Abstract: Examples described herein generally relate to a system for monitoring tags in a retail environment. The system includes an exit system including one or more sensors that read a tag to obtain exit system measurements associated with a tag detection event. The system includes a memory and a processor configured to execute instructions to receive a selection of a base configuration, the base configuration including weighting values for a plurality of exit system measurements. The processor may classify a tag detection event into a first tag status for the tag detection event based on application of the weighting values to exit system measurements associated with the tag detection event. The processor may determine a second tag status of the tag after the tag detection event. The processor may update the weighting values using a machine-learning algorithm based on at least the first tag status and the second tag status.

Abstract: Systems and methods for location identification and tracking of a person, object and/or vehicle. The methods involve: obtaining, by a computing system, a video of a surrounding environment which was captured by a portable camera coupled to the person, object or vehicle; comparing, by the computing system, first images of the video to pre-stored second images to identify geographic locations where the first images were captured by the portable camera; analyzing, by the computing system, the identified geographic locations to verify that the person, object or vehicle is (1) traveling along a correct path, (2) traveling towards a facility for which the person, object or vehicle has authorization to enter, or (3) traveling towards a zone or secured area internal or external to the facility for which the person, object or vehicle has authorization to enter; and transmitting a notification from the computing system indicating the results of the analyzing.

Abstract: Systems and methods for location identification and tracking of a person, object and/or vehicle. The methods involve: obtaining, by a computing system, a video of a surrounding environment which was captured by a portable camera coupled to the person, object or vehicle; comparing, by the computing system, first images of the video to pre-stored second images to identify geographic locations where the first images were captured by the portable camera; analyzing, by the computing system, the identified geographic locations to verify that the person, object or vehicle is (1) traveling along a correct path, (2) traveling towards a facility for which the person, object or vehicle has authorization to enter, or (3) traveling towards a zone or secured area internal or external to the facility for which the person, object or vehicle has authorization to enter; and transmitting a notification from the computing system indicating the results of the analyzing.

Abstract: Examples described herein generally relate to a system for monitoring tags in a retail environment. The system includes an exit system including one or more sensors that read a tag to obtain exit system measurements associated with a tag detection event. The system includes a memory and a processor configured to execute instructions to receive a selection of a base configuration, the base configuration including weighting values for a plurality of exit system measurements. The processor may classify a tag detection event into a first tag status for the tag detection event based on application of the weighting values to exit system measurements associated with the tag detection event. The processor may determine a second tag status of the tag after the tag detection event. The processor may update the weighting values using a machine-learning algorithm based on at least the first tag status and the second tag status.

Abstract: In one embodiment, a network control module permits any or all of power signals, traffic signals and controller command signals to be carried on as few as one wire or cable to a first port of the network control module. In another aspect, a “peripheral array” includes a network control module (in any one of a number of different possible embodiments), with one or more peripheral devices, such as antennas, attached to or coupled with the network control module outputs. In one embodiment, RFID “smart shelving” may be fabricated in sections, with several (for example, 4, 8 or 16) antennas in each section, and as few as one cable coupling adjacent sections. Additional embodiments are described and claimed.