Jay Kumar Pandey – författare

Traditional surveillance systems struggle to process large volumes of visual data, identify specific objects or behaviors, and adapt to dynamic environments. Computational intelligence, which encompasses techniques like artificial intelligence (AI), machine learning (ML), and computer vision, offers powerful tools to address these challenges by enabling automated analysis, pattern recognition, and decision-making based on visual data. Computational Intelligence in Surveillance Systems Using Image Processing addresses the unique challenges and ethical considerations of applying AI and ML, offering a nuanced understanding of the regulatory landscape. It provides insights into the responsible development and deployment of technologies to unlock the transformative potential of computational intelligence to revolutionize surveillance systems and advance the capabilities of security and monitoring across various sectors.Discusses emerging trends, potential challenges, and areas for future research, providing a roadmap for scholars looking to contribute to the evolving field of image processingExplains how AI and ML algorithms can be applied to analyze and interpret visual data captured by surveillance camerasConsiders the challenges and considerations associated with deploying computational intelligence in surveillance, including privacy concerns, ethical considerations, and technical limitationsExplores specific use cases and applications where computational intelligence can enhance surveillance capabilities, such as object detection, activity recognition, anomaly detection, and predictive analytics

The Role of Emotional Intelligence and Artificial Intelligence in Organizations analyzes the synergistic relationship between two revolutionizing forces EI and AI in determining the future of work and leadership. The book offers a novel approach to how emotional intelligence enriches human-centered management, whereas artificial intelligence enhances data-driven decision-making and operational effectiveness.Combining psychology, technology, and organizational strategy, the book is a perfect fit for business leaders, HR professionals, organizational psychologists, scholars, and students of management and leadership. It delves into how bringing EI and AI together can lead to resilient, adaptive, and innovative workplace cultures.Through practical examples, case studies, and research-driven insights, readers will learn how to balance emotional intelligence with technological progress to improve collaboration, leadership performance, employee engagement, and ethical AI implementation. The book also tackles issues like digital exhaustion, AI bias, and upholding human values in automated settings.Readers will receive actionable tools and strategic advice to navigate an ever-changing organizational environment ensuring both technological advancement and emotional health are given priority for long-term success.

The Role of Emotional Intelligence and Artificial Intelligence in Organizations analyzes the synergistic relationship between two revolutionizing forces EI and AI in determining the future of work and leadership. The book offers a novel approach to how emotional intelligence enriches human-centered management, whereas artificial intelligence enhances data-driven decision-making and operational effectiveness.Combining psychology, technology, and organizational strategy, the book is a perfect fit for business leaders, HR professionals, organizational psychologists, scholars, and students of management and leadership. It delves into how bringing EI and AI together can lead to resilient, adaptive, and innovative workplace cultures.Through practical examples, case studies, and research-driven insights, readers will learn how to balance emotional intelligence with technological progress to improve collaboration, leadership performance, employee engagement, and ethical AI implementation. The book also tackles issues like digital exhaustion, AI bias, and upholding human values in automated settings.Readers will receive actionable tools and strategic advice to navigate an ever-changing organizational environment ensuring both technological advancement and emotional health are given priority for long-term success.

AI in Business Management: Bridging the Gap Between Technology and Strategy discusses how artificial intelligence might be used as a strategic enabler throughout contemporary organizations. The book makes AI accessible to business leaders, managers, and decision-makers, providing applied knowledge of how technological capabilities might be matched with corporate strategy. Interweaving case studies, real-world implementations, and forward-looking examination, it illustrates how AI may be used to fuel innovation, operational effectiveness, and competitive advantage when applied carefully within business models.Designed for professionals, MBA students, consultants, and academics, the book equips readers with a balanced understanding of AI’s potential and limitations. It addresses key themes such as digital transformation, ethical AI use, change management, and data-driven decision-making without requiring deep technical knowledge.Readers will gain from practical frameworks, strategic planning resources, and advice on navigating AI adoption in different organizational environments. Whether a digital leader or an executive wanting to future-proof an enterprise, this book provides a critical guide to converting AI technology into strategic effect.

