Abstract: Aspects of the present disclosure include a method, an apparatus, and computer-readable medium for transmitting, via a RFID device, an allocation request for serial numbers to be associated with a product identifier, receiving a batch of serial numbers from a remote server, selecting a first serial number from the batch of serial numbers, wherein the first serial number is selected during a time period in which the RFID device lacks network connectivity with the remote server, transmitting the first serial number to a first RFID tag configured to be coupled with an article associated with the product identifier, and transmitting an update to the remote server indicating that the first serial number has been registered to the first RFID tag, in response to determining the RFID device is communicatively connected to the remote server.

Abstract: Systems and methods for self-checkout using an RFID tag. The methods include: detecting motion of the RFID tag using a motion sensor local to the RFID tag; enabling at least one communication operation of the RFID tag in response to the detection of the RFID tag's motion; performing operations by the RFID tag to communicate first information to an enterprise system; using the first information by the enterprise system to associate the RFID tag with an individual of a plurality of individuals present in a given facility; and dynamically changing displayed content of a display device to include information about an object to which the RFID tag is coupled, the display device being in proximity to the individual, in the possession of the individual or being worn by the individual.

Abstract: Aspects of the present disclosure include a method, an apparatus, and computer-readable medium for transmitting, via a RFID device, an allocation request for serial numbers to be associated with a product identifier, receiving a batch of serial numbers from a remote server, selecting a first serial number from the batch of serial numbers, wherein the first serial number is selected during a time period in which the RFID device lacks network connectivity with the remote server, transmitting the first serial number to a first RFID tag configured to be coupled with an article associated with the product identifier, and transmitting an update to the remote server indicating that the first serial number has been registered to the first RFID tag, in response to determining the RFID device is communicatively connected to the remote server.

Abstract: Aspects of the present disclosure provide streamline techniques to alert sales personal/associate of an item in need of replenishment on the sales floor or in the stock room, and provide real-time data indicating units of an item within a retail location. The present disclosure provides a method, system and computer readable medium for inventory management utilizing radio-frequency identification (RFID) technology. The method may include detecting a first signal from an electronic product code (EPC) tag at a first location; generating a value of an inventory count based on the first signal; detecting a second signal from the EPC tag at a second location; updating the value of the inventory count based on the second signal; comparing the updated value to a threshold value, and when the updated value meets the threshold; and sending a notification of a task to a mobile device.

Abstract: Systems and methods for machine learning inventory management. The methods comprise: capturing images by a plurality of image capture devices of different types (e.g., visual camera, 3D camera and/or thermal camera); reading item identification codes for items represented in the images; and using at least a first portion of the images and known physical appearances of a plurality of items by a machine learning algorithm to learn relationships between the items represented in the images and the item identification codes. At least a second portion of the images are used to learn various types of information that is useful for inventory management (e.g., changes in inventory amounts for display equipment, changes in equipment cleanliness, changes in inventory packaging, item misplacements, etc.).

Abstract: Systems and methods for self-checkout using an RFID tag. The methods comprise: detecting motion of the RFID tag using a motion sensor local to the RFID tag; enabling at least one communication operation of the RFID tag in response to the detection of the RFID tag's motion; performing operations by the RFID tag to communicate first information to an enterprise system; using the first information by the enterprise system to associate the RFID tag with an individual of a plurality of individuals present in a given facility; and dynamically changing displayed content of a display device to include information about an object to which the RFID tag is coupled, the display device being in proximity to the individual, in the possession of the individual or being worn by the individual.

Abstract: Systems and methods for machine learning inventory management. The methods comprise: capturing images by a plurality of image capture devices of different types (e.g., visual camera, 3D camera and/or thermal camera); reading item identification codes for items represented in the images; and using at least a first portion of the images and known physical appearances of a plurality of items by a machine learning algorithm to learn relationships between the items represented in the images and the item identification codes. At least a second portion of the images are used to learn various types of information that is useful for inventory management (e.g., changes in inventory amounts for display equipment, changes in equipment cleanliness, changes in inventory packaging, item misplacements, etc.).

Abstract: An apparatus for predicting a resultant attribute of a text file before it has been converted to an audio file by a text-to-speech converter application. In accordance with an embodiment, the apparatus includes: a receiver component for receiving a text file and a request to determine a resultant attribute of the text file before it is converted to an audio file, by a text-to-speech converter component; a calculation component for determining a file type associated with the received text file and the size of the received text file; a calculation component for identifying an attribute associated with the determined file type; and a calculation component for determining from the identified attribute and the size of the received text file a resultant attribute of the text file before it is converted to an audio file by the text-to-speech converter component.

Abstract: An apparatus for predicting a resultant attribute of a text file before it has been converted to an audio file by a text-to-speech converter application. In accordance with an embodiment, the apparatus includes: a receiver component for receiving a text file and a request to determine a resultant attribute of the text file before it is converted to an audio file, by a text-to-speech converter component; a calculation component for determining a file type associated with the received text file and the size of the received text file; a calculation component for identifying an attribute associated with the determined file type; and a calculation component for determining from the identified attribute and the size of the received text file a resultant attribute of the text file before it is converted to an audio file by the text-to-speech converter component.

Abstract: A recommendation apparatus for selecting, by comparing one or more media files from a plurality of received recommendations, one or more media files for inclusion into a digital media file. A recommendation apparatus in accordance with an embodiment includes: a main controller component for receiving a plurality of recommendations associated with one or more media files from a plurality of recommenders; a weighting component for determining a weighting factor associated with each of the received recommendations; a weighting component for identifying from each of the determined weighting factors each of the recommendations falling within a predetermined threshold and for selecting each of these recommendations for inclusion into an audio playlist.