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English
Wiley-Scrivener
11 September 2024
The main goal of Smart Agritech: Robotics, AI, and Internet of Things (IoT) in Agriculture is to explore how emerging technologies such as robotics, artificial intelligence (AI), and IoT can be leveraged to improve efficiency, sustainability, and productivity in agriculture.

Agriculture has always been a vital sector of the global economy, providing food and raw materials for industries and households. However, with the growing population, changing climate conditions, and limited resources, the agriculture sector faces numerous challenges. To address these challenges, farmers and agricultural companies are turning to advanced technologies such as Robotics, Artificial Intelligence (AI), and the Internet of Things (IoT).

This exciting new volume provides a comprehensive overview of the latest technological advances in agriculture, focusing on these three cutting-edge technologies. The book will explore the potential benefits of these technologies in improving agricultural efficiency, productivity, and sustainability.

Whether for the veteran engineer, scientist in the lab, student, or faculty, this groundbreaking new volume is a valuable resource for researchers and other industry professionals interested in the intersection of technology and agriculture.
Edited by:   , , , , , , , ,
Imprint:   Wiley-Scrivener
Country of Publication:   United States
Weight:   1.134kg
ISBN:   9781394302956
ISBN 10:   1394302959
Pages:   592
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Hardback
Publisher's Status:   Active
1. Introduction to Smart Farming: Definition, Importance and Trends 2. Overview of Robotics in Agriculture: Types and Applications 3. The Role of AI in Precision Agriculture: Algorithms and Techniques 4. The Internet of Things (IoT) in Agriculture: Sensors, Networks, and Communication Protocols 5. Smart Irrigation Systems: Design, Implementation, and Benefits 6. Crop Management using Smart Sensors: Challenges and Opportunities 7. Drones in Agriculture: Mapping, Monitoring, and Decision-making 8. Autonomous Farming: Challenges, Opportunities, and Future Outlook 9. Data Analytics in Agriculture: Predictive Models and Real-time Decision-making 10. Smart Greenhouses: Design, Automation, and Performance Optimization 11. Challenges and Barriers to Smart Farming Adoption

Santosh Kumar Srivastava, PhD, is an assistant professor in the Department of Computer Science and Engineering, School of Computing Science and Engineering, Galgotias University, Uttar Pradesh, India, since 2022. He completed his PhD in Computer Science and Engineering in 2021 from Shri JJT University, Jhunjhunu, Rajasthan, India. He has 20 years of IT administration, research, and academic experience and has published over 15 papers in reputed scientific journals and conferences. He also has five patents to his credit and is a member of IEEE, ACM, and other professional societies. Durgesh Srivastava, PhD, is an associate professor at Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India. He received his PhD degree in computer science and engineering from IKG Punjab Technical University, Jalandhar, Punjab, India in 2020. He has over 14 years of research and academic experience and has published over 30 papers in reputed scientific journals and conferences. He has published several patents and one book. Korhan Cengiz, PhD, is an associate professor in the department of Computer Engineering, Istinye University, Istanbul, Turkey. He earned his PhD in electronics engineering from Kadir Has University, Turkey in 2016. He has published more than 40 articles in scientific journals, holds five international patents, has published more than ten book chapters, and one book. He has edited over 20 books and is the Associate Editor of IEEE Transactions on Intelligent Transportation Systems, IEEE Potentials Magazine, and holds editor positions with other reputed scientific publishers. He has presented more than 40 keynote talks at reputed conferences, and he has earned numerous awards for his research. Pramod Gaur, PhD, is an assistant professor of computer science in the Department of Computer Science, BITS Pilani Dubai Campus, Dubai, UAE. He received his PhD from Ulster University, U.K., in 2018. Previously, he also worked as Assistant Professor at the LNMIIT, Jaipur, and a Postdoctoral RA in Neuro-Imaging Technology with the Intelligent Systems Research Centre, Ulster University. His research interests include brain-computer interface, the analysis of non-stationary signals, and machine learning.

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