AI in Business Management: Bridging the Gap Between Technology and Strategy discusses how artificial intelligence might be used as a strategic enabler throughout contemporary organizations. The book makes AI accessible to business leaders, managers, and decision-makers, providing applied knowledge of how technological capabilities might be matched with corporate strategy. Interweaving case studies, real-world implementations, and forward-looking examination, it illustrates how AI may be used to fuel innovation, operational effectiveness, and competitive advantage when applied carefully within business models.Designed for professionals, MBA students, consultants, and academics, the book equips readers with a balanced understanding of AI’s potential and limitations. It addresses key themes such as digital transformation, ethical AI use, change management, and data-driven decision-making without requiring deep technical knowledge.Readers will gain from practical frameworks, strategic planning resources, and advice on navigating AI adoption in different organizational environments. Whether a digital leader or an executive wanting to future-proof an enterprise, this book provides a critical guide to converting AI technology into strategic effect.

This book offers an in-depth exploration of how innovative technologies are reshaping the landscape of cancer diagnosis, treatment, and care by examining the intersection of precision medicine, digital health, and disruptive scientific advances in oncology and focusing on the integration of molecular profiling, artificial intelligence, and digital health infrastructures to revolutionize cancer care. Through 21 detailed chapters, the book covers a range of cutting-edge topics, including the application of AI and deep learning in oncologic imaging, the rise of liquid biopsy techniques for non-invasive cancer detection, and the powerful synergy of radiogenomics in personalizing patient treatment. It delves into how multi-omics integration and systems biology are being leveraged to understand tumor biology better, predict disease progression, and identify novel therapeutic targets. The book also addresses the evolving role of AI in predictive modeling and decision support systems, providing clinicians with advanced tools for risk stratification and prognostic analysis. It explores the ethical and regulatory challenges of integrating digital technologies into clinical practice and offers a global perspective on the barriers to equitable access in cancer care. Designed for oncologists, researchers, data scientists, biomedical engineers, and healthcare professionals, Precision Digital Oncology bridges the gap between cutting-edge research and real-world application, providing a comprehensive, forward-looking roadmap for the future of cancer treatment. Whether you're exploring the impact of AI in cancer care or seeking insights into the future of digital health technologies, this book offers critical knowledge for anyone interested in the next generation of cancer research and therapeutic strategies.

This book offers a comprehensive and interdisciplinary approach by integrating AI with food, nutrition, agriculture, and biotechnology. It covers both foundational concepts and practical applications, making it valuable for academics and professionals. It simplifies advanced technologies into straightforward explanations and practical examples, illustrating how AI technologies such as sensors, intelligent apps, and computer programs can assist farmers in cultivating more crops with less input, assist individuals in eating more nutritious food according to their individual health requirements, and assist researchers in creating improved seeds and environmental-friendly farming methods.Key Features: Describes how AI technologies such as machine learning, computer vision, and IoT are used in practical farming and food systemsPresents case studies and success stories highlighting AI-based solutions in agriculture, food safety, nutrition planning, and biotechnology researchDiscusses advanced topics such as precision farming, personalized nutrition, AI in genomics, and smart supply chains in a lucid, reader-friendly styleExamines the social, economic, and environmental advantages of using AI in sustainable agriculture, food security, and biotechnological innovation

Quantum Computing for Sustainable Supply Chain Management: Integrating Artificial Intelligence for Eco-Efficient Operations and Strategic Optimization is a relevant, contemporary, and futuristic contribution that discusses, explores, and highlights how emerging paradigms of computation, namely quantum computing, are significantly influencing sustainable supply chain design, planning, and practices. With the growing need to reduce environmentally adverse impacts while remaining efficient, this book fills a crucial divide between quantum computing, intelligence, and sustainable supply chain practices.The volume looks at how quantum algorithms, quantum-AI hybrid models, and optimization tools can help solve supply chain problems like demand forecasting, inventory management, logistics routing, managing risks, and carbon footprints. The book showcases innovative methods for achieving excellence in business operations through sustainable means by incorporating eco-efficiency ratios with intelligent decision support tools.To be specific, this book is intended for research scholars, industry experts, policymakers, and graduate students and aims to provide theoretical concepts, toolkits, and case studies related to quantum intelligence applications in creating greener, smarter, and more resilient supply chains. The book will act as a valuable reference material for those interested in leveraging disruption technologies to achieve sustainable operations globally.

