Artificial Intelligence and Smart Agriculture Applications

An 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. "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 the Earth and humanity. 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. Highlights of the book include: 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"-- Provided by publisher Cover Half Title Title Page Copyright Page Contents Foreword Preface Acknowledgments Editors Contributors 1. Application of Drones and Sensors in Advanced Farming: The Future Smart Farming Technology 2. Development and Research of a Greenhouse Monitoring System 3. A Cloud-Computing Model for Implementing Smart Agriculture 4. Application of Conversational Artificial Intelligence for Farmer’s Advisory and Communication 5. The Use of an Intelligent Fuzzy Logic Controller to Predict the Global Warming Effect on Agriculture: Case of Chickpea (Cicer arietinum L.) 6. Using Machine Learning Algorithms to Mapping of the Soil Macronutrient Elements Variability with Digital Environmental Data in an Alluvial Plain 7. A Smart IoT Framework for Soil Fertility Enhancement Assisted via Deep Neural Networks 8. Plant Disease Detection with the Help of Advanced Imaging Sensors 9. Artificial Intelligence-Aided Phenomics in High-Throughput Stress Phenotyping of Plants 10. Plant Disease Detection Using Hybrid Deep Learning Architecture in Smart Agriculture Applications 11. Classification of Coffee Leaf Diseases through Image Processing Techniques 12. The Use of Artificial Intelligence to Model Oil Extraction Yields from Seeds and Nuts 13. Applications of Artificial Intelligence in Pest Management 14. Applying Clustering Technique for Rainfall Received by Different Districts of Maharashtra State 15. Predicting Rainfall for Aurangabad Division of Maharashtra by Applying Auto-Regressive Moving Average Model (ARIMA) Using Python Programming Index In this book, the recent applications of Artificial Intelligence for smart agriculture have been gathered to provide a valuable source for the literature. Applications vary from use of Machine and Deep Learning to image processing systems. The book aims to provide information on smart methods and intense data processing phases.