Abstract: Systems and methods include automatically identifying items from images of items positioned at a POS system. Cameras capture images of the items in which each camera captures images with different FOVs of the items thereby capturing different item parameters of each item. The items are identified when item parameters of the items match item parameters previously identified and the items are failed to be identified when item parameters fail to match item parameters previously identified. Image pixels associated with each unknown item are extracted and mapped to real world coordinates associated with each unknown item as positioned at the POS system. A bounding polygon for each unknown item is generated that encapsulates each unknown item based on the image pixels mapped to the real world coordinates. The bounding polygon is projected onto each unknown item thereby providing feedback for each unknown item positioned at the POS system.

Abstract: Systems and methods include extracting item parameters from images of items positioned at a POS system. UPC features included in the item parameters associated with each item when combined are indicative as to an indication of the UPC of each item. The UPC features are analyzed to determine whether the UPC features associated with each item when combined match a corresponding combination of UPC features stored in a database. The database stores different combinations of UPC features with each different combination of UPC features associated with a corresponding item thereby identifying each corresponding item based on each different combination of UPC features associated with each item. Each item positioned at the POS system is identified when the UPC features associated with each item when combined match a corresponding combination of UPC features as stored in the database.

Abstract: Systems and methods include extracting item parameters from images of items positioned at a POS system. Item parameters associated with each item when mapped into a feature vector for each item are indicative as to an identification of the item. The feature vectors are analyzed to determine whether item parameters when combined and mapped into the feature vectors match a corresponding feature vector stored in a database. The database stores different combinations of item parameters as mapped into different stored feature vectors with different stored feature vectors associated with different items thereby identifying each item based on each different combination of item parameters as mapped into each stored feature vector associated with each item. Each item positioned at the POS system is identified when the feature vectors associated with each item match a corresponding stored feature vector as stored in the database.

Abstract: Systems and methods include extracting item parameters from images of items positioned at a POS system. The item parameters associated with each item are indicative as to an identification of each item thereby enabling the identification of each item based on the item parameters. The item parameters are analyzed to determine whether the item parameters match item parameters stored in a database. The database stores different combinations of item parameters to thereby identify each item based on each different combination of item parameters associated with each item. Each item positioned at the POS system is identified when the item parameters for each item match item parameters as stored in the database and fail to identify each item when the item parameters fail to match item parameters. The item parameters associated with the items that fail to match are streamed to the database thereby enabling the identification of each failed item.

Abstract: Assisted checkout devices, including point-of-sale stations, can use computer vision and machine learning to speed the checkout process while maintaining human verification, assistance, and customer interaction provided by human clerks. A plurality of optical sensors, including cameras, can be arranged with different views of a checkout plane upon which items being purchased by a buyer are placed. Moreover, one or more support towers can be utilized to elevate the optical sensors to vertical heights at which the checkout plane, and items placed thereon, is within the field of view of the optical sensors. The information captured by the plurality of optical sensors can be analyzed using machine learning models to detect and identify the items placed on the checkout plane.

Abstract: Systems and methods include extracting item parameters from images of items positioned at a POS system. The item parameters associated with each item are indicative as to an identification of each item thereby enabling the identification of each item based on the item parameters. The item parameters are analyzed to determine whether the item parameters match item parameters stored in a database. The database stores different combinations of item parameters to thereby identify each item based on each different combination of item parameters associated with each item. Each item positioned at the POS system is identified when the item parameters for each item match item parameters as stored in the database and fail to identify each item when the item parameters fail to match item parameters. The item parameters associated with the items that fail to match are streamed to the database thereby enabling the identification of each failed item.

Abstract: Assisted checkout devices, including point-of-sale stations, can use computer vision and machine learning to speed the checkout process while maintaining human verification, assistance, and customer interaction provided by human clerks. A plurality of optical sensors, including cameras, can be arranged with different views of a checkout plane upon which items being purchased by a buyer are placed. Moreover, one or more support towers can be utilized to elevate the optical sensors to vertical heights at which the checkout plane, and items placed thereon, is within the field of view of the optical sensors. The information captured by the plurality of optical sensors can be analyzed using machine learning models to detect and identify the items placed on the checkout plane.

Abstract: Systems and methods include extracting item parameters from images of items positioned at a POS system. The item parameters associated with each item are indicative as to an identification of each item thereby enabling the identification of each item based on the item parameters. The item parameters are analyzed to determine whether the item parameters match item parameters stored in a database. The database stores different combinations of item parameters to thereby identify each item based on each different combination of item parameters associated with each item. Each item positioned at the POS system is identified when the item parameters for each item match item parameters as stored in the database and fail to identify each item when the item parameters fail to match item parameters. The item parameters associated with the items that fail to match are streamed to the database thereby enabling the identification of each failed item.

Abstract: Visual analytics systems can use video data from cameras placed throughout a location (e.g., a store or a hospital) to determine poses, gestures, tracks, journeys, and actions, and thereby to provide broader analytics useful in realizing efficiencies and improving human behaviors. Data from visual analytics systems can be used to generate alerts, make useful predictions, and run simulations to test hypotheses.

