<p>Petroleum hydrocarbon pollution is one of the important challenges facing the soil environment, and the traditional monitoring and remediation means generally have problems such as low efficiency and slow response. This paper systematically researches the monitoring technology of petroleum contaminated soil based on intelligent sensors and its application in microbial remediation process. By integrating electrochemical, optical, and biological sensors with IoT communication modules, a real-time soil pollution monitoring system with high spatial and temporal resolution and low power consumption is constructed, which is capable of accurately identifying the concentration of pollutants such as TPHs and PAHs, and dynamically predicting the trend of pollution diffusion by combining with machine learning algorithms. In terms of remediation, this paper thoroughly explored the mechanism of multiple petroleum degrading microorganisms and their response to key environmental factors such as temperature, initial petroleum hydrocarbon concentration and water content, etc. The experimental results showed that the degradation rate of petroleum hydrocarbons could reach up to 59.3% under the appropriate conditions (1%~3% petroleum hydrocarbon concentration, 25°C, and 20% water content). In addition, the stability and degradation activity of the bacteria in extreme environments were further enhanced by biofortification and immobilization. In this study, the integrated management strategy of “intelligent monitoring + microbial precision control” was proposed, which provides a theoretical basis and technical support for the intelligent and efficient remediation of petroleum-contaminated soil.</p>