From Plate to Production: Artificial Intelligence in Modern
Consumer-Driven Food Systems
- URL: http://arxiv.org/abs/2311.02400v1
- Date: Sat, 4 Nov 2023 13:13:44 GMT
- Title: From Plate to Production: Artificial Intelligence in Modern
Consumer-Driven Food Systems
- Authors: Weiqing Min, Pengfei Zhou, Leyi Xu, Tao Liu, Tianhao Li, Mingyu Huang,
Ying Jin, Yifan Yi, Min Wen, Shuqiang Jiang, Ramesh Jain
- Abstract summary: Global food systems confront supplying, nutritious diets in the face of escalating demands.
The advent of Artificial Intelligence is bringing in a personal choice revolution, wherein AI-driven individual decisions transform food systems.
This paper explores AI promise and challenges it poses within the food domain.
- Score: 32.55158589420258
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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.
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