Can Digital Intelligence and Cyber-Physical-Social Systems Achieve Global Food Security and Sustainability?  

作　　者：Yanfen Wang Mengzhen Kang Yali Liu Juanjuan Li Kai Xue Xiujuan Wang Jianqing Du Yonglin Tian Qinghua Ni Fei-Yue Wang 

机构地区：[1]College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100049 [2]Beijing Yanshan Earth Critical Zone National Research Station,University of Chinese Academy of Sciences,Beijing 101408 [3]State Key Laboratory of Tibetan Plateau Earth System,Environment and Resources,Institute of Tibetan Plateau Research,Chinese Academy of Sciences,Beijing 100101,China [4]State Key Laboratory of Multimodal Artificial Intelligence Systems,Institute of Automation,Chinese Academy of Sciences(CASIA),Beijing 100190 [5]School of Artificial Intelligence,University of Chinese Academy of Sciences,Beijing 100049,China [6]School of Grassland Science,Beijing Forestry University,Beijing 100083,China [7]State Key Laboratory of Multimodal Artificial Intelligence Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China [8]State Key Laboratory of Plateau Ecology and Agriculture,Qinghai University,Xining 810016 [9]Key Laboratory of Adaptation and Evolution of Plateau Biota,Northwest Institute of Plateau Biology,Chinese Academy of Sciences,Xining 810001 [10]Binzhou Institute of Technology,Weiqiao-UCAS Science and Technology Park,Binzhou 256606,China [11]Beijing Yanshan Earth Critical Zone National Research Station,University of Chinese Academy of Sciences,Beijing 101408,China [12]Department of Engineering Science,Faculty of Innovation Engineering,Macao University of Science and Technology,Macao 999078 [13]State Key Laboratory of Multimodal Artificial Intelligence Systems,Institute of Automation,Chinese Academy of Sciences(CASIA),Beijing 100190,China [14]Faculty of Innovation Engineering,Macao University of Science and Technology,Macao 999078 [15]Beijing Engineering Research Center of Intelligent Systems and Technology,Chinese Academy of Sciences,Beijing 100098 [16]State Key Laboratory for Management and Control of Complex Systems,Chinese Academy of Sciences,Beijing 100190,China [17]IEEE

出　　处：《IEEE/CAA Journal of Automatica Sinica》2023年第11期2070-2080,共11页自动化学报（英文版）

基　　金：supported in part by the National Key Research and Development Program of China (2021ZD0113704);the National Natural Science Foundation of China (62076239, 42041005,62103411);the Science and Technology Development Fund;Macao SAR(0050/2020/A1)。

摘　　要：Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship. Agricultural production can be regarded as a form of carbon sequestration behavior.From the perspective of the natural-social-economic complex ecosystem, excessive water usage in food production will aggravate regional water pressure for both domestic and industrial purposes. Hence, achieving a harmonious equilibrium between carbon and water resources during the food production process is a key scientific challenge for ensuring food security and sustainability. Digital intelligence(DI) and cyber-physical-social systems(CPSS) are emerging as the new research paradigms that are causing a substantial shift in the conventional thinking and methodologies across various scientific fields, including ecological science and sustainability studies. This paper outlines our recent efforts in using advanced technologies such as big data, artificial intelligence(AI), digital twins, metaverses, and parallel intelligence to model, analyze, and manage the intricate dynamics and equilibrium among plants, carbon, and water in arid and semiarid ecosystems. It introduces the concept of the carbon-water balance and explores its management at three levels: the individual plant level, the community level, and the natural-social-economic complex ecosystem level. Additionally, we elucidate the significance of agricultural foundation models as fundamental technologies within this context. A case analysis of water usage shows that, given the limited availability of water resources in the context of the carbon-water balance, regional collaboration and optimized allocation have the potential to enhance the utilization efficiency of water resources in the river basin. A suggested approach is to consider the river basin as a unified entity and coordinate the relationship between the upstream, midstream and downstream areas. Furthe

关 键 词：Carbon-water balance DECISION-SUPPORT digital intelligence(DI) foundation models planning 

分 类 号：TP399[自动化与计算机技术—计算机应用技术] F49[自动化与计算机技术—计算机科学与技术] F113[经济管理—产业经济]