让二维码直接运行机器学习模型，离线实现智能维护与操作指导。
Executable QR codes with Machine Learning for Industrial Applications
- 通过QRind语言在二维码中嵌入可执行的计算模块。
- 支持离线运行机器学习模型，用于设备预测性维护。
- 适合工业场景，尤其适用于无网络环境下的智能应用。
可执行二维码（eQR码或sQRy）是一种将程序以二进制形式编码于二维码中的特殊技术，可在无网络环境下由手机等移动设备直接执行。该技术应用场景广泛，涵盖智能用户指南与辅助系统。首个支持的编程语言为QRtree，用于实现决策树，例如引导用户操作或维护复杂机械。本文提出新语言QRind，专为工业领域设计，允许在二维码中集成多种计算模块，如机器学习模型以实现预测性维护，以及简化机械使用的算法。该技术使工业4.0/5.0部分功能可在无网络条件下部署，提升现场作业智能化水平。
原文摘要 · Abstract (English)
Executable QR codes, also known as eQR codes or just sQRy, are a special kind of QR codes that embed programs conceived to run on mobile devices like smartphones. Since the program is directly encoded in binary form within the QR code, it can be executed even when the reading device is not provided with Internet access. The applications of this technology are manifold, and range from smart user guides to advisory systems. The first programming language made available for eQR is QRtree, which enables the implementation of decision trees aimed, for example, at guiding the user in operating/maintaining a complex machinery or for reaching a specific location. In this work, an additional language is proposed, we term QRind, which was specifically devised for Industry. It permits to integrate distinct computational blocks into the QR code, e.g., machine learning models to enable predictive maintenance and algorithms to ease machinery usage. QRind permits the Industry 4.0/5.0 paradigms to be implemented, in part, also in those cases where Internet is unavailable.
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