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Hyperautomation in Precision Agriculture. Advancements and Opportunities for Sustainable Farming

  • Book

  • November 2024
  • Elsevier Science and Technology
  • ID: 5978242

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. The book 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.

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).

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Table of Contents

Section I: Fundamentals of Hyperautomation technology for sustainable agriculture
1. A global overview and the fundamentals of sustainable agriculture
2. Smart Contracts for Efficient Resource Allocation and Management in Hyperautomated Agriculture Information Systems
3. Towards Smart Farming: Applications of Artificial Intelligence and Internet of Things in Precision Agriculture
4. Hyperautomation in agriculture sector by technological devices towards irrigation, crop harvest and storage
5. AI-Powered Agriculture and Sustainable Practices in Developing Countries

Section II: Smart agriculture automation using advanced technologies
6. A light-weight Deep Learning model for plant disease detection in hyperautomation
7. Mapping and Retrieval of Agricultural Parameters using Artificial Intelligence
8. Sustainable Plant Disease Protection Using Machine Learning and Deep Learning
9. Cereal crop yield prediction using machine learning techniques
10. Estimation of soil properties for sustainable crop production using multisource data fusion

Section III: Advances in remote sensing for precision crop production
11. Detecting the stages of Ragi crop diseases using satellite data in villages of Nanjangud taluk
12. Soil and field analysis using unmanned aerial vehicles (UAV) for smart and sustainable farming
13. Crop Land Assessment with Deep Neural Network using Hyperspectral Satellite Dataset
14. Development of Soil moisture maps using image fusion of MODIS and optical dataset
15. Advance remote sensing technologies for crop disease and pest detection
16. Estimating Soil Moisture in Semi-Arid Areas for Winter Wheat Using Sentinel-1 and Support Vector Algorithms

Section IV: Robotic/Digital Process Automation (RPA/DPA) in agriculture and field applications
17. Autonomous Robotic Leaf Retrieval
18. Robotics-assisted precision and sustainable irrigation, harvesting and fertilizing processes
19. Computer Vision Technology for Weed Detection
20. LiDAR/RADAR robots in monitoring and mapping crop growth for sustainable crop production

Section V: Emerging trends and case studies in Hyperautomation of Sustainable Agriculture
21. Is Hyper-automation is playing a significant role in Smart Agriculture?
22. Predictive Irrigation: Current practice and Future Prospects
23. Design and fabrication of quad copter for agriculture seeding
24. hallenges and future trends in the Hyperautomation of Sustainable Agriculture
25. Techniques and applications of deep learning in smart agriculture systems
26. Investigation of Automated Plant disease detection Framework using Machine Learning Classifier with novel Segmentation and Feature Extraction Strategy
27. Hyperautomation in precision agriculture using different unmanned aerial vehicles (UAV)
28. Emerging Trends of hyperautomation in decision-making process & sustainable crop production
29. Remote sensors for hyper-automation in agriculture

Authors

Sartajvir Singh Centre of Excellence, Socio-Environmental Sustainability for River Sand-mining, Indian Institute of Technology Ropar.

Dr. Sartajvir Singh is currently serving as Chief Scientific Officer at the Center of Excellence in Socio-Environmental Sustainability for River Sand Mining (SENSRS) and Project Director (ICSSR Project) at Indian Institute of Technology Ropar, India. He is a digital image analyst with expertise in remote sensing and earned his PhD in Electronics & Communication Engineering (Outstanding Thesis Awardee, 2018) after completing his M. Tech (Gold Medalist) and B.Tech with Distinction. He is a Registered Indian Patent & Trademark Agent and a DGCA-approved drone operator, with 70+ innovations (35+ patents granted) and 90+ SCI/Scopus-indexed publications. He has secured over four Crore (INR) research funding, received multiple fellowships, held editorial positions, and is an IEEE Senior Member, advancing electronics, image processing, and geospatial intelligence.

Vishakha Sood Centre of Excellence, Socio-Environmental Sustainability for River Sand-mining, Department of Civil Engineering Indian Institute of Engineering. Vishakha Sood is currently working as a Scientist at the Indian Institute of Technology, Ropar, Punjab, under the Women Scientist Scheme (WOS) of the Department of Science and Technology (DST), Government of India. She is also the founder of Aiotronics Automation Pvt. Ltd., supported under the Himachal Pradesh Chief Minister Startup Scheme. She received her Ph.D. in Electronics and Communication Engineering from Chitkara University, Punjab, in 2020. She earned her B.Tech. degree from Himachal Pradesh University in 2008 and her M.Tech. degree in Electronics and Communication Engineering from Punjab Technical University in 2011. She also completed an MBA in Human Resource Management in 2010. She has extensive academic and research experience and has authored research articles in SCI-indexed journals and SCOPUS-indexed book chapters and holds several inventions. Her research interests include satellite sensors, remote sensing, and digital image analysis. She is a Senior Member of IEEE and an active member of professional bodies including the Indian Society of Remote Sensing (ISRS), Indian Society for Technical Education (ISTE), Punjab Science Congress (Punjab Academy of Sciences), IEEE Sensors Council, IEEE Geoscience and Remote Sensing Society, IEEE Women in Engineering, and the European Geosciences Union (EGU). Arun Lal Srivastav Chitkara University, Himachal Pradesh, Solan, India. Dr. Arun Lal Srivastav is an Professor and Associate Dean (Research)Department of Applied Sciences and EngineeringTula's Institute Dehradun - 248011, Uttarakhand, India Yiannis Ampatzidis Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, USA..

Dr. Ampatzidis is an Associate Professor leading a research and extension precision agriculture engineering program at the Southwest Florida Research and Education Center (SWFREC) in Immokalee, Florida. He received his B.S. in Agriculture Science in 2002 from the Aristotle University of Thessaloniki (AUTH) in Thessaloniki, Greece, with a major in row crops and ecology. After completing his bachelor's degree, he enrolled in the Agricultural Engineering department and completed his M.S. in 2005 with an emphasis on precision agriculture and robotics. At the same time, he completed his second bachelor's degree in Hydraulics, Soil Science and Agricultural Engineering in 2008 (AUTH). He received his PhD in Agricultural Engineering from AUTH in 2010 with an emphasis on precision agriculture and automation for specialty crops. His current research focuses on the mechanical harvesting of specialty crops, mechatronics, artificial intelligence, machine vision, precision agriculture, smart machines (e.g., smart spraying technologies), UAVs, and machine systems.