Abstract: A system is provided for monitoring and predicting traffic conditions in a vicinity of a system vehicle having a stop indicator system. The system may include one or more radar modules programmed to detect the presence of target vehicles traveling within a predetermined radar detection area near the system vehicle. The radar modules may be further programmed to detect signals associated with target vehicles and generate signals indicative of vehicle characteristics, such as vehicle velocity. The radar modules may be programmed to operate in connection with an alarm module to generate alert condition signals in response to assessing the target vehicles detected in the radar detection area. The system can then communicate appropriate alert event notifications in response to the generated alert condition signals.

Abstract: A vehicle analysis system provides an automatic license plate recognition module that receives image data from an ALPR camera detecting a license plate of a target vehicle. A context camera module of the system receives image data from a context camera capturing image data of the target vehicle. A geographical data module of the system can access map image data including a plurality of map definitions associated with a plurality of restricted zones. An artificial intelligence model and/or algorithm combines portions of each of the ALPR image data, the context camera image data, and the map image data, and uses the combined data for determining a location of the target vehicle in relation to at least one restricted zone.

Abstract: A facial recognition system includes a memory for storing a facial image database, wherein the facial image database includes a plurality of entries each corresponding to a different person, and wherein each entry includes a person identifier along with one or more facial images of the person. The facial recognition system further includes a facial recognition module that is operatively coupled to the memory. The facial recognition module is configured to receive a new facial image, and to select one or more facial recognition engines based on one or more facial image parameters of the new facial image, and to use the selected facial recognition engines to compare the new facial image with facial models that are based upon facial images stored in the facial image database in order to identify the person in the new facial image.

Abstract: A method of reducing false positives and identifying relevant true alerts in a video management system includes analyzing images to look for patterns indicating changes between subsequent images. When a pattern indicating changes between subsequent images is found, the video management system solicits from a user an indication of whether the pattern belongs to one of two or more predefined categories. The patterns indicating changes between subsequent images are saved for subsequent use. Subsequent images received from the video camera are analyzed to look for patterns indicating changes between subsequent images. When a pattern indicating changes between subsequent images is detected by the video management system, the video management system compares the pattern indicating changes between subsequent images to those previously categorized into one of the two or more predefined categories. Based on the comparison, the video management system may provide an alert to the user.

Abstract: An illumination control system is configured for operative association with a vehicle lighting system of an emergency vehicle, such as a fire truck or other first responder type of vehicle. The illumination control system includes a video analysis module configured for receiving data from one or more cameras positioned on an exterior of the vehicle, and each camera has an associated region of interest (ROI) defined for a field-of-view for the camera. An artificial intelligence (AI) module is provided to detect whether a person or object of interest has entered the ROI of the camera. The control system includes an algorithm processing module programmed for executing logic associated with one or more decision-making tasks in association with the operation of the AI module. Also, a light control module can be provided for communicating instructions for activating or deactivating various scene lights of the vehicle lighting system.

Abstract: A facial recognition system includes a memory for storing a facial image database, wherein the facial image database includes a plurality of entries each corresponding to a different person, and wherein each entry includes a person identifier along with one or more facial images of the person. The facial recognition system further includes a facial recognition module that is operatively coupled to the memory. The facial recognition module is configured to receive a new facial image, and to select one or more facial recognition engines based on one or more facial image parameters of the new facial image, and to use the selected facial recognition engines to compare the new facial image with facial models that are based upon facial images stored in the facial image database in order to identify the person in the new facial image.

Abstract: A method of reducing false positives and identifying relevant true alerts in a video management system includes analyzing images to look for patterns indicating changes between subsequent images. When a pattern indicating changes between subsequent images is found, the video management system solicits from a user an indication of whether the pattern belongs to one of two or more predefined categories. The patterns indicating changes between subsequent images are saved for subsequent use. Subsequent images received from the video camera are analyzed to look for patterns indicating changes between subsequent images. When a pattern indicating changes between subsequent images is detected by the video management system, the video management system compares the pattern indicating changes between subsequent images to those previously categorized into one of the two or more predefined categories. Based on the comparison, the video management system may provide an alert to the user.

Abstract: A system is provided for monitoring and predicting traffic conditions in a vicinity of a system vehicle having a stop indicator system. The system may include one or more radar modules programmed to detect the presence of target vehicles traveling within a predetermined radar detection area near the system vehicle. The radar modules may be further programmed to detect signals associated with target vehicles and generate signals indicative of vehicle characteristics, such as vehicle velocity. The radar modules may be programmed to operate in connection with an alarm module to generate alert condition signals in response to assessing the target vehicles detected in the radar detection area. The system can then communicate appropriate alert event notifications in response to the generated alert condition signals.

Abstract: A facial recognition system includes a memory for storing a facial image database, wherein the facial image database includes a plurality of entries each corresponding to a different person, and wherein each entry includes a person identifier along with one or more facial images of the person. The facial recognition system further includes a facial recognition module that is operatively coupled to the memory. The facial recognition module is configured to receive a new facial image, and to select one or more facial recognition engines based on one or more facial image parameters of the new facial image, and to use the selected facial recognition engines to compare the new facial image with facial models that are based upon facial images stored in the facial image database in order to identify the person in the new facial image.

