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In the past decade, artificial intelligence (AI), data analytics, and multimedia technology methods for integrating cyber-physical systems (CPS), smart manufacturing, and Industry 4.0 applications in the manufacturing industries have been steadily growing in availability. However, for industrial leaders, finding applicable, cost effective, and readily implementable multimedia, AI, and data analytics methods for industrial applications remains a daunting, laborious, and very expensive endeavor since the ecosystem of these technologies keeps diverging. Applied AI and Multimedia Technologies for Smart Manufacturing and CPS Applications provides a review of the state of the art regarding the integration of AI and multimedia technologies for smart manufacturing applications. It conducts a cost-benefit analysis regarding the benefits of the integration of specific AI and multimedia technologies in specific industrial manufacturing applications. Covering topics such as cognitive lead measurement, nonlinear filtering methods, and global product development, this premier reference source is a dynamic resource for business executives and managers, entrepreneurs, IT professionals, manufacturers, students and faculty of higher education, researchers, and academicians.
The rapid growth and capability of artificial intelligence, digital twin, and the internet of things are unlocking incredible opportunities to overcome some of the greatest environmental and social impact challenges currently facing the global community, such as feeding a growing population, safety, affordable housing, and environmental sustainability. The Handbook of Research on Applications of AI, Digital Twin, and Internet of Things for Sustainable Development provides an interdisciplinary platform encompassing research on the potential opportunities and risks of reaching sustainable development using artificial intelligence, digital twin, and the internet of things. Covering key topics such as big data, environmental protection, and smart cities, this major reference work is ideal for computer scientists, industry professionals, researchers, scholars, academicians, librarians, policymakers, practitioners, educators, and students.
Communication based on the internet of things (IoT) generates huge amounts of data from sensors over time, which opens a wide range of applications and areas for researchers. The application of analytics, machine learning, and deep learning techniques over such a large volume of data is a very challenging task. Therefore, it is essential to find patterns, retrieve novel insights, and predict future behavior using this large amount of sensory data. Artificial intelligence (AI) has an important role in facilitating analytics and learning in the IoT devices. Applying AI-Based IoT Systems to Simulation-Based Information Retrieval provides relevant frameworks and the latest empirical research findings in the area. It is ideal for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society and trust at the levels of the global economy, networks and organizations, teams and work groups, information systems, and individuals as actors in the networked environments. Covering topics such as blockchain visualization, computer-aided drug discovery, and health monitoring, this premier reference source is an excellent resource for business leaders and executives, IT managers, security professionals, data scientists, students and faculty of higher education, librarians, hospital administrators, researchers, and academicians.
Artificial intelligence (AI) and robotics have boomed in the 21st century. These emerging and disruptive technologies are immersed in our lives, from apps in mobile devices, the purchases we make on the internet streaming platforms, and even court decisions and predictive policing. Together with science and certain needs, relevant implementations of AI and robotics arise, related to its transparency, resulting in biases, the kinds of applications that can be implemented, and the degree of workforce replacement in decision-making assistance. It is essential to analyze the widely used AI techniques, the application of these technologies in different sectors, the implications of AI and robotics on society and welfare, and more. The Handbook of Research on Applied Artificial Intelligence and Robotics for Government Processes presents state-of-the-art research on AI and robotics in different fields of knowledge, its benefits, applications, and implications. It features chapters containing theoretical and practical research that analyzes the transparency and expandability of AI in different fields, as well as the analysis of unexpected results, biases, and cases of discrimination. Covering topics such as criminal intelligence, artificial intelligence-based chatbots, and gender violence, this major reference work is an excellent resource for government officials, practitioners in the public sector, business administrators and managers, IT professionals, law enforcement, federal agencies, students and faculty of higher education, researchers, and academicians.
Food is a necessary aspect of human life, and agriculture is crucial to any country’s global economy. Because the food business is essential to both a country’s economy and global economy, artificial intelligence (AI)-based smart solutions are needed to assure product quality and food safety. The agricultural sector is constantly under pressure to boost crop output as a result of population growth. This necessitates the use of AI applications. Artificial Intelligence Applications in Agriculture and Food Quality Improvement discusses the application of AI, machine learning, and data analytics for the acceleration of the agricultural and food sectors. It presents a comprehensive view of how these technologies and tools are used for agricultural process improvement, food safety, and food quality improvement. Covering topics such as diet assessment research, crop yield prediction, and precision farming, this premier reference source is an essential resource for food safety professionals, quality assurance professionals, agriculture specialists, crop managers, agricultural engineers, food scientists, computer scientists, AI specialists, students, libraries, government officials, researchers, and academicians.
