Hyperautomation in Precision Agriculture: Advancements and Opportunities for Sustainable Farming

Hyperautomation in Precision Agriculture: Advancements and Opportunities for Sustainable Farming is the first book to focus on the integration of multiple techniques and technologies to create an ecosystem sustaining approach that doesn’t compromise soil health or environmental safety as it increases crop yield.Hyperautomation is a true digital transformation in sustainable agriculture utilizing advanced techniques such as robotic process automation (RPA), digital process automation (DPA), unmanned aerial vehicle (UAV), controlled-environment agriculture (CEA), remote sensing, internet of things (IoT), crop modeling, precision farming, sustainable yield, image analysis, data fusion, artificial intelligence (AI), machine learning (ML) and deep learning (DL).Hyperautomation in Precision Agriculture: Advancements and Opportunities for Sustainable Farming highlights the integration of state-of-the-art tools and working models to address the various challenges in the field of agriculture. It also identifies and discusses the potential and challenges of hyperautomation in sustainable agriculture with respect to efficiency improvement and human enhancement of automated operations. Provides a comprehensive overview of the current state of the art of automation in agricultureEnables improved productivity and resource optimizationPresents advanced monitoring/mapping methods in soil properties and nutrients, crop growth and yield INDICE: Section I: Fundamentals of Hyperautomation technology for sustainable agriculture1. A global overview and the fundamentals of sustainable agriculture2. Smart Contracts for Efficient Resource Allocation and Management in Hyperautomated Agriculture Information Systems3. Towards Smart Farming: Applications of Artificial Intelligence and Internet of Things in Precision Agriculture4. Hyperautomation in agriculture sector by technological devices towards irrigation, crop harvest and storage5. AI-Powered Agriculture and Sustainable Practices in Developing CountriesSection II: Smart agriculture automation using advanced technologies6. A light-weight Deep Learning model for plant disease detection in hyperautomation7. Mapping and Retrieval of Agricultural Parameters using Artificial Intelligence8. Sustainable Plant Disease Protection Using Machine Learning and Deep Learning9. Cereal crop yield prediction using machine learning techniques10. Estimation of soil properties for sustainable crop production using multisource data fusionSection III: Advances in remote sensing for precision crop production11. Detecting the stages of Ragi crop diseases using satellite data in villages of Nanjangud taluk12. Soil and field analysis using unmanned aerial vehicles (UAV) for smart and sustainable farming13. Crop Land Assessment with Deep Neural Network using Hyperspectral Satellite Dataset14. Development of Soil moisture maps using image fusion of MODIS and optical dataset15. Advance remote sensing technologies for crop disease and pest detection16. Estimating Soil Moisture in Semi-Arid Areas for Winter Wheat Using Sentinel-1 and Support Vector AlgorithmsSection IV: Robotic/Digital Process Automation (RPA/DPA) in agriculture and field applications17. Autonomous Robotic Leaf Retrieval18. Robotics-assisted precision and sustainable irrigation, harvesting and fertilizing processes19. Computer Vision Technology for Weed Detection20. LiDAR/RADAR robots in monitoring and mapping crop growth for sustainable crop productionSection V: Emerging trends and case studies in Hyperautomation of Sustainable Agriculture21. Is Hyper-automation is playing a significant role in Smart Agriculture?22. Predictive Irrigation: Current practice and Future Prospects23. Design and fabrication of quad copter for agriculture seeding24. hallenges and future trends in the Hyperautomation of Sustainable Agriculture25. Techniques and applications of deep learning in smart agriculture systems26. Investigation of Automated Plant disease detection Framework using Machine Learning Classifier with novel Segmentation and Feature Extraction Strategy27. Hyperautomation in precision agriculture using different unmanned aerial vehicles (UAV)28. Emerging Trends of hyperautomation in decision-making process & sustainable crop production29. Remote sensors for hyper-automation in agriculture

• ISBN: 978-0-443-24139-0
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 400
• Fecha Publicación: 01/11/2024
• Nº Volúmenes: 1
• Idioma: Inglés