The Internet of Things, as an important part of important data aggregation, forwarding and control, often leads to objectivity errors due to the huge and complex received data. Based on this, this paper introduces GRU, LSTM, SRU deep learning to optimize the data received by the Internet of Things, and selects the most suitable communication mode optimization algorithm. The experimental results show that the accuracy errors of GRU, LSTM, and SRU algorithms show a downward trend, from 0.024 to 0.010%; the training time is reduced by 254 minutes, and the training speed is increased to 86%, indicating the excellent performance of SRU deep learning in IoT gateways.