Different color space models that smartphones use to extract color information from the sample photos captured by cameras are summarized. The state-of-the-art methods adopted in data processing and quantitative analysis based on the color information are reviewed, followed by the perspective of challenges faced by smartphones in colorimetry and fluorimetry.

With the continuous improvement of hardware, particularly in camera and processor technology, smartphones have gradually become a convenient and efficient tool for analytical science. Compared to traditional spectrophotometers, smartphones provide an ideal solution for field inspections in resource-limited settings, offering advantages such as compact size, low cost, portability, and ease of use, all of which enable real-time detection without the need for laboratory equipment. However, several technical challenges persist, including low sensitivity, accuracy, variability in experimental conditions, and the selection of appropriate color models. This review examines how smartphone cameras extract color information from samples using several different color models and the utilization of this information to quantitative colorimetry and fluorimetry analysis. The theoretical foundations, characteristics, and application cases of these color models are discussed in detail. Additionally, the challenges and future directions in the field of smartphone-based colorimetry and fluorimetry methods are proposed.