Abstract: Embodiments of the present disclosure may include a method of training an electro-mechanical system that includes local trainable AI, the method including training a local AI for a controller of the electro-mechanical surgical device or system with simulated data. Embodiments may also include performing a task or set of tasks or operations with the device or system as controlled, instructed, influenced, or the like by the controller having the local AI system. Embodiments may also include collecting real-life data from the step of performing. Embodiments may also include further training the local AI system and improving the AI simulated data generator with real-life data. Another embodiment relates to a system for providing a user with suggestions during social interactions. Embodiments of the invention may extend across many types of devices and systems, control systems, sensors, types of AI, and so forth, and combinations of the foregoing.

Abstract: A structural-health-monitoring system is disclosed for real-time detection and autonomous maintenance of physical structures. The system includes a sensor network comprising at least one strain gauge and one tri-axial accelerometer mounted on the structure to generate real-time sensor signals. A perception module filters and normalizes the signals and extracts numerical features such as peak amplitude and dominant frequency. A digital-twin module maintains a finite-element model updated in response to the extracted features. A data-driven surrogate model predicts sensor behavior and refines itself using machine-learning techniques. An anomaly-detection module computes an anomaly score from model residuals or classifier outputs. Upon exceeding a threshold, a maintenance module initiates a maintenance action, including generating an inspection schedule or issuing a control signal to an autonomous inspection or repair device.

Abstract: A structural-health-monitoring system is disclosed for real-time detection and autonomous maintenance of physical structures. The system includes a sensor network comprising at least one strain gauge and one tri-axial accelerometer mounted on the structure to generate real-time sensor signals. A perception module filters and normalizes the signals and extracts numerical features such as peak amplitude and dominant frequency. A digital-twin module maintains a finite-element model updated in response to the extracted features. A data-driven surrogate model predicts sensor behavior and refines itself using machine-learning techniques. An anomaly-detection module computes an anomaly score from model residuals or classifier outputs. Upon exceeding a threshold, a maintenance module initiates a maintenance action, including generating an inspection schedule or issuing a control signal to an autonomous inspection or repair device.

Abstract: A structural-health-monitoring system is disclosed for real-time detection and autonomous maintenance of physical structures. The system includes a sensor network comprising at least one strain gauge and one tri-axial accelerometer mounted on the structure to generate real-time sensor signals. A perception module filters and normalizes the signals and extracts numerical features such as peak amplitude and dominant frequency. A digital-twin module maintains a finite-element model updated in response to the extracted features. A data-driven surrogate model predicts sensor behavior and refines itself using machine-learning techniques. An anomaly-detection module computes an anomaly score from model residuals or classifier outputs. Upon exceeding a threshold, a maintenance module initiates a maintenance action, including generating an inspection schedule or issuing a control signal to an autonomous inspection or repair device.

Abstract: A method of enabling a capability of an electronic device includes interrogating, with a radio frequency reader, a passive wireless identifier that is embedded within and shares a power grid with logic circuitry of an integrated circuit die present in the electronic device. The passive wireless identifier occupying no more than about 0.1 mm2 of die area. Identifier data is received from the passive wireless identifier. The method also includes verifying that the identifier data satisfies predetermined unlock criteria. The capability of the electronic device is enabled in response to the verifying.

Abstract: A method includes reading data encoded on a tiny RFID tag that is embedded in an integrated circuit. The RFID tag has an area of 0.1 mm2 or less and, alternatively, of 0.05 mm2 or less. When the data satisfies predetermined criteria, a capability of a device or system is unlocked. The method may be used in conjunction with artificial intelligence (AI) for identification and authentication, fraud detection, behavioral analysis, predictive analytics, and/or access control, for example. The method may also be used in credit and/or debit card transactions, in which the tiny RFID tag and integrated circuit are on a credit and/or debit card. In another embodiment, the RFID tag and IC are incorporated into a label. The label may optionally be on a good for sale.

