从餐盘到生产：现代消费者驱动型食品系统中的人工智能
From Plate to Production: Artificial Intelligence in Modern Consumer-Driven Food Systems
AI总结：
该研究综述了AI在现代消费者驱动型食品系统中的应用，提出AIFS框架融合多技术打造循环模式，指出挑战并倡导合理部署AI以推动食品系统可持续发展。
摘要：
全球食品系统面临着在需求不断攀升的背景下供应可持续、营养膳食的紧迫挑战。人工智能（AI）的出现正掀起一场个人选择革命，其中AI驱动的个体决策从餐桌到农场再回到我们的餐盘，重塑着食品系统。在此背景下，AI算法优化个人饮食选择，进而塑造农业产出，并推动从消费到种植的优化反馈循环。首先，我们深入研究了覆盖食品供应链的AI工具与技术，随后评估了机器学习、计算机视觉和语音识别等AI子领域如何在AI赋能食品系统（AIFS）框架中得到应用，该框架越来越多地利用物联网、多模态传感器和实时数据交换。我们重点介绍了AIFS框架，强调其将AI与数字化、大数据分析、生物技术和物联网等现代食品系统各组件中广泛使用的技术相融合。这种范式将传统的“从农场到餐桌”叙事转变为循环的“消费者驱动的从农场到餐桌”模式，以更好地实现可持续、营养的膳食。本文探讨了AI在食品领域的前景及其带来的内在挑战。通过推行严格的AI治理、统一的数据架构和跨学科合作，我们认为，当AI与以消费者为中心的战略相结合时，有潜力引导食品系统走上可持续发展轨道。我们对食品系统各方面的最新技术进行了全面综述，随后指出了差距，并倡导合理、有效地部署新兴AI方法。
英文摘要：
Global food systems confront the urgent challenge of supplying sustainable, nutritious diets in the face of escalating demands. The advent of Artificial Intelligence (AI) is bringing in a personal choice revolution, wherein AI-driven individual decisions transform food systems from dinner tables, to the farms, and back to our plates. In this context, AI algorithms refine personal dietary choices, subsequently shaping agricultural outputs, and promoting an optimized feedback loop from consumption to cultivation. Initially, we delve into AI tools and techniques spanning the food supply chain, and subsequently assess how AI subfields$\unicode{x2013}$encompassing machine learning, computer vision, and speech recognition$\unicode{x2013}$are harnessed within the AI-enabled Food System (AIFS) framework, which increasingly leverages Internet of Things, multimodal sensors and real-time data exchange. We spotlight the AIFS framework, emphasizing its fusion of AI with technologies such as digitalization, big data analytics, biotechnology, and IoT extensively used in modern food systems in every component. This paradigm shifts the conventional "farm to fork" narrative to a cyclical "consumer-driven farm to fork" model for better achieving sustainable, nutritious diets. This paper explores AI's promise and the intrinsic challenges it poses within the food domain. By championing stringent AI governance, uniform data architectures, and cross-disciplinary partnerships, we argue that AI, when synergized with consumer-centric strategies, holds the potential to steer food systems toward a sustainable trajectory. We furnish a comprehensive survey for the state-of-the-art in diverse facets of food systems, subsequently pinpointing gaps and advocating for the judicious and efficacious deployment of emergent AI methodologies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
