Apparatus and associated methods relate to identifying objects of interest and detecting motion to automatically detect a security threat as a function of video frame delta information received from a video encoder. In an illustrative example, the video encoder may be an H.264 encoder onboard a video camera. A cloud server may receive the video frame delta information in a compressed video stream from the camera. Threats may be detected by the cloud server processing the video frame delta information in the compressed video stream, without decompression, to identify objects and detect motion. The cloud server may employ artificial intelligence techniques to enhance threat detection by the cloud server. Various examples may advantageously provide increased capacity of a computer tasked with detecting security breaches, due to the significant reduction in the amount of data to be processed, relative to threat detection based on processing uncompressed video streams.

A vehicle control-system includes an automated driving controller and a vehicle-side communication section. The automated driving controller executes automated driving in which at least one out of speed control or steering control of a vehicle is performed automatically, and executes automated driving in a mode from out of plural modes with differing degrees of automated driving. The vehicle-side communication section communicates with a server for managing characteristic information of a vehicle occupant. The automated driving controller controls automated driving based on the characteristic information of the vehicle occupant received from a server-side communication section using the vehicle-side communication section.

A method for managing a parking lot is provided. The method includes: capturing, by a first video camera, an image of a vehicle; determining whether the image satisfies a condition; raising a first barrier when the image satisfies the condition; detecting whether there is only the one vehicle between the first barrier and a second barrier; and raising the second barrier to enable the vehicle to enter or leave the parking lot when detecting that there is only the one vehicle between the first barrier and the second barrier.

A device, system, and method for an electronic response to a potential carjacking is provided. A device receives: a location and vehicle ignition status of a vehicle; and sensor data generated by one or more sensors that are onboard the vehicle, the sensor data different from the location and the vehicle ignition status. The device determines whether the location of the vehicle is associated with a carjacking type of location, and whether a combination of the vehicle ignition status and the sensor data meet a carjacking threshold condition. When both the location of the vehicle is associated with the carjacking type of location and the carjacking threshold condition is met, the device: outputs an alert at the vehicle indicative of, or associated with, the potential carjacking; and/or causes, a notification to be transmitted to a communication device associated with a public safety agency or a monitoring service.

Disclosed systems and methods include receiving an image, processing the image with a depth estimation module to generate a first depth map, generating a foreground mask of the image, inpainting regions of the image, generating a second depth map based on the inpainted regions of the image, comparing histograms of the first and second depth maps, and generating proximity warnings based on the comparison of the histograms.

A boundary detection system for a vehicle includes a controller programmed to generate an alert in response to sensing a presence of a person in a first zone extending from the vehicle. The system also includes a wireless receiver configured to receive signals transmitted by a nomadic device in a second zone surrounding the vehicle. The controller is further programmed to, in response to the receiver receiving the signals, output the alert.

A method for managing a parking lot is provided. The method includes: capturing, by a first video camera, an image of a vehicle; determining whether the image satisfies a condition; raising a first barrier when the image satisfies the condition; detecting whether there is only the one vehicle between the first barrier and a second barrier; and raising the second barrier to enable the vehicle to enter or leave the parking lot when detecting that there is only the one vehicle between the first barrier and the second barrier.

At least one detector (2) for visible and/or IR radiation on board of a vehicle (100) is used to determine if an entity (200) is approaching the vehicle (100). If so, sensors (4) for vibration and/or acceleration are activated. Signals from these sensors (4) are used to determine if a contact between the entity (200) and the vehicle (100) has occurred. The contact may be classified based on these signals. The at least one detector (2) may include a camera (21). At least one camera (5, 21) on board of the vehicle may be used to record image data pertaining to a time-interval about the contact. A warning may be triggered if a contact between the entity (200) and the vehicle (100) is likely.

Systems and methods are disclosed for a police vehicle monitor. An example disclosed police vehicle includes first beacons positioned on a chassis of the police vehicle, second beacons position on a lightbar of the police vehicle, and a police assistance unit. The example police assistance unit is to track a distance of wearable nodes associated with a police officer. Additionally, the example police assistance unit is to, in response to the distance satisfying a first threshold, lock doors and roll up windows of the police vehicle.

Apparatus and associated methods relate to identifying objects of interest and detecting motion to automatically detect a security threat as a function of video frame delta information received from a video encoder. In an illustrative example, the video encoder may be an H.264 encoder onboard a video camera. A cloud server may receive the video frame delta information in a compressed video stream from the camera. Threats may be detected by the cloud server processing the video frame delta information in the compressed video stream, without decompression, to identify objects and detect motion. The cloud server may employ artificial intelligence techniques to enhance threat detection by the cloud server. Various examples may advantageously provide increased capacity of a computer tasked with detecting security breaches, due to the significant reduction in the amount of data to be processed, relative to threat detection based on processing uncompressed video streams.