Successful development of a micro-total-analysis system (µTAS, lab-on-a-chip) is strictly related to the degree of miniaturization, integration, autonomy, sensitivity, selectivity, and repeatability of its detector. Fluorescence sensing is an optical detection method used for a large variety of biological and chemical assays, and its full integration within lab-on-a-chip devices remains a challenge. Important achievements were reported during the last few years, including improvements of previously reported methodologies, as well as new integration strategies. However, a universal paradigm remains elusive. This review considers achievements in the field of fluorescence sensing miniaturization, starting from off-chip approaches, representing miniaturized versions of their lab counter-parts, continuing gradually with strategies that aim to fully integrate fluorescence detection on-chip, and reporting the results around integration strategies based on optical-fiber-based designs, optical layer integrated designs, CMOS-based fluorescence sensing, and organic electronics. Further successful development in this field would enable the implementation of sensing networks in specific environments that, when coupled to Internet-of-Things (IoT) and artificial intelligence (AI), could provide real-time data collection and, therefore, revolutionize fields like health, environmental, and industrial sensing.

微量总量分析系统（µTAS，芯片实验室）的成功开发与检测器的小型化，集成度，自主性，灵敏度，选择性和可重复性密切相关。荧光传感是一种用于多种生物学和化学分析的光学检测方法，其在芯片实验室中的设备中的完全集成仍然是一个挑战。在过去几年中报告了重要的成就，其中包括对先前报告的方法的改进以及新的集成策略。但是，通用范例仍然难以捉摸。这篇评论考虑了荧光传感微型化领域的成就，这些研究从芯片外方法开始，代表了其实验室对应部件的微型化版本，继续逐步实现旨在将荧光检测完全集成到芯片上的策略，并报告基于基于光纤的设计，基于光学层的集成设计，基于CMOS的荧光传感和有机电子技术的集成策略的结果。在该领域的进一步成功开发将能够在特定环境中实现传感网络，当将其与物联网（IoT）和人工智能（AI）结合使用时，可以提供实时数据收集，从而革新了诸如健康，环境和工业传感。