In some examples, a security application may monitor data received from one or more of sensors of a computing device, one or more input devices of the computing device, or one or more biometric sensors of a smartwatch that is connected to the computing device. If the user is not logged in and the user that is carrying the computing device has an uneven gait or is stumbling, the security app may, when the user initiates a login process, gather additional data, such as, from the sensors, the smartwatch, or both. If the user makes too many errors, based on data from the input devices, when attempting to login or after logging in, the security application may gather additional data. If the additional data indicates that the user may be under the influence of prescription or recreational drugs or alcohol, the user may be prevented from logging in.

A method may include, in an operating system, implementing a sensor hub in firmware of a platform controller hub of an information handling system, the sensor hub configured to implement a plurality of sensor physical microdrivers, each of the plurality of sensor physical microdrivers corresponding to a respective sensor of a plurality of sensors and configured to communicate a signal representing a physical quantity sensed by the respective sensor; a plurality of algorithm microdrivers implemented as virtual microdrivers, each of the plurality of algorithm microdrivers corresponding to a respective sensor physical microdriver of the plurality of sensor physical microdrivers; and a user-awareness arbitration microdriver implemented as a virtual microdriver and configured to receive an arbitration policy for user awareness detection, receive sensor information from the plurality of algorithm microdrivers, and based on the arbitration policy, apply arbitration logic to the sensor information to determine a user awareness.

The present invention is a human centric lighting (HCL) method with adjustable lighting parameters comprises the following steps: 1) User connects with the cloud through the intelligent communication device and selects the specific spectral recipe that the user wants to achieve a specific emotion from the cloud; 2) The light emitting device is configured to emit light in a specific light field according to the lighting parameters in a specific light field to select the light in a specific light field; 3) After the user performs HCL, when the effect of specific emotion is not reached, the user adjusts the lighting parameters in the selected specific spectral recipe through the intelligent communication device; 4) When the user has achieved the effect of specific emotion after performing HCL, store the corresponding lighting parameters of the adjusted spectral recipe to the cloud.

Apparatus, systems, and methods are provided for generating a quantified indicator of cognitive skills in an individual. In certain configurations, the apparatus, systems, and methods can be implemented for enhancing cognitive skills in an individual.

Provided is a server. The server comprises a communicator configured to receive or transmit data from or to an external network and a processor configured to receive, through the communicator, service data of an electronic device, device data of the electronic device, and weather data for the electronic device and to calculate emotion index data based on the service data, the device data, and the weather data. Accordingly, customer's emotion index data may be efficiently calculated.

A method for performing multi-touch (MT) data fusion is disclosed in which multiple touch inputs occurring at about the same time are received to generating first touch data. Secondary sense data can then be combined with the first touch data to perform operations on an electronic device. The first touch data and the secondary sense data can be time-aligned and interpreted in a time-coherent manner. The first touch data can be refined in accordance with the secondary sense data, or alternatively, the secondary sense data can be interpreted in accordance with the first touch data. Additionally, the first touch data and the secondary sense data can be combined to create a new command.

A volumetric content enhancement system (“the system”) can annotate at least a portion of a plurality of voxels from a volumetric video with contextual data. The system can determine at least one actionable position within the volumetric video. The system can create an annotated volumetric video that includes the volumetric video, an annotation with the contextual data, and the at least one actionable position. The system can provide the annotated volumetric video to a volumetric content playback system. The system can obtain viewer feedback associated with the viewer and can determine an emotional state of the viewer based, at least in part, upon the viewer feedback. The system can receive viewer position information that identifies a specific actionable position of the viewer. The system can generate manipulation instructions to instruct the volumetric content playback system to manipulate the annotated volumetric content to achieve a desired emotional state of the viewer.

Provided is an information processing apparatus that performs human emotion recognition using artificial intelligence.

The information processing apparatus includes: a preprocessing unit that determines whether or not to permit provision of a service based on emotion recognition on the basis of a predetermined criterion; an emotion estimation processing unit that performs the emotion recognition for a user by using an artificial intelligence function; and a service providing processing unit that provides a service based on an emotion recognition result by the emotion estimation processing unit, in which, when the preprocessing unit determines to permit the provision of the service, the emotion estimation processing unit performs the emotion recognition or the service providing processing unit provides the service.

Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing augmented reality assistance mode functionalities. Certain embodiments utilize systems, methods, and computer program products that perform augmented reality assistance mode functionalities by using at least one of environment familiarity predictions, assistance mode triggering need determinations, and threat detection machine learning models.

A system assists a worker in performing manufacturing tasks involving one or more objects. The system comprises an augmented-reality display system, a task-state sensing system that determines a state of a manufacturing task, a physiological-state-sensing system that detects a physiological state of the worker, and an electronic processing system. The electronic processing system determines a guidance setting for the worker from their detected physiological state and determines assistance information to display to the worker based on the state of the manufacturing task and the determined guidance setting for the worker. The augmented-reality display system displays the determined assistance information to the worker in a controlled spatial relationship to the object(s).