Construction of a “School-Village-Enterprise” Collaborative Talent Cultivation Platform for Rural Areas Based on Digital Twin Technology

Talent revitalization is fundamental to sustainable rural development, yet current rural talent cultivation is constrained by fragmented educational resources, weak collaborative mechanisms, and insufficient alignment between training outcomes and practical industrial demands. As digital twin systems increasingly depend on electromagnetic information transmission, wireless sensing networks, and intelligent communication infrastructures for real-time data acquisition and virtual–physical interaction, establishing an integrated collaborative platform has become essential for precision-oriented talent development. This study proposes a “School-Village-Enterprise” collaborative talent cultivation platform driven by digital twin technology. By constructing a geospatial and socio-economic digital mirror of rural environments and integrating Internet of Things technologies, big data analytics, intelligent simulation, and multimodal data fusion, the platform enables coordinated interaction among the education chain, talent chain, industrial chain, and innovation chain. A four-layer architecture consisting of data perception, model construction, service application, and interaction interface is developed, together with a personalized learning path recommendation algorithm and dynamic digital twin updating mechanism. Practical validation demonstrates that the proposed platform improves the alignment between training content and actual rural demands from 32.7% to 73.5%, significantly enhancing collaborative cultivation efficiency while supporting adaptive decision-making in complex rural scenarios. By combining digital twin technology with electromagnetic-enabled communication infrastructures, the proposed framework provides an operational pathway for intelligent rural talent development and offers valuable references for distributed education systems and smart industrial training environments.