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Artificial Intelligence and Machine Learning: 33rd Benelux Conference on Artificial Intelligence, BNAIC/Benelearn 2021, Esch-sur-Alzette, Luxembourg, November 10–12, 2021, Revised Selected Papers (Communications in Computer and Information Science #1530)
by Cédric Pruski Amro Najjar Luis A. Leiva Réka Markovich Christoph SchommerThis book contains a selection of the best papers of the 33rd Benelux Conference on Artificial Intelligence, BNAIC/ BENELEARN 2021, held in Esch-sur-Alzette, Luxembourg, in November 2021. The 14 papers presented in this volume were carefully reviewed and selected from 46 regular submissions. They address various aspects of artificial intelligence such as natural language processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI and education, and data analysis.
Artificial Intelligence and Machine Learning: An Intelligent Perspective of Emerging Technologies (Innovations in Health Informatics and Healthcare)
by Rohit Tanwar Surbhi Bhatia Varun Sapra Neelu Jyoti AhujaThis book focuses on artificial intelligence (AI) and machine learning (ML) technologies and how they are progressively being incorporated into a wide range of products, including consumer gadgets, "smart" personal assistants, cutting-edge medical diagnostic systems, and quantum computing systems. This concise reference book offers a broad overview of the most important trends and discusses how these trends and technologies are being created and employed in the applications in which they are being used. Artificial Intelligence and Machine Learning: An Intelligent Perspective of Emerging Technologies offers a broad package involving the incubation of AI and ML with various emerging technologies such as Internet of Things (IoT), healthcare, smart cities, robotics, and more. The book discusses various data collection and data transformation techniques and also maps the legal and ethical issues of data-driven e-healthcare systems while covering possible ways to resolve them. The book explores different techniques on how AI can be used to create better virtual reality experiences and deals with the techniques and possible ways to merge the power of AI and IoT to create smart home appliances. With contributions from experts in the field, this reference book is useful to healthcare professionals, researchers, and students of industrial engineering, systems engineering, biomedical, computer science, electronics, and communications engineering.
Artificial Intelligence and Machine Learning: An Intelligent Perspective of Emerging Technologies (Innovations in Health Informatics and Healthcare)
by Rohit Tanwar Surbhi Bhatia Khan Varun Sapra Neelu Jyoti AhujaThis book focuses on artificial intelligence (AI) and machine learning (ML) technologies and how they are progressively being incorporated into a wide range of products, including consumer gadgets, "smart" personal assistants, cutting-edge medical diagnostic systems, and quantum computing systems. This concise reference book offers a broad overview of the most important trends and discusses how these trends and technologies are being created and employed in the applications in which they are being used. Artificial Intelligence and Machine Learning: An Intelligent Perspective of Emerging Technologies offers a broad package involving the incubation of AI and ML with various emerging technologies such as Internet of Things (IoT), healthcare, smart cities, robotics, and more. The book discusses various data collection and data transformation techniques and also maps the legal and ethical issues of data-driven e-healthcare systems while covering possible ways to resolve them. The book explores different techniques on how AI can be used to create better virtual reality experiences and deals with the techniques and possible ways to merge the power of AI and IoT to create smart home appliances. With contributions from experts in the field, this reference book is useful to healthcare professionals, researchers, and students of industrial engineering, systems engineering, biomedical, computer science, electronics, and communications engineering.
Artificial Intelligence and Machine Learning for COVID-19 (Studies in Computational Intelligence #924)
by Fadi Al-TurjmanThis book is dedicated to addressing the major challenges in fighting COVID-19 using artificial intelligence (AI) and machine learning (ML) – from cost and complexity to availability and accuracy. The aim of this book is to focus on both the design and implementation of AI-based approaches in proposed COVID-19 solutions that are enabled and supported by sensor networks, cloud computing, and 5G and beyond. This book presents research that contributes to the application of ML techniques to the problem of computer communication-assisted diagnosis of COVID-19 and similar diseases. The authors present the latest theoretical developments, real-world applications, and future perspectives on this topic. This book brings together a broad multidisciplinary community, aiming to integrate ideas, theories, models, and techniques from across different disciplines on intelligent solutions/systems, and to inform how cognitive systems in Next Generation Networks (NGN) should be designed, developed, and evaluated while exchanging and processing critical health information. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies.
