Abstract: A modular biometric retrofit device and universal mounting assembly are disclosed herein. The device integrates RGB and near-infrared imaging, anti-spoofing optics, an internal rechargeable battery, and a USB-C power and data interface within a compact housing that can be attached to existing point-of-sale terminals, kiosks, handheld payment units, drive-thru menu boards, order-confirmation screens, speaker boxes, and humanoid robots for adding biometric identification capabilities thereto. The universal mounting assembly includes a variety of interchangeable mechanical and electrical adapters—clamp, suction, recessed, magnetic, adhesive, and vendor-specific brackets—enabling attachment without modification of host hardware. The retrofit device provides multi-spectral liveness detection, extended-range operation, and secure data communication for payment authorization, creating a standardized platform for biometric identification across retail and service environments.

Abstract: A vendor agnostic biometric kernel provides preprocessing, canonical template generation, multi signal liveness aggregation, interoperability adapters, a secure template vault, and a policy engine that selects among matcher pipelines responsive to context. The kernel records user consent and emits signed audit logs. Portions of the kernel execute on an edge device while other portions execute in cloud services. The system outputs authentication assertions suitable for merchant payment authorization.

Abstract: A flexible robotic kitchen assistant automates the preparation of food items. The robotic kitchen assistant includes a robotic arm, a sensor assembly comprising a plurality of cameras aimed at a kitchen workspace for preparing the food items, a controller operable to move the robotic arm, and a processor. The processor is operable to command the robotic arm to perform a food preparation step on the food items in the kitchen workspace based on order information, recipe information, kitchen equipment information, and camera data. The system is capable of performing a wide range of tasks commonly used in residential and commercial kitchens and is able to work collaboratively with and in close proximity to human kitchen workers.

Abstract: A flexible robotic kitchen assistant automates the preparation of food items. The robotic kitchen assistant includes a robotic arm, a sensor assembly comprising a plurality of cameras aimed at a kitchen workspace for preparing the food items, a controller operable to move the robotic arm, and a processor. The processor is operable to command the robotic arm to perform a food preparation step on the food items in the kitchen workspace based on order information, recipe information, kitchen equipment information, and camera data. The system is capable of performing a wide range of tasks commonly used in residential and commercial kitchens and is able to work collaboratively with and in close proximity to human kitchen workers.

Abstract: The present invention relates to a method and apparatus for biometric identification for use in connection with a payment or transaction based system, a stand alone and retrofit module for carrying out the same.

Abstract: A flexible robotic kitchen assistant automates the preparation of food items. The robotic kitchen assistant includes a robotic arm, a sensor assembly comprising a plurality of cameras aimed at a kitchen workspace for preparing the food items, a controller operable to move the robotic arm, and a processor. The processor is operable to command the robotic arm to perform a food preparation step on the food items in the kitchen workspace based on order information, recipe information, kitchen equipment information, and camera data. The system is capable of performing a wide range of tasks commonly used in residential and commercial kitchens and is able to work collaboratively with and in close proximity to human kitchen workers.

Abstract: An automated kitchen assistant system inspects a food preparation area in the kitchen environment using a novel sensor combination. The combination of sensors includes an Infrared (IR) camera that generates IR image data and at least one secondary sensor that generates secondary image data. The IR image data and secondary image data are processed to obtain combined image data. A trained convolutional neural network is employed to automatically compute an output based on the combined image data. The output includes information about the identity and the location of the food item. The output may further be utilized to command a robotic arm, kitchen worker, or otherwise assist in food preparation. Related methods are also described.

Abstract: A system for face-based payment includes two screens coupled together. One screen is configured to display a payment interface to a cashier. The other screen is configured to display a payment interface to a customer and to receive camera data indicative of the customer. One or more processors are configured to perform a facial recognition operation in response to receiving the camera data indicative of the customer and to perform a payment transaction in response to performing the facial recognition operation. The screens may be coupled to a transparent barrier positioned between the screens and that extends beyond the boundaries of the screens. Other embodiments are described and claimed.

Abstract: A robotic sled-enhanced food preparation system includes a robotic kitchen assistant operable to determine and to perform food preparation steps, and an autonomous mobile sled operable to supply the robotic kitchen assistant with ingredients and supplies. The robotic kitchen assistant includes a scheduling engine to evaluate food inventory levels and automatically determine when to replenish the food inventories using the sled if the food inventory levels are insufficient to complete the food preparation steps. Related methods are also described.

Abstract: In some embodiments, a method for confirming that a biological sample provided by an individual and sent to a testing facility was obtained from the individual includes obtaining a sample collection unit containing the biological sample and a video of the individual providing the biological sample. The individual provides the biological sample by recording a video of himself or herself: opening the sample collection unit; depositing the biological sample into the sample collection unit; and closing the sample collection unit. The method further includes analyzing the biological sample for one or more of at least one pathogen and at least one antibody to a pathogen; analyzing the video to ensure that the individual in the video provided the sample; and performing facial recognition on the video to correlate the sample collection unit and the biological sample to the individual.