Abstract: A method of unlocking an operation of a Class III medical device suitable for use in treating, for example, COVID 19 in humans is presented. An integrated circuit is inserted or integrated into a medical device having an RFID reader, the medical device having a capability that is in a locked state. The integrated circuit has a first tiny RFID tag embedded therein. The RFID tag has an area of about 0.1 mm2 or less. The RFID tag is a largely digital tag that is implemented using portable digital IP blocks, the RFID tag utilizing dual-phase RF-only logic.

Abstract: The present disclosure may include a method of training an electro-mechanical system that includes local trainable AI, including training a local AI for a controller of the electro-mechanical system with simulated data. A task or set of tasks or operations with the device or system as controlled, instructed, influenced, or the like by the controller having the local AI system may be performed. Real-life data may be collected from the step of performing. Further training of the local AI system is done and improving the AI simulated data generator with real-life data. A chat function may provide a human ability to ask questions. In another aspect, a system for providing a user with suggestions during social interactions. The invention may extend across many combinations of devices and systems, control systems, sensors, types of AI, and so forth.

Abstract: A method includes reading data encoded on a tiny RFID tag that is embedded in an integrated circuit. The RFID tag has an area of 0.1 mm2 or less and, alternatively, of 0.05 mm2 or less. When the data satisfies predetermined criteria, a capability of a device or system is unlocked. The method may be used in conjunction with artificial intelligence (AI) for identification and authentication, fraud detection, behavioral analysis, predictive analytics, and/or access control, for example. The method may also be used in credit and/or debit card transactions, in which the tiny RFID tag and integrated circuit are on a credit and/or debit card. In another embodiment, the RFID tag and IC are incorporated into a label. The label may optionally be on a good for sale.

Abstract: \A method of unlocking an operation of a Class III medical device suitable for use in treating, for example, COVID 19 in humans is presented. An integrated circuit is inserted or integrated into a medical device having an RFID reader, the medical device having a capability that is in a locked state. The integrated circuit has a first tiny RFID tag embedded therein. The RFID tag has an area of about 0.1 mm2 or less. The RFID tag is a largely digital tag that is implemented using portable digital IP blocks, the RFID tag utilizing dual-phase RF-only logic.

Abstract: A method of unlocking an operation of a Class III medical device suitable for use in treating, for example, COVID 19 in humans is presented. An integrated circuit is inserted or integrated into a medical device having an RFID reader, the medical device having a capability that is in a locked state. The integrated circuit has a first tiny RFID tag embedded therein. The RFID tag has an area of about 0.1 mm2 or less. The RFID tag is a largely digital tag that is implemented using portable digital IP blocks, the RFID tag utilizing dual-phase RF-only logic.

Abstract: A method of unlocking an operation of a Class III medical device suitable for use in treating, for example, COVID 19 in humans is presented. An integrated circuit is inserted or integrated into a medical device having an RFID reader, the medical device having a capability that is in a locked state. The integrated circuit has a first tiny RFID tag embedded therein. The RFID tag has an area of about 0.1 mm2 or less. The RFID tag is a largely digital tag that is implemented using portable digital IP blocks, the RFID tag utilizing dual-phase RF-only logic.

Abstract: An apparatus and method is provided for gyro-controlled gaming viewpoint with auto-centering. A virtual camera is positioned at a first position while the virtual camera views a first object at a first direction. Once the system moves, the virtual camera moves to a second position based on a measurement by an angular velocity sensor. While the virtual camera moves to the second position, the viewing direction of the virtual camera simultaneously so as to keep the first object positioned in a same position of a viewing direction of the virtual camera. The apparatus and method allow the system to move a virtual camera based on a measurement of a gyroscope while keeping an object of importance in the center of the field-of-view of the virtual camera.

Abstract: An apparatus and method is provided for controlling a virtual camera. The virtual camera is positioned in a first position and a first direction while an object is in a first state and the virtual camera is moved to a second position and second direction when the object transitions from a first state to a second state. The virtual camera is held in the second position and second direction while the object is in the second state and then moves back to the first position and first direction when the object transitions from the second state back to the first state. While the virtual camera is in the second position and second direction, the lowest part of the object is made more easily viewable.