"Data Feedback to Agriculture": Research on Humanized Iteration Mechanism of Smart Planting System-Taking Shanghai Zhilian Plant Factory Practice as an Example

The global agricultural digital transformation faces a pressing issue of "technological alienation," with 62% of smart farming systems remaining underutilized due to incompatibility. Using Shanghai Zhilian Plant Factory as a case study, this research identifies three human-centered challenges through case analysis, field surveys, and data processing: "demand mismatch, feedback deficiency, and value fragmentation." Grounded in agricultural big data governance theory and humanistic principles, the study establishes a "three-dimensional four-stage" iterative mechanism. Field validation demonstrates a 142.1% increase in operational satisfaction and a 21.4% boost in production efficiency. This research fills a theoretical gap in human-centered iteration of smart farming systems, providing replicable solutions for agricultural digital transformation. Additionally, the paper explores a promotion pathway combining policy incentives with market-oriented approaches, supporting the commercialization of these technologies.