Abstract: A method is provided for detecting proximity between objects using threshold based clustering. The method includes receiving object data of a plurality of objects in a space to be monitored, from one or more data capturing devices disposed in a space, clustering the object data into one or more clusters, based on a predetermined threshold distance, thereby reducing the search space, and processing the one or more clusters using brute force 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.

Abstract: A system and method for mapping location of one or more target data points to a D-dimensional environment are provided. The method includes mapping a sorted array of D-dimensional polygons to a D-dimensional cartesian coordinate system, determining a floor value and a ceiling value of each coordinate point of each target data point, calculating one or more shifted floor value and one or more shifted ceiling value of each coordinate point, combining the shifted floor value and the shifted ceiling value for determining one or more potential centroids, authenticating the potential centroids for determining one or more real centroids by determining the presence of the potential centroid in the array, calculating the distance of the target data point from the real centroids, and determining the polygon having the real centroid with the least distance from the target data point.