Agriculture & Allied Sciences

Sustainable Smart Agriculture 2.0, Volume 2
Volume 2: Transforming Precision Farming with Artificial Intelligence and Machine Learning Models

Editors: Gnanasankaran Natarajan, MCA, PhD, RUSA PDF
Saravanan Chandran, PhD
Subrata Chowdhury, PhD
B. Surendiran, PhD

Sustainable Smart Agriculture 2.0, Volume 2

In Production
Pub Date: Forthcoming April 2026
Hardback Price: $200 US | £150 UK
Hard ISBN: 9781779643988
E-Book ISBN: 978-1-77964-399-5
Pages: Est 322pp w index
Binding Type: hardbound / ebook

This new two-volume book set offers comprehensive information on the latest technological advancements and promising smart farming techniques that offer a significant means of preserving sustainability in both precision and smart farming in the modern farming environment.

The volumes demystify contemporary smart farming methods used worldwide to produce a variety of health food crops, preserve the longevity of crops, grow multiple crops more efficiently, and provide a range of resources required for successful smart farming techniques and better decision-making capability. The chapters explore the cutting-edge smart technologies such as artificial intelligence, robotics, drones, machine learning and deep learning algorithms, computer vision, edge computing, the Internet of Things, modern advanced sensors, data science and analytics, sensors, solar-based applications, and classification techniques for increased crop yield while also explaining the distinctions between traditional and modern farming methods.

The volumes are:
Volume 1: Drones, Robots and Intelligent Computing: Redefining Precision Agriculture

Volume 2: Artificial Intelligence and Machine Learning Models: Transforming Precision Farming


Serving as a useful resource for in-depth knowledge about preserving agricultural sustainability worldwide with the latest technological advancements, these two volumes will be of benefit and interest to government and private agricultural professionals as well agricultural researchers and faculty and students in agricultural science interested in the field of smart farming and precision agriculture.

Click here for Sustainable Smart Agriculture 2.0, Volume 1: Redefining Precision Agriculture with Drones, Robots, and Intelligent Computing

Click here for Sustainable Smart Agriculture 2.0, 2-volume set

CONTENTS:
Preface

1. The Transformative Influence of AI in Farming: Practical Examples and Roadblocks
Prakash J., Anitha G., and Gnanasankaran Natarajan

2. AI-ML Decision System for Effective Farming: Optimizing Pesticide and Fertilizer Selection Using Crop Survey Data
Padmavati E. Gundgurti, Suparna Das, Sivaraman Eswaran, and Nara Poojitha

3. From Field to Edge: AI-Enabled Robotics in Rice Farming: Monitoring, Control, and Sustainability
Sharon Christa, Suma V., Surendiran Balasubramanian, Riya Sharma, and Aditya Pai H.

4. The Importance of Machine Learning and Deep Learning Algorithms in Precision Agriculture
Latha Narayanan Valli, N. Sujatha, Mukul Mech, and Lokesh V. S.

5. The Modern Way to Analyze Crop Disease Using Machine Learning Methods: A Detailed Study
G. B. Govindaprabhu, T. S. Urmila, C. Jayapratha,Gnanasankaran Natarajan, and M. Sumathi

6. Unveiling Machine Learning Solutions for Crop Disease Prediction
Sandhya Soman, Suresh K., Gnanasankaran Natarajan, Cecil Donald, and Sundaravadivazhagan Balasubramaniam

7. Machine Learning and Deep Learning Algorithms for Crop Monitoring
Mahalakshmi Jeyabalu, Balakrishnan Chinnayan, Gnanasankaran Natarajan, and Gayathry S. Warrier

8. Early Detection of Crop Diseases in Indian Cash Crops Using Transfer Learning and Vision Transformers Models
S. Muthukumar, S. M. Keerthana, S. Murugaanandam, G. Smilarubavathy, and R. Sarath Kumar

9. Analyzing and Selecting Optimal Pesticide and Fertilizer Using ResNet-152
V. Sudha, S. Hemalatha, U. Hemalatha, S. Sangeetha, and S. Tamil Selvi

10. Harnessing Data Analytics for Precision Agriculture and Enhanced Crop Monitoring
Tina Babu, Rekha R. Nair, Ebin P. M., and Kishore S.

