Abstract: In some embodiments, apparatuses and methods are provided herein useful to inventory management. In some embodiments, an inventory management system comprises a mobile device comprising an image capture device configured to capture an image and a communications transceiver configured to transmit the image, and a control circuit configured to receive, from the mobile device, the image, detect, within the image, the first sign and the second sign, identify, based on the first sign, a product associated with the first sign, identify, based on the second sign, a location of the product storage unit, associate, in a database, an indication of the product associated with the first sign and the location of the product storage unit.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to inventory management. In some embodiments, an inventory management system comprises a mobile device comprising an image capture device configured to capture an image and a communications transceiver configured to transmit the image, and a control circuit configured to receive, from the mobile device, the image, detect, within the image, the first sign and the second sign, identify, based on the first sign, a product associated with the first sign, identify, based on the second sign, a location of the product storage unit, associate, in a database, an indication of the product associated with the first sign and the location of the product storage unit.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to processing captured images. In some embodiments, there is provided a system for processing captured images of objects at a product storage facility including a trained machine learning model; and a control circuit. The control circuit may group a plurality of product identifiers into one or more clusters based on at least one of visual similarity of corresponding images, textual similarity of corresponding associated descriptions, and associated relationships between product identifiers of the plurality of product identifiers; determine clusters having common elements that are at least within a similarity threshold of each other; merge the clusters with the common elements; and generate a mapping dataset used to retrain the trained machine learning model to identify a plurality of objects. The mapping dataset may include a plurality of associations of associated product identifiers to a single object.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to processing captured images. In some embodiments, there is provided a system for processing captured images of objects at a product storage facility including a trained machine learning model stored in a memory; and a control circuit. The control circuit may obtain an image at the product storage facility; cluster objects depicted in the image that have same product identifiers into a corresponding group; determine coordinates of each bounding box of each clustered object in the corresponding group; determine a bounding box representative depth value of pixels inside the bounding box of each clustered object; determine an overall representative depth value of the corresponding group based on bounding box representative depth values of clustered objects; and exclude the clustered objects from identified objects in the image upon a determination that the overall representative depth value is greater than a threshold.

Abstract: Systems and methods of detecting support members of product storage structures that store products at a product storage facility include an image capture device that captures images of a product storage structure including vertical and horizontal support members. A computing device including a control circuit is configured to: obtain the images of the product storage structure captured by the image capture device, stitch the obtained images together to generate a stitched image that depicts the product storage structure, generate a color distribution map of the stitched image of the product storage structure to detect individual ones of the horizontal and vertical support members of the product storage structure.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to processing captured images of objects at a product storage facility. In some embodiments, there is provided a system for processing captured images of objects including a trained machine learning model and a control circuit. In some embodiments, the trained machine learning model is configured to process unprocessed captured images. In some embodiments, the control circuit is configured to associate each of the processed images into one of a first group, a second group, or a third group; remove at least one processed image associated with the first group from the processed images in accordance with a first processing rule; and output remaining processed images associated with the first group and processed images associated with the second group to be used to retrain the trained machine learning model.

Abstract: Systems and methods of creating reference template images for detecting and recognizing products at a product storage facility include an image capture device having a field of view that includes a product storage structure of the product storage facility, and a computing device including a control circuit and being communicatively coupled to the image capture device. The computing device obtains images of the product storage structure captured by the image capture device, analyzes the obtained images to detect individual ones of the products located on the product storage structure. Then, the computing device identifies the individual ones of the products detected in the images and crops each of the individual ones of the identified products from the images to generate cropped images. The computing device then creates a cluster of the cropped images, and selects one of the cropped images as a reference template image of an identified individual product.

Abstract: Systems and methods of detecting and recognizing products on product storage structures of a product storage facility include an image capture device that moves about and captures images of the product storage structures at the product storage facility. A computing device processes the obtained images to detect and identify the products on the product storage structure, crops each of the identified individual products from the image to generate a plurality of cropped images and generates an image histogram template, feature vector template and location information template for each of the cropped images. The cropped images are stored in an electronic database and represent a reference model for each of the identified individual products and are stored in association with the generated image histogram template, feature vector template and location information template to facilitate recognition of products subsequently captured on the product storage structure by the image capture device.

Abstract: Systems and methods of analyzing on-shelf price tag labels and products at a product storage facility include an image capture device that captures one or more images of one or more product storage structures at a product storage facility. A computing device communicatively coupled to the image capture device analyzes the images of the product storage structures captured by the image capture device and detects individual price tag labels and individual products located on the product storage structure. Based on the detection of the price tag labels and the products, the computing device also defines separate product storage spaces of the product storage structure, determines which price tag labels are allocated to which of the separate product storage spaces, and associates in a database the price tag labels allocated to the product storage spaces with the products stored in those product storage spaces.