Abstract: An automated kitchen assistant system inspects a food preparation area in the kitchen environment using a novel sensor combination. The combination of sensors includes an Infrared (IR) camera that generates IR image data and at least one secondary sensor that generates secondary image data. The IR image data and secondary image data are processed to obtain combined image data. A trained convolutional neural network is employed to automatically compute an output based on the combined image data. The output includes information about the identity and the location of the food item. The output may further be utilized to command a robotic arm, kitchen worker, or otherwise assist in food preparation. Related methods are also described.

Abstract: An automated kitchen assistant system inspects a food preparation area in the kitchen environment using a novel sensor combination. The combination of sensors includes an Infrared (IR) camera that generates IR image data and at least one secondary sensor that generates secondary image data. The IR image data and secondary image data are processed to obtain combined image data. A trained convolutional neural network is employed to automatically compute an output based on the combined image data. The output includes information about the identity and the location of the food item. The output may further be utilized to command a robotic arm, kitchen worker, or otherwise assist in food preparation. Related methods are also described.

Abstract: A food preparation system is configured to enhance the efficiency of food preparation operations in a commercial kitchen by displaying instructions on a surface in the kitchen work area. The food preparation system includes a plurality of cameras aimed at a kitchen workspace for preparing the plurality of food items and a processor operable to compute an instruction for a kitchen worker to perform a food preparation step based on one or more types of information selected from order information, recipe information, kitchen equipment information, data from the cameras, and food item inventory information. A projector in communication with the processor visually projects the instruction onto a location in the kitchen workspace for the kitchen worker to observe. Related methods for projecting food preparation instructions are described.

Abstract: In some embodiments, a system for regulating a digital door lock based on facial recognition includes a graphical user interface, an optical camera, communication circuitry, and processing circuitry configured to receive a signal corresponding to an image of the face of an individual captured by the optical camera. The processing circuitry may determine an identity of the individual based on the image of the face and determine whether or not to instruct the digital door lock to unlock or cause the interface to display instructions for the individual to access reserved goods or services based on the identity the individual. In any embodiments, a system may include a temperature sensor or other physiological parameter sensor to enable the processing circuitry to determine whether to unlock a door or provide access to goods or services based on the individual's health status, which may include a body temperature and/or other parameter.

Abstract: A flexible robotic kitchen assistant automates the preparation of food items. The robotic kitchen assistant includes a robotic arm, a sensor assembly comprising a plurality of cameras aimed at a kitchen workspace for preparing the food items, a controller operable to move the robotic arm, and a processor. The processor is operable to command the robotic arm to perform a food preparation step on the food items in the kitchen workspace based on order information, recipe information, kitchen equipment information, and camera data. The system is capable of performing a wide range of tasks commonly used in residential and commercial kitchens and is able to work collaboratively with and in close proximity to human kitchen workers.

Abstract: A method of making a virtual substrate includes providing a donor substrate comprising a single crystal donor layer of a first material over a support substrate, wherein the first material comprises a ternary, quaternary or penternary semiconductor material or a material which is not available in bulk form, bonding the donor substrate to a handle substrate, and separating the donor substrate from the handle substrate such that a single crystal film of the first material remains bonded to the handle substrate.

Abstract: A robotic sled-enhanced food preparation system includes a robotic kitchen assistant operable to determine and to perform food preparation steps, and an autonomous mobile sled operable to supply the robotic kitchen assistant with ingredients and supplies. The robotic kitchen assistant includes a scheduling engine to evaluate food inventory levels and automatically determine when to replenish the food inventories using the sled if the food inventory levels are insufficient to complete the food preparation steps. Related methods are also described.

Abstract: An automated kitchen assistant system inspects a food preparation area in the kitchen environment using a novel sensor combination. The combination of sensors includes an Infrared (IR) camera that generates IR image data and at least one secondary sensor that generates secondary image data. The IR image data and secondary image data are processed to obtain combined image data. A trained convolutional neural network is employed to automatically compute an output based on the combined image data. The output includes information about the identity and the location of the food item. The output may further be utilized to command a robotic arm, kitchen worker, or otherwise assist in food preparation. Related methods are also described.

Abstract: A method for processing a database application component modification request includes receiving a request to modify a database application component of a database application, initiating the database application component modification, sending a response including instructions for accessing a database application component definition including the database application component modification, wherein the database application component definition is provided as a locally accessible temporary copy of the database application component.

Abstract: Protein-based meal replacements and foods, methods of manufacturing the protein-based meal replacements and foods, and different forms of the protein-based meal replacements and foods are disclosed. Implementations of the invention include combinations of egg based materials and value-added ingredients processed to form desired end products. Examples of end products include, but are not limited to, snack chips, crisps, croutons, French fries, cookies, donuts, breads, taco shells, tortillas, cereal, coatings, and other types of fried, baked, puffed, and/or otherwise cooked products.