Abstract: A work and resource data management system, for example for managing security officers in the field, uses a blockchain data structure providing a fully immutable and cryptographically secured system, instead of a traditional database structure. Separate chains of blocks can be used for different actors, parties or resources while linking data between the various blockchains to provide a connected data structure related to each work item. The improved system may allow for being temporarily disconnected, any part of the system may branch off to an asynchronous state while disconnected and resynchronize when connection to the network is re-established. As blocks can be added and not deleted, a full history of every action that happened in the system can be retained.

Abstract: In some embodiments, an apparatus includes a memory and a processor. The processor is configured to receive a set of images associated with a video recorded by a moving or a non-moving camera. The processor is configured to detect a structure of a region of interest from a set of regions of interest in an image from the set of images. The processor is configured to classify the structure into a geometric class from a set of predefined geometric classes using machine learning techniques. The processor is configured to alter the region of interest to generate an altered image when the geometric class is associated with an identity of a person, such that privacy associated with the identity of the person is protected. The processor is configured to send the altered image to a user interface or store the altered image in a standardized format.

Abstract: In some embodiments, an apparatus includes a memory and a processor. The processor is configured to receive a set of images associated with a video recorded by a moving or a non-moving camera. The processor is configured to detect a structure of a region of interest from a set of regions of interest in an image from the set of images. The processor is configured to classify the structure into a geometric class from a set of predefined geometric classes using machine learning techniques. The processor is configured to alter the region of interest to generate an altered image when the geometric class is associated with an identity of a person, such that privacy associated with the identity of the person is protected. The processor is configured to send the altered image to a user interface or store the altered image in a standardized format.

Abstract: In some embodiments, an apparatus includes a memory and a processor. The processor is configured to receive a set of images associated with a video recorded by a moving or a non-moving camera. The processor is configured to detect a structure of a region of interest from a set of regions of interest in an image from the set of images. The processor is configured to classify the structure into a geometric class from a set of predefined geometric classes using machine learning techniques. The processor is configured to alter the region of interest to generate an altered image when the geometric class is associated with an identity of a person, such that privacy associated with the identity of the person is protected. The processor is configured to send the altered image to a user interface or store the altered image in a standardized format.

Abstract: In some embodiments, an apparatus includes a memory and a processor. The processor is configured to receive a set of images associated with a video recorded by a moving or a non-moving camera. The processor is configured to detect a structure of a region of interest from a set of regions of interest in an image from the set of images. The processor is configured to classify the structure into a geometric class from a set of predefined geometric classes using machine learning techniques. The processor is configured to alter the region of interest to generate an altered image when the geometric class is associated with an identity of a person, such that privacy associated with the identity of the person is protected. The processor is configured to send the altered image to a user interface or store the altered image in a standardized format.

Abstract: In some embodiments, an apparatus includes a memory and a processor. The processor is configured to receive a set of images associated with a video recorded by a moving or a non-moving camera. The processor is configured to detect a structure of a region of interest from a set of regions of interest in an image from the set of images. The processor is configured to classify the structure into a geometric class from a set of predefined geometric classes using machine learning techniques. The processor is configured to alter the region of interest to generate an altered image when the geometric class is associated with an identity of a person, such that privacy associated with the identity of the person is protected. The processor is configured to send the altered image to a user interface or store the altered image in a standardized format.

Abstract: In a method for locating patterns of movement in a first digital video signal, wherein the first digital video signal comprising at least indirectly succeeding individual digital images is analyzed in real time, it is proposed for the locating of patterns of movement in a first digital video signal, during the occurrence of larger moving object volumes in real time, to assign at least a first location-changing foreground region in a first individual image in a predefined manner with a predefinable number of first markings, to subsequently determine the relative movement of the first markings between the first individual image and a subsequent second individual image, to subsequently associate each of the first markings with a predefinable first environment, to assign the first and/or at least one second location-changing foreground region in a predefined manner with a predefinable number of second markings, to remove the second markings disposed inside intersecting regions of a predefinable number of intersec

Abstract: In a method for locating patterns of movement in a first digital video signal, wherein the first digital video signal comprising at least indirectly succeeding individual digital images is analyzed in real time, it is proposed for the locating of patterns of movement in a first digital video signal, during the occurrence of larger moving object volumes in real time, to assign at least a first location-changing foreground region in a first individual image in a predefined manner with a predefinable number of first markings, to subsequently determine the relative movement of the first markings between the first individual image and a subsequent second individual image, to subsequently associate each of the first markings with a predefinable first environment, to assign the first and/or at least one second location-changing foreground region in a predefined manner with a predefinable number of second markings, to remove the second markings disposed inside intersecting regions of a predefinable number of intersec