用低代码平台DIZEST让AI自助机开发更简单高效
A Low-Code Methodology for Developing AI Kiosks: a Case Study with the DIZEST Platform
- 基于DIZEST低代码平台，实现AI功能直观搭建
- 相比Jupyter等平台，性能与集成度显著提升
- 适合快速开发智能自助终端，降低技术门槛
本文针对自助终端系统存在的集成困难、结构僵化、性能瓶颈及缺乏协作框架等问题，提出一种基于DIZEST的低代码方法论。该平台支持直观的工作流设计与AI功能无缝集成。通过与Jupyter Notebook、ComfyUI、Orange3等平台的对比分析，DIZEST在关键评估指标上表现更优。以照片自助机为例的案例研究进一步验证了该方法在提升系统互操作性、优化用户体验和增强部署灵活性方面的有效性。
原文摘要 · Abstract (English)
This paper presents a comprehensive study on enhancing kiosk systems through a low-code architecture, with a focus on AI-based implementations. Modern kiosk systems are confronted with significant challenges, including a lack of integration, structural rigidity, performance bottlenecks, and the absence of collaborative frameworks. To overcome these limitations, we propose a DIZEST-based approach methodology, a specialized low-code platform that enables intuitive workflow design and seamless AI integration. Through a comparative analysis with existing platforms, including Jupyter Notebook, ComfyUI, and Orange3, we demonstrate that DIZEST delivers superior performance across key evaluation criteria. Our photo kiosk case study further validates the effectiveness of this approach in improving interoperability, enhancing user experience, and increasing deployment flexibility.
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