Electrochemiluminescence (ECL) represents a unique optical-electrochemical transduction mechanism with high sensitivity, low background noise, and excellent controllability. However, conventional ECL systems rely on bulky, expensive laboratory instruments, severely limiting their application in point-of-care testing (POCT) and resource-limited scenarios. The integration of smartphones, with their high-performance processors, high-resolution cameras, programmable light sources, and wireless communication modules, has opened a new avenue for miniaturized, portable, and intelligent ECL sensing. This review systematically summarizes the fundamental principles of smartphone-based ECL detection, including ECL luminescence mechanisms, electrode configurations, and smartphone module integration. The latest advances in representative applications of smartphone ECL technology in bioanalysis, environmental monitoring, and food safety are comprehensively overviewed. Particular attention is paid to the auxiliary role of artificial intelligence, specifically the differentiated contributions of traditional machine learning algorithms for small-sample spectral feature analysis and deep learning architectures for high-dimensional imaging data processing, and machine learning in solving core challenges such as weak signal detection, background interference, and quantitative accuracy improvement. Finally, current limitations and future development directions toward fully integrated, self-powered, and intelligent ECL platforms are discussed, aiming to provide a systematic reference for the practical translation of this technology.
You et al. (Tue,) studied this question.