| CPC G06F 18/2321 (2023.01) [G06F 16/29 (2019.01); G06F 18/231 (2023.01)] | 9 Claims |

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1. A method (200) for detecting proximity between objects using threshold-based clustering, the method (200) comprising:
receiving (210) object data of a plurality of objects in a space to be monitored, from one or more data capturing devices (102) disposed in a space, wherein the one or more data capturing devices include 3D sensors such as radars, LiDARs, Laser Detection and Ranging (LaDAR), Light Emitting Diode Detection and Ranging (LeDDAR) mmWave Radar, C or K Band Radar, laser scanners and Time of Flight (ToF) sensors;
clustering (220) the object data using Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) clustering into one or more clusters, based on a predetermined spatial threshold distance, thereby reducing the search space, wherein the object data is represented as 2D, 3D, or N-dimensional point clouds;
processing (230) the one or more clusters by performing brute force computation on the reduced search space to identify the plurality of objects which lie within the predetermined threshold distance of each other, thereby identifying the plurality of objects that are at risk of collision; and
providing real-time results of identified objects at risk of collision.
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