Abstract: Systems and methods of verifying pairings of price tag labels and products at a product storage facility include an image capture device that moves about and captures images of product storage structures at the product storage facility, and a database that stores inventory data associated with the products stocked at the product storage facility. A computing device processes the images to extract one or more characters from the price tag labels and products detected in the images, correlates the extracted characters to the inventory data to identify a product code and a product name that matches the characters extracted from the price tag labels and the products. If the characters extracted from the price tag and from the on-shelf product to which the price tag label is allocated match, the database is updated to reflect that the price tag label is properly allocated to the appropriate on-shelf product.

Abstract: Systems and methods of analyzing on-shelf price tag labels and products at a product storage facility include an image capture device that captures one or more images of one or more product storage structures at a product storage facility. A computing device communicatively coupled to the image capture device analyzes the images of the product storage structures captured by the image capture device and detects individual price tag labels and individual products located on the product storage structure. Based on the detection of the price tag labels and the products, the computing device also defines separate product storage spaces of the product storage structure, determines which price tag labels are allocated to which of the separate product storage spaces, and associates in a database the price tag labels allocated to the product storage spaces with the products stored in those product storage spaces.

Abstract: Systems and methods for use in mapping an interior space of a product storage facility include at least one sensor that captures distance measurement data with respect to an interior space of the product storage facility. A computing device obtains a first image representing a 2-dimensional map of the interior space of the product storage facility and processes this image to define a boundary of the interior space of the product storage facility and detect individual structures located within the interior space of the product storage facility. Then, the computing device defines separate department areas, assigns a department label to each of the separate department areas, and converts the 2-dimensional map representing the detected structures and the defined separate department areas and the department labels assigned to the separate department areas into a second image representing a 3-dimensional map of the interior space of the product storage facility.

Abstract: Some embodiments provide systems comprising: a machine learning model database; a deblur system configured to receive at least a portion of an image comprising a presumed location label captured by the image capture device, and apply at least a deblurring machine learning framework to generate a deblurred label image comprising the presumed location label; a rectification system configured to apply an machine learning transform algorithm to the deblurred label image to generate a rectified label image; an optical character recognition (OCR) system configured to apply a recognition machine learning model to the rectified label image to estimate text; and a location estimation system configured to estimate a location of the presumed location label as a function of the estimated text of the presumed location label relative to known text on known location labels position at respective different known locations within the product storage facility.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to screening a body temperature of a human. In some embodiments, there is provided a temperature screening system that screens a body temperature of a human including a housing comprising an output interface; one or more first sensors; a temperature sensor; and a control circuit configured to: cause the output interface to provide one or more messages; receive the one or more user inputs indicative of responses to at least one of the one or more messages; receive temperature data corresponding to the body temperature; determine whether the human meets a health criteria; and transmit a control signal indicative of the human meeting the health criteria in response to the human meeting the health criteria.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to screening a body temperature of a human. In some embodiments, there is provided a touchless temperature screening system that screens a body temperature of a human including a housing comprising an output interface; one or more first sensors; a temperature sensor; and a control circuit configured to: cause the output interface to provide one or more messages; receive the one or more user inputs indicative of responses to at least one of the one or more messages; receive temperature data corresponding to the body temperature; determine whether the human meets a health criteria; and transmit a control signal indicative of the human meeting the health criteria in response to the human meeting the health criteria.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to a price display system for a product. In some embodiments, a price display system for a product comprises a product display unit, a price sign comprising a substrate upon which markings are applied, wherein the markings include a price for a product and a visual identifier to identify the product, the visual identifier comprising a plurality of markers including a pair of markers, the pair of markers indicate boundaries of the visual identifier, data markers, wherein each of the data markers represents one of two states, wherein the data markers collectively represent an identification number corresponding to the product for sale in the retail environment, and timing markers, wherein each of the timing markers represent one of two states, wherein the timing markers collectively represent a timing value.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to inventory management. In some embodiments, an inventory management system comprises a mobile device comprising an image capture device configured to capture an image and a communications transceiver configured to transmit the image, and a control circuit configured to receive, from the mobile device, the image, detect, within the image, the first sign and the second sign, identify, based on the first sign, a product associated with the first sign, identify, based on the second sign, a location of the product storage unit, associate, in a database, an indication of the product associated with the first sign and the location of the product storage unit.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to screening a body temperature of a human. In some embodiments, there is provided a touchless temperature screening system that screens a body temperature of a human including a housing comprising an output interface; one or more first sensors; a temperature sensor; and a control circuit configured to: cause the output interface to provide one or more messages; receive the one or more user inputs indicative of responses to at least one of the one or more messages; receive temperature data corresponding to the body temperature; determine whether the human meets a health criteria; and transmit a control signal indicative of the human meeting the health criteria in response to the human meeting the health criteria.