Artificial Intelligence and Machine Learning for Healthcare: Vol. 1: Image and Data Analytics (Intelligent Systems Reference Library #228)
by Chee-Peng Lim Ashlesha Vaidya Yen-Wei Chen Tejasvi Jain Lakhmi C. JainArtificial intelligence (AI) and machine learning (ML) have transformed many standard and conventional methods in undertaking health and well-being issues of humans. AL/ML-based systems and tools play a critical role in this digital and big data era to address a variety of medical and healthcare problems, improving treatments and quality of care for patients. This edition on AI and ML for healthcare consists of two volumes. The first presents selected AI and ML studies on medical imaging and healthcare data analytics, while the second unveils emerging methodologies and trends in AI and ML for delivering better medical treatments and healthcare services in the future.In this first volume, progresses in AI and ML technologies for medical image, video, and signal processing as well as health information and data analytics are presented. These selected studies offer readers theoretical and practical knowledge and ideas pertaining to recent advances in AI and ML for effective and efficient image and data analytics, leading to state-of-the-art AI and ML technologies for advancing the healthcare sector.
Artificial Intelligence and Machine Learning in Public Healthcare: Opportunities and Societal Impact (SpringerBriefs in Applied Sciences and Technology)
by KC Santosh Loveleen GaurThis book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.
Artificial Intelligence and Machine Learning in Satellite Data Processing and Services: Proceedings of the International Conference on Small Satellites, ICSS 2022 (Lecture Notes in Electrical Engineering #970)
by Sumit Kumar Kuldeep Singh Raj SetiaThis book, Artificial Intelligence and Machine Learning in Satellite: Data Processing and Services, presents the selected proceedings of the International Conference on Small Satellites (ICSS 2022) that aims to provide an opportunity for academicians, scientists, researchers, and industry experts, engaged in teaching, research, and development on satellite data processing and its services by employing advanced artificial intelligence-based machine learning techniques. This book covers the application of artificial intelligence and machine learning techniques in various domains of earth observations like natural resources and environmental management, water resources, urban and rural development, climate change, and other contemporary subjects. The book will surely be a valuable asset for beginners, researchers, and professionals working in satellite data processing and services using artificial intelligence and machine learning approaches.
Artificial Intelligence and Machine Learning in the Thermal Spray Industry: Practices, Implementation, and Challenges (Multi-Scale and Multi-Functional Materials)
by Lalit Thakur Hitesh Vasudev Jashanpreet Singh Gaurav PrasharThis book details the emerging area of the induction of expert systems in thermal spray technology, replacing traditional parametric optimization methods like numerical modeling and simulation. It promotes, enlightens, and hastens the digital transformation of the surface engineering industry by discussing the contribution of expert systems like Machine Learning (ML) and Artificial Intelligence (AI) toward achieving durable Thermal Spray (TS) coatings. Artificial Intelligence and Machine Learning in the Thermal Spray Industry: Practices, Implementation, and Challenges highlights how AI and ML techniques are used in the TS industry. It sheds light on AI’s versatility, revealing its applicability in solving problems related to conventional simulation and numeric modeling techniques. This book combines automated technologies with expert machines to show several advantages, including decreased error and greater accuracy in judgment, and prediction, enhanced efficiency, reduced time consumption, and lower costs. Specific barriers preventing AI’s successful implementation in the TS industry are also discussed. This book also looks at how training and validating more models with microstructural features of deposited coating will be the center point to grooming this technology in the future. Lastly, this book thoroughly analyzes the digital technologies available for modeling and achieving high-performance coatings, including giving AI-related models like Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) more attention. This reference book is directed toward professors, students, practitioners, and researchers of higher education institutions working in the fields that deal with the application of AI and ML technology.
