The paper introduces a novel indexing technique, the Time-Parameterized R-tree (TPR-tree), which efficiently supports the querying of current and future positions of moving objects in one-, two-, and three-dimensional space. The TPR-tree extends the R*-tree by using time-parameterized bounding rectangles, which are functions of time and can adapt to the movement of objects. The technique is designed to handle dynamic data sets where objects may appear and disappear, and changes in anticipated positions occur. The paper discusses the problem statement, including the indexing of current and future positions, and the indexing of trajectories. It also presents the TPR-tree structure, algorithms for querying and updating the index, and performance experiments. The experiments demonstrate that the TPR-tree outperforms traditional R-trees, especially in scenarios with skewed data distributions and varying querying windows. The paper concludes by summarizing the contributions and suggesting future research directions.The paper introduces a novel indexing technique, the Time-Parameterized R-tree (TPR-tree), which efficiently supports the querying of current and future positions of moving objects in one-, two-, and three-dimensional space. The TPR-tree extends the R*-tree by using time-parameterized bounding rectangles, which are functions of time and can adapt to the movement of objects. The technique is designed to handle dynamic data sets where objects may appear and disappear, and changes in anticipated positions occur. The paper discusses the problem statement, including the indexing of current and future positions, and the indexing of trajectories. It also presents the TPR-tree structure, algorithms for querying and updating the index, and performance experiments. The experiments demonstrate that the TPR-tree outperforms traditional R-trees, especially in scenarios with skewed data distributions and varying querying windows. The paper concludes by summarizing the contributions and suggesting future research directions.