In mobile cognitive wireless sensor networks, the mobile characteristics of nodes will lead to continuous changes in network topology and uneven energy consumption of nodes. This study proposes an event-based clustering algorithm for mobile cognitive wireless sensor networks. The above problem is solved. The algorithm determines the qualified node and the standby node according to the pre-estimated dwell time in the communication area and adopts the direct clustering method to build the node by the moving direction, speed, and pre-estimated connection time of the node in the cluster. Clusters improve the stability of the cluster and ensure the minimum number of router hops. Compared with the simulation algorithms of mESAC, EACRP, and MNB, the algorithm has lower cluster energy consumption and better connectivity.