Abstract:
A method, system and computer program product for intelligent tracking and transformation between interconnected sensor devices of mixed type is disclosed. Metadata derived from image data from a camera is compared to different metadata derived from radar data from a radar device to determine whether an object in a Field of View (FOV) of one of the camera and the radar device is an identified object that was previously in the FOV of the other of the camera and the radar device.
Abstract:
A method and apparatus for detecting that a stun gun has been deployed is provided herein. During operation a periodic nature of a stun-gun voltage will be utilized to determine if the stun-gun has been fired. More specifically, an electric/magnetic field (EMF) and/or a sound will be analyzed to determine if the periodic nature of the EMF and/or sound matches that of a stun gun. If so, a command center will be notified of the event. In order to increase the accuracy of any stun-gun detect, a gun-draw sensor may be used in combination with the above technique.
Abstract:
In embodiments a host reserves capacity of a wireless adapter for critical data transmission. Critical data is injected into a transport interface of the host, which passes the critical data to the wireless adapter for wireless transmission to a destination device.
Abstract:
A communication system (100) provides a wearable firearm detection system comprising a first body area network (BAN) node (120) coupled to the firearm, a second BAN node (122) coupled to a body wearable apparatus, such as a holster, and a third BAN node (124) coupled to a portable radio (150). The first BAN node detects the presence or absence of the firearm in and out of the holster and communicates the presence or absence of the firearm to the third BAN node coupled to the radio. In response to the firearm being withdrawn from the holster, the radio can enable one or more actions such as an alert to the user, an alert to a dispatch center (170), or enabling a recording (140) of firearm movement.
Abstract:
Authentication methods are used to authenticate, a device1 having an ESN1 (electronic serial number), a device2 having an ESN2, and/or a user of the devices. In one implementation, device1 receives the ESN2 in a near-field signal; derives an authentication result as a function of the ESN1 and ESN2; and sends the authentication result to an authenticator device to use in completing authentication. Authentication is confirmed when the device1 authentication result matches an authentication result independently generated by the authenticator device, which is provisioned with the ESN1 and ESN2. In a second implementation, device1 generates a RAND1 (random number) and sends the RAND1 to device2 over a near-filed link. An authenticator device confirms authentication upon receiving the same RAND1 from both device1 and device2.
Abstract:
Systems for personalized intent prediction may perform a process including receiving image data depicting the behavior of a person on approach toward a secure location, generating intent data including data representing a current trajectory of the person on the current approach, comparing the intent data with a personal statistical model for the person that includes data representing trajectories associated with historical approaches by the person toward the secure location and respective result data indicating whether the historical approach resulted in the person entering the secure location, determining, dependent on the comparing, a personalized intent score representing a likelihood that the person intends to enter the secure location on the current approach, and pre-emptively enabling, or refraining from pre-emptively enabling, entry to the secure location prior to the person reaching the secure location based on whether the personalized intent score meets or exceeds a predetermined minimum confidence threshold for enabling entry.
Abstract:
Systems and methods for intelligent traffic stop classifier loading are provided. A processor may receive a plurality of inputs related to a current context of a law enforcement officer. Based on the plurality of inputs, it may be determined that the current context of the law enforcement officer is a vehicle traffic stop. An image classifier may be loaded onto an image capture device associated with the law enforcement officer based on the vehicle traffic stop determination. An object type associated with the image classifier may be scanned for using the image classifier loaded onto the image capture device.
Abstract:
A method, apparatus, and system are provided for authentication of collaborative mobile devices. A first mobile device receives a challenge message, derives a first mobile device authentication result based on the challenge message, and conveys, to a second mobile device of a user of the first mobile device, a first short-range wireless signal comprising the challenge message. The second mobile device receives the challenge message from the first mobile device, derives a second mobile device authentication result based on the challenge message, and conveys, to the first mobile device, a first short-range wireless signal comprising the second mobile device authentication result. The first mobile device receives the second mobile device authentication result and authenticates one or more of the first mobile device, the second mobile device, and the user by conveying, to an authenticator device, the first mobile device authentication result and the second mobile device authentication result.