As a mobile data collection platform， unmanned aerial vehicle （UAV） has significant application prospects in the field of wireless sensor network （WSN） due to its superior mobility. To solve the problem of high energy consumption in wireless sensor networks， this study proposes a UAV-vehicle collaborative data collection optimization method for the sensor location information sharing scenario to achieve the optimization goal of minimizing sensor energy consumption under non-fixed take-off and landing of UAVs. This method considers the scheduling problem of each sensor， specifically， by introducing a convex optimization algorithm based on block coordinate descent techniques to iteratively solve the mixed integer non-convex problem in the alternating optimization of trajectory and wake-up strategy. This approach ensures that the data collection needs are met while minimizing the energy consumption of the sensor nodes （SNs）. Simulation results demonstrate that this method can effectively reduce the energy consumption of wireless sensor networks in typical sensor distributions， showing its potential in more complex environments and its significant adaptability and scalability.