesses can streamline processes, reduce costs, mitigate risks, and create new business models. Few key applications of AI-Blockchain integration in modern business include supply chain management, financial services, healthcare, identity verification, and intellectual property protection. 2024, IGI Global. All rights reserved. -
Artificial Neural Network with Firefly Algorithm-Based Collaborative Spectrum Sensing in Cognitive Radio Networks
Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network. Copyright 2023 KSII.