Design of a Multi-Method Integrated Intelligent UAV System for Vertical Greening Maintenance

Vertical greening (VG) delivers measurable urban ecosystem benefits, yet maintenance is constrained by at-height safety risks, heterogeneous facade geometries, and low labor efficiency. Although unmanned aerial vehicles show promise, most studies optimize isolated modules rather than providing a user-oriented, system-level pathway. This paper proposes a closed-loop, multi-method framework integrating the Decision-Making Trial and Evaluation Laboratory–-Analytic Network Process, the Functional Analysis System Technique, and the Theory of Inventive Problem Solving. DEMATEL-ANP models causal interdependencies among requirements and derives prioritized weights,; FAST decomposes functions and localizes conflicts, and TRIZ converts those conflicts into principle-guided structural concepts—establishing a traceable requirements → functions → conflicts → structure pipeline. We illustrate the approach at the prototype level with Rhino–KeyShot visualizations under near-facade constraints, showing how prioritized requirements propagate into candidate UAV architectures. The framework structures the identification and resolution of tightly coupled technical conflicts, supports adaptability in facade-proximal scenarios, and provides a transparent mapping from user needs to structure-level concepts. Claims are restricted to methodological feasibility; comprehensive quantitative field validation remains for future work. The framework offers a reproducible methodological reference for the systematic design and decision-making of intelligent UAV maintenance systems for VG.