To solve the problem of personal location privacy leakage under the rapid development of the Internet of Things （IoT） technology, a location perturbation algorithm of Geo-indistinguishability based on the Region Of Interest (GROI) was proposed. Firstly, a random noise satisfying planar Laplacian distribution was added to the real location of the user. Secondly, the approximate location was obtained by the discretization operation. Thirdly, the query results were sanitized based on the given Region Of Interest (ROI), and the query errors were further reduced while the availability of the mechanism remained unchanged. Finally, experiments were carried out on Google map queries to compare the proposed algorithm with the geo-indistinguishable location privacy protection algorithm. The results show that the proposed algorithm has the average error of query results reduced at least 2% compared to geo-indistinguishable algorithm within a 6.0 km retrieval range, and the accuracy of query results better than that of geo-indistinguishable algorithm while the privacy level is not degraded. Especially for close-range retrieval, the proposed algorithm can reduce the query error.