Artificial Intelligence and Machine Learning in the Thermal Spray Industry: Practices, Implementation, and Challenges (Multi-Scale and Multi-Functional Materials)
by Lalit Thakur Hitesh Vasudev Jashanpreet Singh Gaurav PrasharThis book details the emerging area of the induction of expert systems in thermal spray technology, replacing traditional parametric optimization methods like numerical modeling and simulation. It promotes, enlightens, and hastens the digital transformation of the surface engineering industry by discussing the contribution of expert systems like Machine Learning (ML) and Artificial Intelligence (AI) toward achieving durable Thermal Spray (TS) coatings. Artificial Intelligence and Machine Learning in the Thermal Spray Industry: Practices, Implementation, and Challenges highlights how AI and ML techniques are used in the TS industry. It sheds light on AI’s versatility, revealing its applicability in solving problems related to conventional simulation and numeric modeling techniques. This book combines automated technologies with expert machines to show several advantages, including decreased error and greater accuracy in judgment, and prediction, enhanced efficiency, reduced time consumption, and lower costs. Specific barriers preventing AI’s successful implementation in the TS industry are also discussed. This book also looks at how training and validating more models with microstructural features of deposited coating will be the center point to grooming this technology in the future. Lastly, this book thoroughly analyzes the digital technologies available for modeling and achieving high-performance coatings, including giving AI-related models like Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) more attention. This reference book is directed toward professors, students, practitioners, and researchers of higher education institutions working in the fields that deal with the application of AI and ML technology.
Artificial Intelligence and Machine Learning Methods in COVID-19 and Related Health Diseases (Studies in Computational Intelligence #1023)
by Victor Chang Harleen Kaur Simon James FongThis Springer book provides a perfect platform to submit chapters that discuss the prospective developments and innovative ideas in artificial intelligence and machine learning techniques in the diagnosis of COVID-19. COVID-19 is a huge challenge to humanity and the medical sciences. So far as of today, we have been unable to find a medical solution (Vaccine). However, globally, we are still managing the use of technology for our work, communications, analytics, and predictions with the use of advancement in data science, communication technologies (5G & Internet), and AI. Therefore, we might be able to continue and live safely with the use of research in advancements in data science, AI, machine learning, mobile apps, etc., until we can find a medical solution such as a vaccine. We have selected eleven chapters after the vigorous review process. Each chapter has demonstrated the research contributions and research novelty. Each group of authors must fulfill strict requirements.
Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision
by Karm Veer Arya Saurabh Singh Ciro Rodriguez Rodriguez Abhishek SinghalThis new volume provides in-depth and detailed knowledge about the latest research in image processing and computer vision techniques. Explaining the machine learning algorithms and models involved, the authors differentiate between the various algorithms available and how to choose which to use for the most precise results for a specific task involving certain constraints. The volume provides real-world examples to illustrate the concepts and methods.The authors discuss machine learning in healthcare systems for detection, diagnosis, classification, and segmentation. They also explore the diverse applications of image and video processing, including image colorization and restoration using deep learning, using machine learning to record the climate changes in over time with remote sensing, and more.
Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision
This new volume provides in-depth and detailed knowledge about the latest research in image processing and computer vision techniques. Explaining the machine learning algorithms and models involved, the authors differentiate between the various algorithms available and how to choose which to use for the most precise results for a specific task involving certain constraints. The volume provides real-world examples to illustrate the concepts and methods.The authors discuss machine learning in healthcare systems for detection, diagnosis, classification, and segmentation. They also explore the diverse applications of image and video processing, including image colorization and restoration using deep learning, using machine learning to record the climate changes in over time with remote sensing, and more.
Artificial Intelligence and Modeling for Water Sustainability: Global Challenges
by Alaa El Din Mahmoud Manal Fawzy Nadeem Ahmad KhanArtificial intelligence and the use of computational methods to extract information from data are providing adequate tools to monitor and predict water pollutants and water quality issues faster and more accurately. Smart sensors and machine learning models help detect and monitor dispersion and leakage of pollutants before they reach groundwater. With contributions from experts in academia and industries, who give a unified treatment of AI methods and their applications in water science, this book help governments, industries, and homeowners not only address water pollution problems more quickly and efficiently, but also gain better insight into the implementation of more effective remedial measures. FEATURES Provides cutting-edge AI applications in water sector. Highlights the environmental models used by experts in different countries. Discusses various types of models using AI and its tools for achieving sustainable development in water and groundwater. Includes case studies and recent research directions for environmental issues in water sector. Addresses future aspects and innovation in AI field related to watersustainability. This book will appeal to scientists, researchers, and undergraduate and graduate students majoring in environmental or computer science and industry professionals in water science and engineering, environmental management, and governmental sectors. It showcases artificial intelligence applications in detecting environmental issues, with an emphasis on the mitigation and conservation of water and underground resources.
