社会 5.0 支持农业:驱动因素、使能技术、架构、机遇和挑战

IF 7.7 Q1 AGRICULTURE, MULTIDISCIPLINARY
Kossi Dodzi Bissadu, Salleh Sonko, Gahangir Hossain
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引用次数: 0

摘要

现有的农业实践面临许多挑战,无法满足不断增长的人口的一些最关键的需求。粮食不安全、智能农业的高初始成本、全球范围内严重的农业劳动力短缺、与饥荒、贫困、气候变化相关的经济、社会和政治危机以及农业4.0的技术重点要求我们重新思考农业范式。此外,日本政府提出的社会5.0理念引发了政策制定者、政府、私人机构、学者和研究人员的许多立场反应。最近,以人为中心的社会概念引起了学者们的关注,在这个社会中,每个人都有对幸福、社会和谐、可持续性和弹性的共同愿景,从而充分享受自己的生活。一些研究人员调查了社会5.0及其关键组成部分,包括农业5.0。农业5.0不仅可以用来解决许多现有的问题,而且可以成为实现社会5.0目标的主要推动力。本文采用系统的文献综述方法,研究了农业5.0的主要驱动因素、前沿技术、发展、采用和实施农业5.0的各种机遇和挑战。强调了基于12层农业5.0范式的整体整体架构框架。“农业5.0”虽然为年轻一代创造新的就业机会、促进大规模定制等带来了很多机会,但也面临着许多潜在的挑战。一些挑战包括网络安全和隐私问题,由于高度自动化和大规模个性化,难以建立有效的法律、监管和合规系统,标准化问题,以及使农业生产战略和模式适应不断变化的客户偏好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Society 5.0 enabled agriculture: Drivers, enabling technologies, architectures, opportunities, and challenges
The existing agriculture practices faced many challenges and fail to address some of the most critical needs of the growing population. Food insecurity, high initial cost of smart farming, severe farm labor shortage worldwide, economic, social, and political crises related to famines, poverty, climate change, and the technology focus of Agriculture 4.0 calls for rethinking the agriculture paradigm. Moreover, the idea of Society 5.0 promoted by Japanese government triggered many position reactions from policymakers, governments, private institutions, academicians, and researchers. The idea of human centered society where individuals live their lives to the fullest with shared vision of happiness, social harmony, sustainability, and resilience recently caught scholars’ attention. Several researchers investigated the society 5.0 and its critical components including Agriculture 5.0. Agriculture 5.0 not only could be leveraged to address many existing issues, but could become a major driving force for achieving Society 5.0’s goals. This paper follows a systematic literature review approach to investigate the major drivers, enabling cutting-edge technologies, various opportunities and challenges for developing, adopting, and implementation Agriculture 5.0. It also highlighted the overall and holistic architectural framework based on 12 layers of Agriculture 5.0 paradigm. Though Agriculture 5.0 is promising with many opportunities, such as creating new job opportunities for young generations, and boosting mass customization, it will face many potential challenges. Some challenges include cybersecurity and privacy issues, difficulties for an effective legal, regulatory and compliance system due to high automation and mass personalization, standardization issues, and adapting agricultural production strategies and models to constantly changing customer preferences.
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来源期刊
Information Processing in Agriculture
Information Processing in Agriculture Agricultural and Biological Sciences-Animal Science and Zoology
CiteScore
21.10
自引率
0.00%
发文量
80
期刊介绍: Information Processing in Agriculture (IPA) was established in 2013 and it encourages the development towards a science and technology of information processing in agriculture, through the following aims: • Promote the use of knowledge and methods from the information processing technologies in the agriculture; • Illustrate the experiences and publications of the institutes, universities and government, and also the profitable technologies on agriculture; • Provide opportunities and platform for exchanging knowledge, strategies and experiences among the researchers in information processing worldwide; • Promote and encourage interactions among agriculture Scientists, Meteorologists, Biologists (Pathologists/Entomologists) with IT Professionals and other stakeholders to develop and implement methods, techniques, tools, and issues related to information processing technology in agriculture; • Create and promote expert groups for development of agro-meteorological databases, crop and livestock modelling and applications for development of crop performance based decision support system. Topics of interest include, but are not limited to: • Smart Sensor and Wireless Sensor Network • Remote Sensing • Simulation, Optimization, Modeling and Automatic Control • Decision Support Systems, Intelligent Systems and Artificial Intelligence • Computer Vision and Image Processing • Inspection and Traceability for Food Quality • Precision Agriculture and Intelligent Instrument • The Internet of Things and Cloud Computing • Big Data and Data Mining
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