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In order to solve the problem that the fog of the Yellow River Special Bridge cannot be predicted, the distribution state of the fog is difficult to estimate, and the impact range of the fog is difficult to measure the traffic control measures that affect the Yellow River Special Bridge, in view of the meteorological conditions of the Yellow River Special Bridge, a highway yellow river special bridge fog early warning system based on the echo state network (ESN) prediction algorithm is designed; the early warning system adopts a distributed structure, consisting of the main station and the sub-station, using the meteorological sensors, lightning and other equipment connected by the main station and the sub-station. The master station and the sub-station can obtain the measurement information related to the realization of fog prediction; the sub-station sends the obtained data information to the master station through the zigbee network, and the edge computing terminal in the master station uses the data obtained by the master station and the data transmitted by the sub-station to predict whether the fog will occur in combination with the ESN prediction algorithm, and uses the fog end road test terminal to send the early warning information to the cloud or the designated server; the fog early warning system is deployed in the Yellow River Special Bridge for experimental testing. The results show that the system can accurately warn whether there is fog on the Yellow River Special Bridge.