Artificial Intelligence and Modeling for Water Sustainability: Global Challenges
by Alaa El Din Mahmoud Manal Fawzy Nadeem Ahmad KhanArtificial intelligence and the use of computational methods to extract information from data are providing adequate tools to monitor and predict water pollutants and water quality issues faster and more accurately. Smart sensors and machine learning models help detect and monitor dispersion and leakage of pollutants before they reach groundwater. With contributions from experts in academia and industries, who give a unified treatment of AI methods and their applications in water science, this book help governments, industries, and homeowners not only address water pollution problems more quickly and efficiently, but also gain better insight into the implementation of more effective remedial measures. FEATURES Provides cutting-edge AI applications in water sector. Highlights the environmental models used by experts in different countries. Discusses various types of models using AI and its tools for achieving sustainable development in water and groundwater. Includes case studies and recent research directions for environmental issues in water sector. Addresses future aspects and innovation in AI field related to watersustainability. This book will appeal to scientists, researchers, and undergraduate and graduate students majoring in environmental or computer science and industry professionals in water science and engineering, environmental management, and governmental sectors. It showcases artificial intelligence applications in detecting environmental issues, with an emphasis on the mitigation and conservation of water and underground resources.
Artificial Intelligence and Natural Language: 11th Conference, AINL 2022, Saint Petersburg, Russia, April 14–15, 2022, Revised Selected Papers (Communications in Computer and Information Science #1731)
by Valentin Malykh Andrey FilchenkovThis book constitutes the refereed proceedings of the 11th Conference on Artificial Intelligence and Natural Language, AINL 2022, held in St. Petersburg, Russia, in April 2022. The 8 revised full papers and 1 short paper were carefully reviewed and selected from 20 submissions. The volume presents recent research in areas of of text mining, speech technologies, dialogue systems, information retrieval, machine learning, articial intelligence, and robotics.
Artificial Intelligence and Online Engineering: Proceedings of the 19th International Conference on Remote Engineering and Virtual Instrumentation (Lecture Notes in Networks and Systems #524)
by Michael E. Auer Samir A. El-Seoud Omar H. KaramNowadays, online technologies are the core of most fields of engineering and the whole society and are inseparable connected for example with Internet of Things & Industrial Internet of Things (Industry 4.0), Online & Biomedical Engineering, Data Science, Machine Learning, and Artificial Intelligence, Cross & Mixed Reality, and Remote Working Environments. to name only a few. Since the first REV conference in 2004, we tried to focus on the upcoming use of the Internet for engineering tasks and the opportunities as well as challenges around it. Consequently, the motto of this year’s REV2022 was “Artificial Intelligence and Online Engineering”. In a globally connected world, the interest in online collaboration, teleworking, remote services, and other digital working environments is rapidly increasing. In response to that, the general objective of this conference is to contribute and discuss fundamentals, applications, and experiences in the field of Online and Remote Engineering, Virtual Instrumentation and other related new technologies like Cross Reality, Data Science & Big Data, Internet of Things & Industrial Internet of Things, Industry 4.0, Cyber-Security, and M2M & Smart Objects. Another objective of the conference is to discuss guidelines and new concepts for engineering education in higher and vocational education institutions, including emerging technologies in learning, MOOCs & MOOLs, and Open Resources. REV2022 was the 19th in a series of annual events concerning the area of Online Engineering. It has been organized in cooperation with The British University in Egypt (BUE), Cairo, as a hybrid event from February 28 until March 02, 2022.
Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry
by M. Catherine MajumdarThis conference brought together experts from 15 countries to discuss application of Artificial Intelligence (AI) techniques to the nuclear industry. It was apparent from the meeting that even those active in the field were surprised at the extent of work and the progress made. There was a strong impression that application of this technology to nuclear power plants is inevitable. The benefits to improved operation, design, and safety are simply too significant to be ignored. This is a much different conclusion than might have been reached a few years ago when the technology was new and people were struggling to understand its significance. We believe that this meeting reflects a major turning point for the technology. It has moved from being a topic understood only by specialists to a situation where users are the most active people in the field. A broad array of innovative work is described from all of the participating countries. The activity in the u.s. is large and diverse. Although there is no nationally focussed policy for AI research in the U.S., many of these activities are reported here. Japan and France have a strong drive to integrate AI technology into their nuclear plants, and this is reflecteq in these proceedings.
