In order to reduce the energy loss during data transmission and storage in the Internet of Things system and improve the transmission efficiency of fetal heart rate data to allow real-time monitoring of the fetus, we used a convolutional codec network (CC-Net) to compress the data. The network has two modules: the encoding and decoding modules. The original data are compressed in the encoding module and reconstructed in the decoding module. The internal parameters are continuously updated using the mean square error of the original and the reconstructed signals to minimize the error to obtain effectively compressed data in the encoding module. In this study, the compression ratio of fetal heart rate signals using this method reached 12.07% , and the error between the reconstructed and original signals was 0.03. The proposed CC-Net can achieve a very low compression ratio for fetal heart rate compression while ensuring a high similarity between the reconstructed and the original signals to retain important information in fetal heart rate signals.