AgAID Institute—AI for agricultural labor and decision support

IF 2.5 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ai Magazine Pub Date : 2024-02-16 DOI:10.1002/aaai.12156
Alan Fern, Margaret Burnett, Joseph Davidson, Janardhan Rao Doppa, Paola Pesantez-Cabrera, Ananth Kalyanaraman
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引用次数: 0

Abstract

The AgAID Institute is a National AI Research Institute focused on developing AI solutions for specialty crop agriculture. Specialty crops include a variety of fruits and vegetables, nut trees, grapes, berries, and different types of horticultural crops. In the United States, the specialty crop industry accounts for a multibillion dollar industry with over 300 crops grown just along the U.S. west coast. Specialty crop agriculture presents several unique challenges: they are labor-intensive, are easily impacted by weather extremities, and are grown mostly on irrigated lands and hence are dependent on water. The AgAID Institute aims to develop AI solutions to address these challenges, particularly in the face of workforce shortages, water scarcity, and extreme weather events. Addressing this host of challenges requires advancing foundational AI research, including spatio-temporal system modeling, robot sensing and control, multiscale site-specific decision support, and designing effective human–AI workflows. This article provides examples of current AgAID efforts and points to open directions to be explored.

Abstract Image

AgAID 研究所--用于农业劳动和决策支持的人工智能
AgAID 研究所是一家国家人工智能研究所,致力于为特种作物农业开发人工智能解决方案。特种作物包括各种水果和蔬菜、坚果树、葡萄、浆果以及不同类型的园艺作物。在美国,特种作物产业是一个价值数十亿美元的产业,仅在美国西海岸就种植了 300 多种作物。特种作物农业面临着一些独特的挑战:它们是劳动密集型产业,容易受到极端天气的影响,而且大多在灌溉地种植,因此对水的依赖性很强。AgAID 研究所旨在开发人工智能解决方案来应对这些挑战,尤其是在劳动力短缺、水资源匮乏和极端天气事件面前。要应对这些挑战,就必须推进人工智能基础研究,包括时空系统建模、机器人传感与控制、多尺度现场决策支持,以及设计有效的人类-人工智能工作流程。本文提供了当前农业人工智能工作的实例,并指出了有待探索的开放方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Ai Magazine
Ai Magazine 工程技术-计算机:人工智能
CiteScore
3.90
自引率
11.10%
发文量
61
审稿时长
>12 weeks
期刊介绍: AI Magazine publishes original articles that are reasonably self-contained and aimed at a broad spectrum of the AI community. Technical content should be kept to a minimum. In general, the magazine does not publish articles that have been published elsewhere in whole or in part. The magazine welcomes the contribution of articles on the theory and practice of AI as well as general survey articles, tutorial articles on timely topics, conference or symposia or workshop reports, and timely columns on topics of interest to AI scientists.
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