Artificial Intelligence and Renewables Towards an Energy Transition (Lecture Notes in Networks and Systems #174)
by Mustapha HattiThis proceedings book emphasizes adopting artificial intelligence-based and sustainable energy efficiency integrated with clear objectives, to involve researchers, students, and specialists in their development and implementation adequately in achieving objectives. The integration of artificial intelligence into renewable energetic systems would allow the rapid development of a knowledge-based economy suitable to the energy transition, while fully integrating the renewables into the global economy. This is how artificial intelligence has hand in by conceptualizing this transition and above all by saving time. The knowledge economy is valuated within the smart cities, which are fast becoming the favorite places where the energy transition will take place efficiently and intelligently by implementing integrated approaches to energy saving and energy supply and integrated urban approaches that go beyond individual interventions in buildings or transport modes using information and communication technologies.
Artificial Intelligence and Robotics: Ten Short Lessons (Pocket Einstein Series #1)
by Peter J. BentleyIn Artificial Intelligence and Robotics: Ten Short Lessons, leading expert Peter J. Bentley breaks down the fast-moving world of computers into ten pivotal lessons, presenting the reader with the essential information they need to get to understand our most powerful technology and its remarkable implications for our species.From the origins and motivation behind the birth of AI and robotics to using smart algorithms that allow us to build good robots, from the technologies that enable computers to understand a huge range of sensory information, including language and communication, to the challenges of emotional intelligence, unpredictable environments, and imagination in artificial intelligence, this is a cutting-edge, expert-led guide for curious minds. Packed full of easy-to-understand diagrams, pictures, and fact boxes, these ten lessons cover all the basics, as well as the latest understanding and developments, to enlighten the nonscientist.About the series: The Pocket Einstein series is a collection of essential pocket-sized guides for anyone looking to understand a little more about some of the most important and fascinating areas of science in the twenty-first century. Broken down into ten simple lessons and written by leading experts in their field, the books reveal the ten most important takeaways from those areas of science you've always wanted to know more about.
Artificial Intelligence and Robotics: Ten Short Lessons (Pocket Einstein Series)
by Peter J. BentleyIn Artificial Intelligence and Robotics: Ten Short Lessons, leading expert Peter J. Bentley breaks down the fast-moving world of computers into ten pivotal lessons, presenting the reader with the essential information they need to get to understand our most powerful technology and its remarkable implications for our species.From the origins and motivation behind the birth of AI and robotics to using smart algorithms that allow us to build good robots, from the technologies that enable computers to understand a huge range of sensory information, including language and communication, to the challenges of emotional intelligence, unpredictable environments, and imagination in artificial intelligence, this is a cutting-edge, expert-led guide for curious minds. Packed full of easy-to-understand diagrams, pictures, and fact boxes, these ten lessons cover all the basics, as well as the latest understanding and developments, to enlighten the nonscientist.About the series: The Pocket Einstein series is a collection of essential pocket-sized guides for anyone looking to understand a little more about some of the most important and fascinating areas of science in the twenty-first century. Broken down into ten simple lessons and written by leading experts in their field, the books reveal the ten most important takeaways from those areas of science you've always wanted to know more about.
Artificial Intelligence and Robotics (Studies in Computational Intelligence #917)
by Huimin LuThis book provides insights into research in the field of artificial intelligence in combination with robotics technologies. The integration of artificial intelligence and robotic technologies is a highly topical area for researchers and developers from academia and industry around the globe, and it is likely that artificial intelligence will become the main approach for the next generation of robotics research. The tremendous number of artificial intelligence algorithms and big data solutions has significantly extended the range of potential applications for robotic technologies, and has also brought new challenges for the artificial intelligence community. Sharing recent advances in the field, the book features papers by young researchers presented at the 4th International Symposium on Artificial Intelligence and Robotics 2019 (ISAIR2019), held in Daegu, Korea, on August 20–24, 2019.
