Wireless video transmission and video compression technology are the foundations and cores of many Internet of Things(IoT)applications and embedded systems in these days. However,multi-channel transmission always causes video frame loss and delay jitter because of the continuous change of wireless network state. Although the adaption algorithm can solve the video transmission problem under PC or server platform to a certain extent,the real-time performance and Quality of Service(QoS)requirement cannot be satisfied under the embedded platform and wireless network. Therefore, based on the DM368 chip,a complete platform was designed from video capture,compression,WiFi transmission,control unit reception to host computer display. At the same time,with the full consideration of the characteristics of embedded platform,a rate adaption algorithm that combines signal quality,network bandwidth,buffer status and congestion control was proposed. In this algorithm,the Gaussian function was used to calculate network bandwidth,the segmented inverse proportional function was used to adjust buffer status,the weighted moving method was adopted to smooth rate,and the extreme value suppression method was used for rate balancing. The smooth rate adjustment was realized by this algorithm, and the algorithm was applied to the proposed platform to realize the management of the control unit on multiple WiFi cameras,multi-channel transmission and load balancing. The QoS was used as the evaluation index for experimental verification. The results show that the algorithm performs well on the embedded platform with great improvements of smoothness and buffer stability,and has significantly fairness and bandwidth utilization improvements under multi-channel condition. In a variety of situations,such as single camera signal quality dynamic change or multi-camera bandwidth competition,compared with the McGinely Dynamic Indicator(MDI)algorithm,the proposed algorithm has the smoothness improved by 16% to 59%;compared with the Buffer-Based Algorithm(BBA),the proposed algorithm has the cache jitter reduced by 15% to 72%,and the delay jitter reduced by 12% to 76%.