From Parallel Plants to Smart Plants: Intelligent Control and Management for Plant Growth

Mengzhen Kang; Fei-Yue Wang

doi:10.1109/JAS.2017.7510487

Volume 4 Issue 2

Apr. 2017

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2017 > 4(2): 161-166

Mengzhen Kang and Fei-Yue Wang, "From Parallel Plants to Smart Plants: Intelligent Control and Management for Plant Growth," IEEE/CAA J. Autom. Sinica, vol. 4, no. 2, pp. 161-166, Apr. 2017. doi: 10.1109/JAS.2017.7510487

Citation:

Mengzhen Kang and Fei-Yue Wang, "From Parallel Plants to Smart Plants: Intelligent Control and Management for Plant Growth," IEEE/CAA J. Autom. Sinica, vol. 4, no. 2, pp. 161-166, Apr. 2017. doi: 10.1109/JAS.2017.7510487

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From Parallel Plants to Smart Plants: Intelligent Control and Management for Plant Growth

doi: 10.1109/JAS.2017.7510487

Mengzhen Kang^{1, 2, 3
,},
Fei-Yue Wang^{4, 5, 6
,
,}

1.
Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences (SKL-MCCS, CASIA), Beijing 100190, China
2.
Qingdao Academy of Intelligent Industries, Qingdao 266000, China
3.
Beijing Engineering Research Center of Intelligent Systems and Technology, Beijing 100190, China
4.
Key Laboratory of Management and Control for Complex Systems (SKL-MCCS), Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing 100190, China
5.
School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
6.
Research Center for Military Computational Experiments and Parallel Systems Technology, National University of Defense Technology, Changsha 410073, China

Funds:

This work was supported by the National High Technology Research and Development Program (863 program) of China 2012AA101906-2

the National Natural Science Foundation of China 3140030594

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Author Bio:
Mengzhen Kang (M'16) is an associate professor with the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences. Her current research interests include parallel agriculture and computational plant sciences. She has published over 50 scientific papers in her research field. She received her Ph.D. degree in pattern recognition and intelligent systems from Institution of Automation, Chinese Academy of Sciences in 2003. From 2005-2006, she was a postdoctoral fellow with DigiPlante, INRIA in France and Plant Sciences, Wageningen University in Netherland. She organized the international conference on Functional-Structural Plant Growth Modeling, Simulation, Visualization and Application (PMA'12 and FSPMA2016) as the general co-chair from China (e-mail: mengzhen.kang@ia.ac.cn)
Corresponding author: Fei-Yue Wang (S'87-M'89-SM'94-F'03) received his Ph. D. in computer and systems engineering from Rensselaer Polytechnic Institute, Troy, New York in 1990. He joined the University of Arizona in 1990 and became a professor and director of the Robotics and Automation Lab (RAL) and Program in Advanced Research for Complex Systems (PARCS). In 1999, he founded the Intelligent Control and Systems Engineering Center at the Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China, under the support of the Outstanding Overseas Chinese Talents Program from the State Planning Council and "100 Talent Program" from CAS, and in 2002, was appointed as the director of the Key Lab of Complex Systems and Intelligence Science, CAS. In 2011, he became the State Specially Appointed Expert and the Director of The State Key Laboratory of Management and Control for Complex Systems. Dr. Wang's current research focuses on methods and applications for parallel systems, social computing, and knowledge automation. He was the Founding Editor in-Chief of the International Journal of Intelligent Control and Systems (1995–2000), the Founding EiC of the IEEE ITS Magazine (2006–2007), the EiC of the IEEE Intelligent Systems (2009–2012), and the EiC of the IEEE Transactions on ITS (2009–2016). Currently he is the EiC of the China's Journal of Command and Control. Since 1997, he has served as General or Program Chair of more than 20 IEEE, INFORMS, ACM, ASME conferences. He was the President of IEEE ITS Society (2005–2007), Chinese Association for Science and Technology (CAST, USA) in 2005, the American Zhu Kezhen Education Foundation (2007–2008), and the Vice President of the ACM China Council (2010–2011). Since 2008, he is the Vice President and Secretary General of Chinese Association of Automation. Dr. Wang is elected Fellow of IEEE, INCOSE, IFAC, ASME, and AAAS. In 2007, he received the 2nd Class National Prize in the Natural Sciences of China and awarded the Outstanding Scientist by ACM for his work in intelligent control and social computing. He received the IEEE ITS Outstanding Application and Research Awards in 2009 and 2011, and the IEEE SMC Norbert Wiener Award in 2014. Corresponding author of this paper. (email:feiyue.wang@ia.ac.cn)
Received Date: 2017-01-15
Accepted Date: 2017-03-06

Abstract

Abstract

Precision management of agricultural systems, aiming at optimizing profitability, productivity and sustainability, comprises a set of technologies including sensors, information systems, and informed management, etc. Expert systems are expected to aid farmers in plant management or environment control, but they are mostly based on the offline and static information, deviated from the actual situation. Parallel management, achieved by virtual/artificial agricultural system, computational experiment and parallel execution, provides a generic framework of solution for online decision support. In this paper, we present the three steps toward the parallel management of plant: growth description (the crop model), prediction, and prescription. This approach can update the expert system by adding learning ability and the adaption of knowledge database according to the descriptive and predictive model. The possibilities of passing the knowledge of experienced farmers to younger generation, as well as the application to the parallel breeding of plant through such system, are discussed.
- Artificial intelligence,
- cropping plan,
- management system,
- precision agriculture,
- plant model

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References(37)

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From Parallel Plants to Smart Plants: Intelligent Control and Management for Plant Growth

doi: 10.1109/JAS.2017.7510487

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