11. Role of Data Analytics in Precision Agriculture and Crop Monitoring
Mohamed Ansari Raja, Parvin Banu, Nooriya Begam, Ramasamy Vidhyavathi, and B. Sundaravadivazhagan

12. Artificial Intelligence-Based Models for Predicting Soil Hydraulic and Cracking
Rakesh Gnanasekaran, Gnanasankaran Natarajan, and M. Karthikeyan

Index


About the Authors / Editors:
Editors: Gnanasankaran Natarajan, MCA, PhD, RUSA PDF
Assistant Professor, Department of Computer Science, Thiagarajar College, Madurai, India

Gnanasankaran Natarajan, MCA, PhD, RUSA PDF, is presently working as an Assistant Professor in the Department of Computer Science, Thiagarajar College, Madurai, India. He has 15 years of teaching and over 14 years of research experience. His areas of research specialization include software engineering, SQA, data science, machine learning, big data, and IoT. He has contributed to more than 35 research articles in Scopus- and Web of Science-indexed journals and conferences from IEEE, Elsevier, Springer, Tech Science Press etc. He has also contributed to one textbook publication and four edited book volumes. He has published 14 book chapters with prominent publishers such as Taylor and Francis, CRC Press, Routledge, etc. He holds eight patent works (two Indian design and one utility patent, three UK design patents, two German utility patents) in the field of cyber security, IoT, drone technology, and healthcare. He has secured major and minor funded projects from the University Grants Commission, India. He is also a review committee member for many Scopus- and SCI-indexed journals. He has organized many seminars, workshops, and faculty development programs at various institutions and is a life member of several societies.

Saravanan Chandran, PhD
Associate Professor, Department of Computer Science and Engineering, National Institute of Technology, Durgapur, West Bengal, India

Saravanan Chandran, PhD, is currently an Associate Professor in the Department of Computer Science and Engineering at the National Institute of Technology, Durgapur, India. He has over 27 years of teaching experience. His academic career spans more than two decades, specializing in research areas such as digital image processing, computer vision, and biometrics. He had the privilege of engaging in collaborative research at the University of Texas, Arlington, USA, under the TEQIP–I project, resulting in the publication of an IEEE conference paper. He successfully guided two faculty members in completing their PhD degrees under his joint supervision. He is a member of the Information Security Education and Awareness (ISEA) Phase I & II projects as well as TEQIP–I and II projects. His scholarly achievements include securing two patents, publishing three books, contributing to four book chapters, and authoring 118 research articles in international peer-reviewed journals and conferences. He has guided eight research scholars to PhD completion with over 80 students in other higher education pursuits. He has also organised numerous conferences, seminars, and workshops. He serves as a reviewer for leading publishers such as IEEE, Springer, Elsevier, Taylor & Francis, and ACM, and is a board member for several peer-reviewed international journals.

Subrata Chowdhury, PhD
Associate Professor, Department of the Computer Science of Engineering, Sreenivasa, Institute of Technology and Management, India

Subrata Chowdhury, PhD, is working in the Department of the Computer Science of Engineering at the Sreenivasa Institute of Technology and Management, India, as an Associate Professor. He has been working in the IT industry for more than five years in the R&D department. He has also been handling projects related to AI, blockchain, and cloud for various national and international clients. He had published four books with international publishers such as CRC Press and River Publishers. He has also served as the editor for two books. He has participated in the organizing committees and technical programmed committees and as a guest speaker for more than 10 conference and webinars. He has also reviewed and evaluated more than 50 papers for conferences, journals, book chapters and science articles in AI, data science, IoT, blockchain and cloud computing for CRC, Springer, Elsevier, Emerald, etc. He is the Associate Editor for the Journal of Engineering (JoE), published by Institution of Engineering and Technology and Wiley. He has taken part in various workshops, webinars, and faculty development programs as a resource person. He has published more than 30 papers and has copyrights and patents to his name. He has been awarded by various international and nationals science societies for his contributions in the R&D field. He has received travel grants and is also a member of the IET, IEEE, ISTE, ACM, and other accretional bodies.

B. Surendiran, PhD
Associate Professor, Department of Computer Science and Engineering, NIT Puducherry, Karaikal, India

B. Surendiran, PhD, currently working as Associate Professor in the Department of Computer Science and Engineering at NIT Puducherry, Karaikal, India. He has over 15 years of teaching and research experience. He has delivered more than 100 guest lectures and reviewed over 1000 research papers. He has published more than 100 research papers to his credit. He has received a top reviewer award from Publons in the year 2019. He has three funded research projects as principal investigator or co- principal investigator. His areas of interest include machine learning, medical imaging, dimensionality reduction, and recommender systems. He completed his MTech CSE at VIT Vellore and PhD at NIT Trichy, India.




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