The intelligent embedded system is a computing system combining artificial intelligence science and embedded technology, the system combines general-purpose processor and FPGA to achieve stronger processing capability, but it also brings system hardware and software design challenges. This paper proposes an intelligent embedded system task scheduling algorithm based on heterogeneous multi-core, which reasonably allocates hardware resources on the FPGA to optimize energy consumption under the premise of meeting system reliability requirements. The algorithm adopts a critical path-based energy consumption pre-allocation strategy, and the task scheduling makes the system schedule length shortest based on system reliability. Experiments show that the method of this paper outperforms other algorithms by an average of 5.34% in terms of energy consumption, and by an average of 6.83% in terms of scheduling length, which reflects the reasonableness and advancement of the method of this paper.