The idea of context-aware privacy preservation in location-based services employing several plausible trajectories is investigated in this research work. We study the efficiency of producing several possible trajectories as a strategy to improve user privacy while preserving data usefulness. The work contrasts conventional geo-indistinguishability methods with a modified, context-aware strategy including frequent locations, long stays, and unusual events. We show, by theoretical analysis and empirical evaluation, that the suggested context-aware technique provides better privacy protection and lower spatial error than more traditional approaches. Our results imply that one may better balance privacy protection with data utility by including contextual information into privacy-preserving systems. Contributions of this work include a fresh context-aware privacy preservation technique, an examination of the privacy–utility trade-off, and a comparison with conventional geo-indistinguishability techniques.