This book provides extensive information about smart farming, precision agriculture and the technologies that make them succeed. The authors provide detailed machine learning and deep learning models and algorithms that can be implemented effectively to improve smart farming methods. The authors also give elaborate information about the various IoT devices and types of drones that are used vastly in smart farming culture. The authors show specifically how methods and techniques used to improve the crop yield can be executed to help the farmers to improve the agricultural process and cultivation methods using a rule-based methodology. The purpose of this book is to articulate the need for processes, platforms, practices, patterns, and rules to be followed for the better yield of crop production and how IoT, robotics and drones can be used to improve the economy of the countries in the field of agriculture. In a nutshell, the book shows how the combination of multiple cutting-edge technologies leads to the realization of state-of-the-art infrastructures for next-generation agriculture.

Provides insight on collecting and analyzing data using machine learning and deep learning methods for smart farming Includes detail on how to use AI, IoT, drone technology and robotics effectively in smart farming Details irrigation methods, soil classification, and prominent cultivation tools that can be improved using technology

Autorentext

Dr. B. Sundaravadivazhagan is an experienced researcher and educator in the field of Information and Communication Engineering. He has more than 22 years of experience in teaching and research and has earned his Ph.D. in Information and Communication Engineering from Anna University in Chennai in 2016. He is a member of various professional bodies such as IEEE, ISACA, ISTE, and ACM, and has published over 45 research articles in SCI and Scopus journals. He has also served as a resource person, keynote speaker, and advisory committee member in more than 20 international and national conferences. He has received two research grants from the Ministry of Higher Education, Research and Innovation, The Research Council (TRC), Oman. His research interests include IoT, AI and Machine learning, Deep learning, Cloud computing, Networks and security, Wireless networks, and MANET. He is a reputable journal editor and reviewer and also serves on the Doctoral Committee in International CommitteeMember- Amrita University, Bangalore, as well as an Adjunct Faculty in Saveetha School of Engineering, Chennai. In addition to his research publications, he has also authored and edited several books, including "Performance Analysis of Broadcast Schemes in MANET" published by LAMBERT Academic Publishing, Germany and "Leveraging Artificial Intelligence (AI) Competencies for Next-Generation Cybersecurity Solutions" published by Apple Academic Press, Exclusive Co-Publishing with CRC press Taylor and Francis Group, USA. He has also proposed and received approval for several upcoming book publications, such as "Deep Learning for Smart Healthcare: Trends, Challenges and Applications" approved by CRC Taylor and Francis Group Publisher, "Demystifying Probability and Statistics for Data Scientists with R" accepted by CRC Taylor and Francis Group, and "The Power of Artificial Intelligence for the Next-Generation Oil & Gas Industry: Envisaging AI-inspired Intelligent Energy Systems & Environments" accepted by IEEE and Wiley Publishers,"

Dr. N. Gnanasankaran MCA., Ph.D., RUSA PDF,. Is presently working as an Assistant Professor in the Department of Computer Science, Thiagarajar College, Madurai, India. He has 14 Years of Teaching and 13 years of Research Experience. His areas of research specialization include Software Engineering, SQA, Data Science, Machine Learning, Big Data and IOT. He pursued his Masters in Computer Application (2008) and Doctorate in Computer Science (2014) from Madurai Kamaraj University, Madurai, Tamilnadu, India and Completed his Post Doc in Computer Science (2020) from Alagappa University, Karaikudi, Tamilnadu, India. He has contributed more than 35 research articles in Scopus and Web of Science Indexed journals from IEEE, Elsevier, Tech Science Press and contributed 5 Book Chapters in prominent Publishers such as Taylor and Francis, CRC Press, De Gruyter, IEEE River publishers. He holds two patent work in the field of IoT and secured major and minor funded projects from UGC, India.

C. Pethuru Raj PhD is a chief architect at the Edge AI division of Reliance Jio Platforms Ltd. (JPL) Bangalore. Previously. worked in IBM Global Cloud Centre of Excellence (CoE), Wipro consulting services (WCS), and Robert Bosch Corporate Research (CR). I have gained over 22 years of IT industry experience and 9 years of research experience. Finished the CSIR-sponsored PhD degree at Anna University, Chennai, and continued with the UGC-sponsored postdoctoral research in the Department of Computer Science and Automation, Indian Institute of Science (IISc), Bangalore. After that, I was granted two international research fellowships (JSPS and JST) to work as a research scientist for 3.5 years in two leading Japanese universities. 

I am focusing on some of the emerging technologies such as the Internet of Things (IoT), Artificial Intelligence (AI) Model Optimization Techniques, Prompt Engineering for Large Language Models (LLMs), Efficient, Explainable, and Edge AI, Blockchain, Digital Twins, Cloud-native and Edge computing, Green and Generative AI, Reliability and Platform Engineering, 5G/6G, etc.

Inhalt

Introduction.- Intelligent computing with drones and robotics for Precision Agriculture.- Smart Farming and Precision Agriculture and Its Need in Today's World.- Role of Machine Learning in Smart Farming and Its Applications.- Types of Soil Classification for the Identification of the Right Crop to be Cultivated.- Convergence of IoT, Big Data and Machine Learning for better yield Prediction in Smart Farming.- Soil Classification and Crop Prediction using Machine Learning Techniques.- Artificial Intelligence (AI) enabled Drone Technology for Smart Farming.- Connected Drones for Smart Farming: The Use Cases and Challenges.- Drones and Robots in Smart Agriculture.- IoT-based Precision Agriculture and Crop Management using Machine Learning Approaches.- Smart Organic Agriculture in Traditional South Indian Based Farming System.- Crop and Fertilizer Recommendation System for Sustainable Agricultural Development.- The Role of Robotics and Drones in Precision Farming using Artificial Intelligence with an Automatic Learning Approach.- Applications of UAV-AD (Unmanned Aerial Vehicle-Agricultural Drones) in Precision Farming.- Machine Learning (ML) Algorithms on IoT and Drone Data for Smart Farming.- Recent improvements and major challenges in Digitized farming: A review.- A Comprehensive Review on the Internet of Things, 5G network, Drone Technologies for Smart Agriculture.- Internet of Things based Smart Agriculture Advisory System.- Conclusion.