To optimize the energy consumption of unmanned aerial vehicle (UAV)-assisted information collection system in wireless sensor networks (WSN), we propose a joint optimization algorithm for UAV trajectory and sensor power allocation that considers inter-link interference. This approach comprehensively takes into account both UAV flight energy consumption and sensor node uplink data transmission energy consumption. Firstly, we construct a system energy minimization problem model based on practical constrains. Then, considering the non-convex nature of the multi-constraint optimization problem, we employ the block coordinate descent (BCD) method to decompose the problem of minimizing system energy consumption into two sub-problems: power allocation with a fixed UAV trajectory and UAV trajectory optimization with fixed power allocation. We apply convex approximation to transform the non-convex problem into a solvable approximate convex optimization problem by leveraging the mathematical characteristics of the sub-problems. We obtain an approximate sub-optimal solution to the original non-convex problem through alternating iterative optimization of the two sub-problems. Finally, the feasibility and effeetiveness of the proposed algorithm are verified through simulation experiments. The results show that the proposed algorithm can reduce system energy consumption by up to 22%, significantly outperforming the comparison algorithms. Furthermore, the advantages of the algorithm become more pronounced as the number of sensor nodes increases. This study provides a systematic approach for energy optimization in information collection in WSNs, effectively reducing system energy consumption by slightly increasing UAV flight energy consumption.