Conceptual Design of an Ecosystem for Real Farm Data Collection toward Agricultural AI Foundation Models
Junsei Tanaka, Yoshihiro Sato
- 发表年份
- 2026
- 访问权限
- 开放获取
摘要
Data scarcity is a fundamental challenge in developing AI and foundation models for agricultural robots. Existing open-source data platforms do not provide sufficient incentives for data providers so long-term data collection remains difficult. Furthermore, advances in generative AI have introduced a new challenge of verifying that collected data genuinely originates from real farm environments. We propose an ecosystem for the sustainable collection and distribution of real farm data, integrating automatic pricing driven by demand and rarity, revenue sharing that distributes earnings to farmers as an incentive to keep providing data, and data authenticity guarantees through authenticated device uploads. To demonstrate the economic sustainability for all three parties among farmers, AI companies, and the platform, we estimate the economic value that agricultural robots stand to generate.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992