Abstract: Coal spontaneous combustion (CSC) is one of the main disasters in the process of coal mining. The rapid and precise monitoring of the characteristic parameters of CSC and the timely warning of the danger degree are important guarantees for achieving safe and efficient production in coal mines. The principle and research and application status of CSC monitoring and early warning technology are summarized from two aspects: CSC precursor information monitoring technology and prediction methods. And the main problems of the existing CSC monitoring and early warning technology are analyzed as follows. ① The integrated monitoring of CSC precursor information is greatly affected by underground environment. ② The construction of early warning index system and model is based on experiments, and is a bit tricky to correlate the actual scene. ③ There are few effective samples of CSC, and the prediction timeliness lacks advancement. Based on the development trend of coal mine intelligence, the research prospects of intelligent monitoring and early warning technology for CSC are proposed. ① It is suggested to establish a joint prediction model of CSC early warning and real-time forecast. ② It is proposed to develop a multi-source information fusion analysis method based on mechanism modeling and machine learning. ③ It is recommended to build a one-stop, visual and intelligent CSC monitoring and early warning platform for mines. It is expected to be beneficial to improve the ability of monitoring and early warning for CSC and enhance the intelligent development level of coal mines.