Quantum Computing for Sustainable Supply Chain Management: Integrating Artificial Intelligence for Eco-Efficient Operations and Strategic Optimization is a relevant, contemporary, and futuristic contribution that discusses, explores, and highlights how emerging paradigms of computation, namely quantum computing, are significantly influencing sustainable supply chain design, planning, and practices. With the growing need to reduce environmentally adverse impacts while remaining efficient, this book fills a crucial divide between quantum computing, intelligence, and sustainable supply chain practices.The volume looks at how quantum algorithms, quantum-AI hybrid models, and optimization tools can help solve supply chain problems like demand forecasting, inventory management, logistics routing, managing risks, and carbon footprints. The book showcases innovative methods for achieving excellence in business operations through sustainable means by incorporating eco-efficiency ratios with intelligent decision support tools.To be specific, this book is intended for research scholars, industry experts, policymakers, and graduate students and aims to provide theoretical concepts, toolkits, and case studies related to quantum intelligence applications in creating greener, smarter, and more resilient supply chains. The book will act as a valuable reference material for those interested in leveraging disruption technologies to achieve sustainable operations globally.

The traditional food packaging industry promises to be revolutionized by the integration of cutting-edge Artificial Intelligence (AI) technologies to enhance food safety, minimize environmental impact, and introduce intelligent packaging systems. AI in Food Packaging explores the transformative impact of artificial intelligence on the food packaging industry. It describes the cutting-edge technologies that enhance food safety, optimize sustainability, and enable smart packaging solutions. From intelligent labeling systems that monitor product freshness to AI-driven design innovations that minimize environmental impact, readers will discover practical applications and future trends shaping the industry. It combines insights from technology, science, and business to provide a comprehensive guide for professionals and enthusiasts alike.Key Features:Analyzes cutting-edge AI technologies such as machine learning, IoT, and computer vision applied to food packaging systemsPresents real-world case studies and industry applications demonstrating smart packaging for quality monitoring and traceabilityCovers sustainability-focused innovations including AI-driven material selection and eco-friendly packaging designsProvides insight into regulatory frameworks, safety standards, and ethical concerns related to AI in the food supply chain

Revolutionizing Agricultural Quality Control with AI, Image Processing, and Computational Intelligence Techniques As the global demand for high-quality, sustainable agricultural products increases, advanced technology becomes critical in meeting these challenges. Computational Intelligence and Image Processing in Agriculture explores how innovative technologies are transforming agricultural quality evaluation. Combining foundational concepts with practical applications, this comprehensive text delves into innovative techniques to improve accuracy, efficiency, and sustainability in quality control. Addressing key challenges faced by researchers, practitioners, and industry professionals, contributions from leading experts in AI, agriculture, and computational intelligence provide a deep understanding of technologies such as deep learning, computer vision, and AI-driven robotics. Real-world examples, step-by-step tutorials, and code snippets make the concepts accessible and actionable, while coverage of emerging trends and future directions highlights the evolving landscape of agricultural technology. Offering interdisciplinary insights and practical tools to modernize evaluation techniques, reduce waste, enhance food safety, and meet the growing demands of sustainable farming practices, this book: Addresses challenges and solutions for real-time monitoring systems in agricultureHighlights cutting-edge applications such as AI-driven robotics and LiDAR in farmingEmphasizes sustainability and environmental impact through technological innovation Offers detailed coverage of image analysis algorithms for quality controlDiscusses ethical and environmental implications of technology in agricultureThis book is ideal for advanced undergraduate and graduate courses in agricultural engineering, computer science, and AI applications. It is also an essential reference for professionals including agricultural scientists, AI practitioners, and quality control experts.

Rapid non-destructive nutritional analysis using advanced imaging technologies Traditional nutritional analysis methods are destructive, slow, and impractical for large-scale applications. Nutritional Imaging in Agri-Food Systems presents image processing as a rapid, non-destructive alternative with real-time monitoring capabilities. A team of specialists in food science, imaging, and data analytics demonstrates how visual data can assess quality, detect adulteration, and monitor safety with unprecedented speed. This volume covers imaging technologies from visible light to multispectral, hyperspectral, thermal, fluorescence, and microscopy techniques, detailing specific applications in nutritional assessment. Case studies demonstrate scalable utilization in agriculture and food systems, including spoilage detection, automated grading, and real-time monitoring using edge AI and IoT. The book integrates machine learning, remote sensing, and digital agriculture insights. Readers will also find: Detailed coverage of how cameras and sensors detect color, texture, and chemical composition to identify ripeness, spoilage, and fat contentPractical applications for smartphones, drones, and smart farming equipment that make food analysis faster and more accessible across operationsIntegration strategies connecting machine learning, robotics, and remote sensing technologies for comprehensive agricultural and nutritional monitoring systemsMethods for reducing food waste and improving food safety through automated quality control and real-time assessment at production scaleScalable solutions linking agriculture, nutrition, and digital innovation for healthier food systems and more efficient supply chain managementWritten for scientists in agricultural science, food science, nutrition, computer vision, and image processing, this reference serves professionals in food processing, quality control, and agricultural technology. Regulatory agencies and remote sensing specialists will find practical frameworks for leveraging technology in food monitoring and policy development.

