This paper proposes a computational framework for rural revitalization and new quality productivity development path driven by smart agriculture. The experimental data set was constructed from the aspects of Internet of things perception, remote sensing slices, agricultural machinery logs, circulation records and digital service information, covering 164 administrative villages, 4286 land units and multiple types of agricultural operation records. Firstly, a multi-source heterogeneous feature extraction module was designed to uniformly encode production intensity, facility activity, circulation smoothness and digital participation. Then, the graph correlation reasoning model was introduced to identify the development bottlenecks, and the path states of production, processing, distribution and service were described. Based on the intelligent decision-making algorithm, the development path under the constraints of resources, facilities and ecology is generated. Experimental results show that the accuracy of path generation is 91.5%, the macro-F1 value is 0.914, and the RMSE is 0.214. It maintains stable state expression and path ranking results in five types of regional samples, and the overall stability is also high. The framework provides a computable technical basis for rural development in smart agriculture scenarios, and has strong deployment interpretation ability.
