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The study of fatigue driving monitoring and warning method can avoid traffic accidents caused by fatigue driving, and reduce the casualties and economic losses caused by fatigue driving. The current methods of monitoring and early warning for driving fatigue have the disadvantages of low sensitivity and poor reliability. It is impossible to alarm the drivers in time to avoid the occurrence of traffic accidents. To this end, put forward the fatigue driving multi-source intelligent monitoring and early warning methods, the driver collected camera images preprocessing, gray image information by calculating the driver value, distribution density in the image pixel driver, to provide information for the follow-up monitoring and early warning work. Secondly, tracking using Calman filtering algorithm on the driver image information, each time the driver in the state estimation, finally, to determine whether the driver fatigue state by estimating the driver state value. Experimental results show that the proposed method has low packet loss rate, high diversity, strong anti-interference ability and high computational efficiency.