In this era of unprecedented connectivity and technological evolution, the fusion of 5G networks with healthcare promises a transformative journey that transcends the boundaries of traditional medical practices. The relentless pursuit of innovation, underpinned by the power of fifth-generation wireless technology, is poised to redefine the landscape of healthcare delivery, patient outcomes, and the very fabric of medical research. This new volume focuses on the recognition of 5G as a catalyst for monumental change in the healthcare sector in order to take advantage of today’s technology that fosters more interconnectedness, with the potential to leverage high-speed, low-latency communication afforded by 5G, opening up new frontiers for medical breakthroughs. This book helps to unravel the layers of this technological revolution and illuminate the ways in which 5G is reshaping the future of healthcare.Combining theoretical insights with real-world examples, case studies, and expert perspectives, the volume provides an introduction to communication systems in healthcare and the role of 5G technology and then goes on to discuss specific applications, such as in remote surgery and roboticassisted procedures; for liver tumor segmentation and classification using deep learning models; in telemedicine and mobile health apps; in dentistry; in health security; and more. The volume showcases the diverse applications of artificial intelligence, big data, digital twin, real-time data analytics, etc. in the healthcare sector.

Machine Learning Based Air Traffic Surveillance System Using Image Processing analyses how advanced machine learning algorithms and image processing technologies are revolutionising air-traffic management. By integrating real-time visual data analysis with sophisticated artificial intelligence techniques, this book highlights the potential to enhance situational awareness, safety, and efficiency in managing increasingly complex and congested airspaces. It delves into the use of convolutional neural networks (CNNs) and deep learning models to identify, track, and analyse aircraft movements, offering precise and actionable insights for air-traffic controllers.This comprehensive resource combines theoretical foundations with practical applications, including real-world case studies and discussions on system implementation. It addresses critical aspects such as object detection, anomaly identification, and trajectory prediction, alongside regulatory, ethical, and cybersecurity considerations. With its blend of cutting-edge research and practical insights, this book is an invaluable guide for professionals, researchers, and students in aerospace engineering, artificial intelligence, and computer vision, providing a roadmap for advancing air-traffic surveillance and management in the era of intelligent systems.

AI and Deep Learning Enabled Surveillance System Using Image Processing is an essential resource for anyone interested in the convergence of advanced technologies to enhance surveillance capabilities. This book explores in detail how artificial intelligence and deep learning can be applied to image processing, offering a transformative approach to modern surveillance systems. It covers foundational concepts of AI and deep learning, explaining how these technologies are reshaping the way we understand and utilize image data. The book emphasizes practical implementation, guiding readers through the integration of AI algorithms with image processing techniques to create sophisticated, real-time surveillance solutions.Through in-depth discussions and real-world case studies, the book highlights the applications of AI in various surveillance contexts, such as public safety, traffic monitoring, and access control. Readers will learn about the latest advancements in neural networks, object detection, and anomaly detection, gaining insights into developing and deploying intelligent surveillance systems. Additionally, the book addresses critical ethical and privacy considerations, ensuring that readers are aware of the balance between enhanced security and individual privacy rights. This comprehensive guide is an invaluable tool for professionals and researchers aiming to harness the power of AI and deep learning in the field of surveillance.

AI and Deep Learning Enabled Surveillance System Using Image Processing is an essential resource for anyone interested in the convergence of advanced technologies to enhance surveillance capabilities. This book explores in detail how artificial intelligence and deep learning can be applied to image processing, offering a transformative approach to modern surveillance systems. It covers foundational concepts of AI and deep learning, explaining how these technologies are reshaping the way we understand and utilize image data. The book emphasizes practical implementation, guiding readers through the integration of AI algorithms with image processing techniques to create sophisticated, real-time surveillance solutions.Through in-depth discussions and real-world case studies, the book highlights the applications of AI in various surveillance contexts, such as public safety, traffic monitoring, and access control. Readers will learn about the latest advancements in neural networks, object detection, and anomaly detection, gaining insights into developing and deploying intelligent surveillance systems. Additionally, the book addresses critical ethical and privacy considerations, ensuring that readers are aware of the balance between enhanced security and individual privacy rights. This comprehensive guide is an invaluable tool for professionals and researchers aiming to harness the power of AI and deep learning in the field of surveillance.