With the advancement of intelligent design, data models are playing an increasingly important role in optimizing intelligent product design processes. However, effectively integrating data models into the design process remains a significant challenge. To address this issue, this study adopts the KJ-AHP data model and explores its application in the design of intelligent wearable devices, using an intelligent firefighting helmet as a case study. This study utilized the KJ-AHP integrated method to analyze the design of an intelligent firefighting helmet. Initially, the demands for firefighting wearable devices were systematically screened to extract the core requirement indicators for the new helmet. Subsequently, an AHP hierarchical model was constructed to systematically analyze these requirements, ultimately refining the demand criteria for firefighting wearable devices. The study demonstrated that the KJ-AHP method, through qualitative and quantitative analysis, effectively identified and addressed the core issues in firefighting safety, comprehensively capturing the essential requirements for the intelligent firefighting helmet. This approach significantly enhanced design efficiency and product performance, providing new insights and methodological support for the development of intelligent products.