Contemporary Developments in Agricultural Cyber-Physical Systems

Contemporary Developments in Agricultural Cyber-Physical Systems

Release Date: August, 2023|Copyright: © 2023 |Pages: 293
DOI: 10.4018/978-1-6684-7879-0
ISBN13: 9781668478790|ISBN10: 166847879X|EISBN13: 9781668478813
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Description & Coverage
Description:

The cultivation of crops plays a very important role in agriculture. However, proper maintenance and management are required. Lack of such management would lead to crop loss or reduced crop yields. Hence, the ability to detect and identify diseases on infected crops is a problem of increasing concern. Real-time disease detection systems do not exist in the current agricultural landscape. It requires tremendous amounts of work, expertise in plant diseases, and excessive processing time. Using precision agriculture techniques, combined with AI, a great deal of work is reduced.

Contemporary Developments in Agricultural Cyber-Physical Systems provides a forum for researchers and practitioners to exchange ideas and achieve progress in cyber-physical systems by highlighting agricultural applications, advances, and research challenges. The book features chapters on all aspects pertaining to this multidisciplinary paradigm, in particular in its application to sustainable agriculture developments. Covering topics such as automation, monitoring systems, and smart agriculture, this premier reference source is an excellent resource for scientists, healthcare professionals, data analysts, computer scientists, students and educators of higher education, researchers, and academicians.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Agricultural Cyber-Physical Systems
  • Automation
  • Experimental Studies
  • Internet of Things (IoT)
  • Irrigation Systems
  • Monitoring Systems
  • Nanoscience
  • Precision Agriculture
  • Smart Agriculture
  • Technology Integration
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Editor/Author Biographies
|G. S. Karthick - Editor| is currently working as an Assistant Professor in the Department of Software Systems, PSG College of Arts & Science, Coimbatore, India. Previously, he worked as a Research Fellow under the DST-ICPS Project from April 2019 to March 2022 in the Department of Computer Science, School of Computer Science and Engineering, Bharathiar University, Coimbatore, India. Also, he worked as an Assistant Professor in the Department of Computer Science, Sri Ramakrishna College of Arts and Science, Coimbatore, India. Previously, he worked as an Assistant Professor in the Department of Computer Science, Sri Ramakrishna College of Arts and Science, Coimbatore, India. He received his Ph.D. in Computer Science from Bharathiar University (University Department) in February 2023. He topped the Post-Graduation with Gold Medal in 2017 from Bharathiar University, Coimbatore, India. He topped Under-Graduation with an exemplary performance from SNR Sons College, Coimbatore, India, and also aced three subjects to receive gold medals in 2015. He has qualified UGC-NET Computer Science and Applications in December 2020. Further, he has visited many institutions and universities as a resource person at various events. He has received an Indian Patent Grant for his innovative contribution to the field of Wireless Networks and the Internet of Things. He has published research papers in international journals and presented papers at International and National Conferences. He has published many book chapters and in addition, he has edited one book and authored two books. He is an active Editorial Member of IJHIS, IJERTCS, and IJEHMC. Also, he is an active reviewer in high-standard journals of Elsevier, IEEE, Springer, IGI Journals, and many peer-reviewed journals. He has received many awards and rewards for his achievements in academic and research careers. His areas of specialization are Machine Learning, the Internet of Things, Wireless Sensor Networks, and Analysis of Algorithms. His current research interests focus on the recent developments in the healthcare Internet of Things and Machine Learning Algorithms.
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