With the rapid development of Location-Based Services (LBS), user trajectory data faces the risk of privacy leakage, and the existing methods have the problem that privacy protection and data availability are difficult to balance. In view of the above problems, a trajectory privacy protection scheme based on region of interest protection is proposed. The stay point detection algorithm is used to accurately divide the stay and transition areas of the moving trajectory. The innovations of the scheme are as follows: (1) Precision protection strategy: focusing on the protection of user stay area, replacing the traditional full trajectory protection strategy, effectively improving the efficiency and accuracy of privacy protection; (2) Decentralized architecture: using decentralized architecture design to avoid dependence on third-party service providers and eliminate the possibility of attackers using background knowledge to implement privacy inference; (3) Service quality optimization: The Voronoi diagram is used to constrain the false location generation range, reduce the service quality loss, and maintain good performance when the privacy budget is dynamically adjusted. The experimental results show that the scheme achieves a better balance between privacy protection intensity, trajectory similarity and edge computing resource utilization.