Artificial Intelligence and Security: 5th International Conference, ICAIS 2019, New York, NY, USA, July 26-28, 2019, Proceedings, Part I (Lecture Notes in Computer Science #11632)
by Xingming Sun Zhaoqing Pan Elisa BertinoThe 4-volume set LNCS 11632 until LNCS 11635 constitutes the refereed proceedings of the 5th International Conference on Artificial Intelligence and Security, ICAIS 2019, which was held in New York, USA, in July 2019. The conference was formerly called “International Conference on Cloud Computing and Security” with the acronym ICCCS.The total of 230 full papers presented in this 4-volume proceedings was carefully reviewed and selected from 1529 submissions. The papers were organized in topical sections as follows: Part I: cloud computing; Part II: artificial intelligence; big data; and cloud computing and security; Part III: cloud computing and security; information hiding; IoT security; multimedia forensics; and encryption and cybersecurity; Part IV: encryption and cybersecurity.
Artificial Intelligence and Security: 5th International Conference, ICAIS 2019, New York, NY, USA, July 26–28, 2019, Proceedings, Part IV (Lecture Notes in Computer Science #11635)
by Xingming Sun Zhaoqing Pan Elisa BertinoThe 4-volume set LNCS 11632 until LNCS 11635 constitutes the refereed proceedings of the 5th International Conference on Artificial Intelligence and Security, ICAIS 2019, which was held in New York, USA, in July 2019. The conference was formerly called “International Conference on Cloud Computing and Security” with the acronym ICCCS.The total of 230 full papers presented in this 4-volume proceedings was carefully reviewed and selected from 1529 submissions. The papers were organized in topical sections as follows: Part I: cloud computing; Part II: artificial intelligence; big data; and cloud computing and security; Part III: cloud computing and security; information hiding; IoT security; multimedia forensics; and encryption and cybersecurity; Part IV: encryption and cybersecurity.
Artificial Intelligence and Smart Agriculture: Technology and Applications (Advances in Geographical and Environmental Sciences)
by Kusum Pandey N. L. Kushwaha Chaitanya B. Pande K. G. SinghAs technology continues to saturate modern society, agriculture has started to adopt digital computing and data-driven innovations. This emergence of “smart” farming has led to various advancements in the field, including autonomous equipment and the collection of climate, livestock, and plant data. As connectivity and data management continue to revolutionize the farming industry, empirical research is required to understand these technological developments. This book explores the applications of various artificial intelligence techniques by identifying and describing technical, functional, and non-functional future technologies for smart farming and agriculture. The book also presents practical application opportunities for the resolution of real-world problems, including contributions from precision irrigation, greenhouse data, livestock monitoring, automation, IoT ecosystems for agriculture, cloud computing, mobile robots for precision agriculture, remote sensing applications, anddata mining. In addition, this book provides summary information about different soilless techniques such as hydroponics, aeroponics, and aquaponics, among others. This book is ideally designed for farmers, agriculturalists, product managers, farm holders, manufacturers, equipment suppliers, industrialists, governmental professionals, researchers, academicians, and students seeking current research on technological applications within agriculture and farming.
Artificial Intelligence and Smart Agriculture Applications
by Utku KoseAn essential resource work for understanding how to design and develop smart applications for present and future problems of the field of agriculture.— Dr. Deepak Gupta, Maharaja Agrasen Institute of Technology, Delhi, India As a result of the advances in Artificial Intelligence (AI), many aspects of daily life have been transformed by smart digital technology. Advanced intelligent algorithms can provide powerful solutions to real-world problems. Smart applications have become commonplace. All areas of life are being changed by smart tools developed to deal with complex issues challenging both humanity and the earth. Artificial Intelligence and Smart Agriculture Applications presents the latest smart agriculture applications developed across the globe. It covers a broad array of solutions using data science and AI to attack problems facing agriculture worldwide. Features: Application of drones and sensors in advanced farming A cloud-computing model for implementing smart agriculture Conversational AI for farmer's advisory communications Intelligent fuzzy logic to predict global warming’s effect on agriculture Machine learning algorithms for mapping soil macronutrient elements variability A smart IoT framework for soil fertility enhancement AI applications in pest management A model using Python for predicting rainfall The book examines not only present solutions but also potential future outcomes. It looks at the role of AI-based algorithms and the almost infinite combinations of variables for agricultural applications. Researchers, public and private sector representatives, agriculture scientists, and students can use this book to develop sustainable and solutions for smart agriculture. This book’s findings are especially important as the planet is facing unprecedented environmental challenges from over-farming and climate change due to global warming.