Wind　conditions　are　crucial　in　agricultural　production,　and　wind　vectors　play　a　significant　role　in　agricultural　planting　plans.　However,　traditional　anemometers　rely　on　external　power　sources　such　as　lithium　batteries,　while　wind　energy　in　farmlands　is　usually　neglected.　This　paper　proposes　an　intelligent　wind　vector　monitoring　system　based　on　a　dual-module　triboelectric　nanogenerator　(DM-TENG),　which　consists　of　a　fan-blade　type　soft-contact　triboelectric　nanogenerator　(FBTSC-TENG)　and　a　disc-shaped　triboelectric　nanogenerator　(DS-TENG).　FBTSC-TENG　collects　wind　energy　in　the　environment　to　power　the　temperature　and　humidity　sensors,　while　determining　wind　speed　through　the　frequency　of　voltage　pulses.　DS-TENG　can　monitor　wind　direction,　identifying　8　wind　directions　through　output　pulse　signals　and　deep　learning　algorithms.　Therefore,　the　DM-TENG　proposed　in　this　study　is　expected　to　play　a　significant　role　in　the　field　of　smart　agriculture　in　the　future.