Abstract: A method of reducing false positives and identifying relevant true alerts in a video management system includes analyzing images to look for patterns indicating changes between subsequent images. When a pattern indicating changes between subsequent images is found, the video management system solicits from a user an indication of whether the pattern belongs to one of two or more predefined categories. The patterns indicating changes between subsequent images are saved for subsequent use. Subsequent images received from the video camera are analyzed to look for patterns indicating changes between subsequent images. When a pattern indicating changes between subsequent images is detected by the video management system, the video management system compares the pattern indicating changes between subsequent images to those previously categorized into one of the two or more predefined categories. Based on the comparison, the video management system may provide an alert to the user.

Abstract: A system is provided for monitoring and predicting traffic conditions in a vicinity of a system vehicle having a stop indicator system. The system may include one or more radar modules programmed to detect target vehicles traveling within a predetermined radar detection area near the system vehicle. The radar modules may be further programmed to detect signals associated with target vehicles and generate signals indicative of alert conditions. The radar modules may be programmed to execute various algorithms which generate alert condition signals in response to determining and analyzing a current distance, a braking distance, and/or a velocity of the target vehicle detected in the radar detection area. The system can communicate appropriate alert notifications in response to the generated alert condition signals.

Abstract: A system is provided for monitoring and predicting traffic conditions in a vicinity of a system vehicle having a stop indicator system. The system may include one or more radar modules programmed to detect target vehicles traveling within a predetermined radar detection area near the system vehicle. The radar modules may be further programmed to detect signals associated with target vehicles and generate signals indicative of alert conditions. The radar modules may be programmed to execute various algorithms which generate alert condition signals in response to determining and analyzing a current distance, a braking distance, and/or a velocity of the target vehicle detected in the radar detection area. The system can communicate appropriate alert notifications in response to the generated alert condition signals.

Abstract: A facial recognition system includes a memory for storing a facial image database, wherein the facial image database includes a plurality of entries each corresponding to a different person, and wherein each entry includes a person identifier along with one or more facial images of the person. The facial recognition system further includes a facial recognition module that is operatively coupled to the memory. The facial recognition module is configured to receive a new facial image, and to select one or more facial recognition engines based on one or more facial image parameters of the new facial image, and to use the selected facial recognition engines to compare the new facial image with facial models that are based upon facial images stored in the facial image database in order to identify the person in the new facial image.

Abstract: The filtering tasks that are conventionally applied in a video monitoring application, to distinguish images that may be relevant to the application, are distributed to the image source, or near-source devices. Source devices, such as cameras and playback devices, and near-source devices, such as video concentrators and streaming devices, are configured to include video processing tools that can be used to pre-filter the image data to identify frames or segments of frames that include image information that is likely to be relevant to the receiving video monitoring application. In this manner, the receiving processor need not spend time and resources processing images that are pre-determined to be irrelevant to the receiving application.

Abstract: A data analysis system and approach having sensors, a collective processing mechanism connected to the sensors, and a threshold logic panel connected to the collective processing mechanism. Raw data from the sensors may be subject to collective processing and collective threshold logic analysis. The collective processing mechanism and the threshold logic panel may be situated outside of or in the cloud. Big data analytics may be performed on the data. The sensors may be homogeneous or heterogeneous. Consequently, there may be data fusion for false alarm reduction and advanced alarm detection, and application of big data analysis. Raw data may be used for determining positional information.

Abstract: The filtering tasks that are conventionally applied in a video monitoring application, to distinguish images that may be relevant to the application, are distributed to the image source, or near-source devices. Source devices, such as cameras and playback devices, and near-source devices, such as video concentrators and streaming devices, are configured to include video processing tools that can be used to pre-filter the image data to identify frames or segments of frames that include image information that is likely to be relevant to the receiving video monitoring application. In this manner, the receiving processor need not spend time and resources processing images that are pre-determined to be irrelevant to the receiving application.

Abstract: A system and method of detecting tampering at an automatic teller machine includes detecting start and end indicators of a transaction. A representation of a scene at the teller machine, prior to the start of the transaction can be compared to a representation of the scene after the end of the transaction. Variations therebetween can indicate tampering at the machine.

Abstract: The filtering tasks that are conventionally applied in a video monitoring application, to distinguish images that may be relevant to the application, are distributed to the image source, or near-source devices. Source devices, such as cameras and playback devices, and near-source devices, such as video concentrators and streaming devices, are configured to include video processing tools that can be used to pre-filter the image data to identify frames or segments of frames that include image information that is likely to be relevant to the receiving video monitoring application. In this manner, the receiving processor need not spend time and resources processing images that are pre-determined to be irrelevant to the receiving application.

Abstract: A home control system comprises a control apparatus for controlling devices in a home. A user interface is mountable to a wall in the home and is operatively connected to the control apparatus. The user interface comprises a display screen for displaying images relating to operation of the controlled devices. A memory stores an image of the wall proximate the user interface device. A control apparatus and the user interface selectively display the image of the wall on the display screen to camouflage the user interface.

Abstract: Blocking zones of a surveillance system are configured to prevent false alarms caused by motion within the zones, while allowing tracking of objects through the zones. An object that first appears within a blocking zone is not considered to be a reportable object until the object leaves the zone. All reportable objects are tracked, without regard to the blocking zones. Objects that remain within their initial blocking zone are not deemed to be reportable objects, and therefore do not generate alarms. If an object initially appears within overlapping zones, the object is not deemed to be reportable until it leaves each of the zones at least once. The blocking zones do not mask the video images, and thus a complete record of activity is available for forensic purposes.