Abstract: A system includes: first tags configured to organize activities regarding respective physical objects, each of the first tags including at least a first processor, a first memory, a sensor, an input device, an output device, a wireless communication component, and a first activity component operated using the first processor and the first memory to adapt a behavior of the respective first tag; and a processing device configured to receive first wireless signals from at least some of the first tags, the processing device including a second processor, a second memory, and a second activity component operated using the second processor and the second memory to determine at least presence, proximity, and movement of the first tags based on the first wireless signals.

Abstract: A method includes: receiving, in a first tag, a first security certificate for a second tag and a session token corresponding to an arrangement involving the first and second tags; determining, by the first tag, that the second tag satisfies a proximity criterion with regard to the first tag; receiving, in the first tag and from the second tag, the first security certificate and the session token; and generating, by the first tag and in response to the determination and the receipt of the first security certificate and the session token, a first output corresponding to verification of a custodian of the second tag as a participant in the arrangement.

Abstract: A method includes: sending, by a first processing device, a first message including an instruction to a first tag to collect first data from at least one device, the first tag coupled to a first physical object for organizing the first physical object; receiving, by the first processing device, a second message from the first tag, the second message including the first data; obtaining, by the first processing device, a first descriptor as being associated with the first data; and presenting, by the first processing device, at least the first descriptor to a user as an indication to a location of the first physical object.

Abstract: A tag includes: a housing configured for coupling the tag to a physical object to organize activities regarding the physical object; and coupled to the housing: a wireless communication component; circuitry electrically coupled to the wireless communication component, the circuitry having a reset port and a switch port; a power source electrically coupled to the wireless communication component and the circuitry; a first switch between the power source and the reset port; a second switch between the reset port and ground, the second switch controlled by the switch port; and a capacitor between the reset port and the ground.

Abstract: A method includes: sending, by a first processing device, a first message including an instruction to a first tag to collect first data from at least one device, the first tag coupled to a first physical object for organizing the first physical object; receiving, by the first processing device, a second message from the first tag, the second message including the first data; obtaining, by the first processing device, a first descriptor as being associated with the first data; and presenting, by the first processing device, at least the first descriptor to a user as an indication to a location of the first physical object.

Abstract: A system includes: first tags configured to organize activities regarding respective physical objects, each of the first tags including at least a first processor, a first memory, a sensor, an input device, an output device, a wireless communication component, and a first activity component operated using the first processor and the first memory to adapt a behavior of the respective first tag; and a processing device configured to receive first wireless signals from at least some of the first tags, the processing device including a second processor, a second memory, and a second activity component operated using the second processor and the second memory to determine at least presence, proximity, and movement of the first tags based on the first wireless signals.

Abstract: A tag includes: a housing configured for coupling the tag to a physical object to organize activities regarding the physical object; and coupled to the housing: a wireless communication component; circuitry electrically coupled to the wireless communication component, the circuitry having a reset port and a switch port; a power source electrically coupled to the wireless communication component and the circuitry; a first switch between the power source and the reset port; a second switch between the reset port and ground, the second switch controlled by the switch port; and a capacitor between the reset port and the ground.

Abstract: A method includes: receiving, by a first tag and from a second tag, a first message including an identifier of the second tag, the first and second tags configured for coupling to respective first and second physical objects to organize activities; identifying, by the first tag and based on a proximity measure, the second tag for a pairing process to register the second tag as a child tag of the first tag; and providing, by the first tag, a second message with the identifier to a processing device configured to register the second tag as the child tag of the first tag.

Abstract: A sensing device includes a pair of contactless electrodes for placement on a coating on a surface of a structure or within or between one or more coatings on or over the surface of the structure. The electrodes function as sensors when activated to generate a current flow through the electrodes at multiple different frequencies. The sensing device also includes contactless control circuitry co-located with or separate from the electrodes that transmits impedance data generated from the activated electrodes. The impedance data is associated with corrosion condition information of the structure and/or the one or more coatings. A data collection system and display system useable with the sensing device are also described.

Abstract: A sensing device includes a pair of contactless electrodes for placement on a coating on a surface of a structure or within or between one or more coatings on or over the surface of the structure. The electrodes function as sensors when activated to generate a current flow through the electrodes at multiple different frequencies. The sensing device also includes contactless control circuitry co-located with or separate from the electrodes that transmits impedance data generated from the activated electrodes. The impedance data is associated with corrosion condition information of the structure and/or the one or more coatings. A data collection system and display system useable with the sensing device are also described.

Abstract: A composite slab assembly having an elongated metal deck provided with a number of longitudinally oriented upwardly directed integrally formed ribs and a concrete layer disposed on the metal deck with longitudinally oriented portions in complementary surface to surface engagement with the underlying metal deck. A transversely oriented integral reinforcing beam formed by a thickened portion of the concrete layer and having a lower extremity disposed below the level of the uppermost surfaces of the metal deck. The metal deck having at least one transversely directed discontinuity within which a portion of the transverse beam is received. Reinforcing rods may be provided in the integral reinforcing beam.The metal deck rib discontinuity may be partial and take the form of a number of longitudinally spaced notches generally aligned with similar notches in other ribs. The discontinuity may also be total with a complete transverse deck gap in the region of the beam.