Computer-implemented method for detecting moving bodies or pieces of cargo inside a cargo space, wherein the cargo space is measured three-dimensionally using at least one distance-measuring, depth-sensitive sensor, and the current distances of measuring points or measuring point sets of any bodies or pieces of cargo (6, 6.1) located in the cargo space are detected by the sensor as measured values in the form of 3D data, - wherein, in a first step, in a first measurement, the 3D data describing each measuring point of any bodies or pieces of cargo (6, 6.1) located in the cargo space are stored as a first data set (3D point cloud) in a computing and/or evaluation unit and optionally provided with a time stamp, - wherein, in a second step, at least one further, subsequent three-dimensional measurement is executed, and the 3D data describing the corresponding measuring points of the bodies or pieces of cargo (6, 6.1) located in the cargo space are stored in the computing and/or evaluation unit as further data sets and optionally also provided with a time stamp, - wherein, in a third step, 3D data of the individual, spatially corresponding measuring points of the first and the further measurement or measurements are compared with one another by means of an algorithm programmed in the computing and/or evaluation unit, and, in the event that changes in the 3D data of spatially corresponding measuring points of the first and the further data set are detected, the fourth step and the following further steps are executed, characterized in that - without prior execution of the third step, in a fourth step, the first and the further data set/the further data sets (3D point cloud/3D point clouds) are checked by means of an algorithm programmed in the computing and/or evaluation unit to ascertain whether subsets of the 3D data contained therein characterize a three-dimensional body or a piece of cargo (6.1) and, if applicable, are stored as a 3D data cluster characterizing a three-dimensional body or piece of cargo (volume), indexed and optionally also provided with a time stamp, - wherein, in a fifth step, the 3D data clusters of the first and further data sets, which data clusters characterize three-dimensional bodies or pieces of cargo determined from spatially corresponding measuring points or measuring point sets, are compared with one another by means of the algorithm in the computing and/or evaluation unit, wherein, in the event that, during the comparison of the 3D data clusters for spatially corresponding three-dimensional bodies or pieces of cargo of the first and further data sets/further data sets, changes in the 3D data clusters are determined that characterize spatial changes in the spatially corresponding three-dimensional bodies or pieces of cargo within a time interval, a signal which describes these changes and can be further processed is provided by the computing and/or evaluation unit. - wherein, in a first step, in a first measurement, the 3D data describing each measuring point of any bodies or pieces of cargo (6, 6.1) located in the cargo space are stored as a first data set (3D point cloud) in a computing and/or evaluation unit and optionally provided with a time stamp, - wherein, in a second step, at least one further, subsequent three-dimensional measurement is executed, and the 3D data describing the corresponding measuring points of the bodies or pieces of cargo (6, 6.1) located in the cargo space are stored in the computing and/or evaluation unit as further data sets and optionally also provided with a time stamp, - wherein, in a third step, 3D data of the individual, spatially corresponding measuring points of the first and the further measurement or measurements are compared with one another by means of an algorithm programmed in the computing and/or evaluation unit, and, in the event that changes in the 3D data of spatially corresponding measuring points of the first and the further data set are detected, the fourth step and the following further steps are executed, characterized in that - without prior execution of the third step, in a fourth step, the first and the further data set/the further data sets (3D point cloud/3D point clouds) are checked by means of an algorithm programmed in the computing and/or evaluation unit to ascertain whether subsets of the 3D data contained therein characterize a three-dimensional body or a piece of cargo (6.1) and, if applicable, are stored as a 3D data cluster characterizing a three-dimensional body or piece of cargo (volume), indexed and optionally also provided with a time stamp, - wherein, in a fifth step, the 3D data clusters of the first and further data sets, which data clusters characterize three-dimensional bodies or pieces of cargo determined from spatially corresponding measuring points or measuring point sets, are compared with one another by means of the algorithm in the computing and/or evaluation unit, wherein, in the event that, during the comparison of the 3D data clusters for spatially corresponding three-dimensional bodies or pieces of cargo of the first and further data sets/further data sets, changes in the 3D data clusters are determined that characterize spatial changes in the spatially corresponding three-dimensional bodies or pieces of cargo within a time interval, a signal which describes these changes and can be further processed is provided by the computing and/or evaluation unit.