Artificial intelligence (AI) is influencing the future of almost every sector and human being. AI has been the primary driving force behind emerging technologies such as big data, blockchain, robots, and the internet of things (IoT), and it will continue to be a technological innovator for the foreseeable future. New algorithms in AI are changing business processes and deploying AI-based applications in various sectors. The Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence is a comprehensive reference that presents cases and best practices of AI and knowledge engineering applications on business intelligence. Covering topics such as deep learning methods, face recognition, and sentiment analysis, this major reference work is a dynamic resource for business leaders and executives, IT managers, AI scientists, students and educators of higher education, librarians, researchers, and academicians.
Unmanned aerial vehicles (UAVs) and artificial intelligence (AI) are gaining the attention of academic and industrial researchers due to the freedoms that UAVs afford when operating and monitoring activities remotely. Applying machine learning and deep learning techniques can result in fast and reliable outputs and have helped in real-time monitoring, data collection and processing, and prediction. UAVs utilizing these techniques can become instrumental tools for computer/wireless networks, smart cities, military applications, agricultural sectors, and mining. Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques is an essential reference source that covers pattern recognition, machine and deep learning-based methods, and other AI techniques and the impact they have when applied to different real-time applications of UAVs. It synthesizes the scope and importance of machine learning and deep learning models in enhancing UAV capabilities, solutions to problems, and numerous application areas. Covering topics such as vehicular surveillance systems, yield prediction, and human activity recognition, this premier reference source is a comprehensive resource for computer scientists; AI engineers; data scientists; agriculturalists; government officials; military leaders; business managers and leaders; students and faculty of higher education; academic libraries; academicians; and researchers in computer science, computer vision, pattern recognition, imaging, and engineering.
The financial services sector experiences millions of transactions representing billions of dollars every day, with security, transparency, and cost-efficiency being top priorities. Blockchain usage is increasing in the financial services sector; it is a breakthrough that has changed the global financial system, making it safer and more efficient. Revolutionizing Financial Services and Markets Through FinTech and Blockchain explores the application of blockchain technology within financial services and financial markets. Covering topics such as blockchain technology, e-finance applications, and financial product innovation, this book is ideal for academicians, investment institutions, asset management professionals, consultants, and more.
The convergence of modern technology and social dynamics have shaped the very fabric of today’s organizations, making the role of Business Intelligence (BI) profoundly significant. Data-Driven Business Intelligence Systems for Socio-Technical Organizations delves into the heart of this transformative realm, offering an academic exploration of the tools, strategies, and methodologies that propel enterprises toward data-driven decision-making excellence. Socio-technical organizations, with their intricate interplay between human and technological components, require a unique approach to BI. This book embarks on a comprehensive journey, revealing how BI tools empower these entities to decipher the complexities of their data landscape. From user behavior to social interactions, technological systems to environmental factors, this work sheds light on the multifaceted sources of information that inform organizational strategies. Decision-makers within socio-technical organizations leverage BI insights to discern patterns, spot trends, and uncover correlations that influence operations and the intricate social dynamics within their entities. Research covering real-time monitoring and predictive analytics equips these organizations to respond swiftly to demands and anticipate future trends, harnessing the full potential of data. The book delves into their design, development, and architectural nuances, illuminating these concepts through case studies. This book is ideal for business executives, entrepreneurs, data analysts, marketers, government officials, educators, and researchers.
In today's rapidly evolving landscape, AI has become an indispensable tool for organizations seeking to enhance their understanding of customers, boost productivity, and foster stronger connections with their target audience. The Use of Artificial Intelligence in Digital Marketing: Competitive Strategies and Tactics is a comprehensive and timely exploration of the integration of artificial intelligence (AI) into the field of digital marketing. Authored by experts in the field, this book delves into the profound and far-reaching changes that AI is bringing to the digital marketing arena. It provides a detailed examination of how organizations can leverage AI technologies to gain a competitive edge in the market. By mastering these new technologies, companies can effectively navigate the dynamic digital landscape, optimize their marketing strategies, and deliver highly personalized content to their customers. Ideal for a wide range of audiences, including researchers, teachers, students, and executives, this book serves as a vital resource for those seeking to stay ahead of the curve in the ever-evolving world of digital marketing. Through its comprehensive coverage of AI applications in the field, it equips readers with the knowledge and insights necessary to make informed decisions, develop effective marketing strategies, and drive business growth.