A reader device of a physical access control system comprises an ultra-wide band (UWB) physical layer and processing circuitry. The processing circuitry is operatively coupled to the UWB physical layer and is configured to: receive access credential information from a separate second device; receive ranging information from the second device; grant access through a physical portal according to the access credential information and ranging information; determine a number of people intending to pass through the physical portal; and generate an indication according to the determined number.

Systems and methods are described, and an example method includes a training an artificial intelligence (AI) classifier of scanned items, including obtaining a training set of sample raw scans. The set includes a population of sample in-class raw scans, which include blocks of sensor data from scans of regions having in-class objects, and the set includes a population of sample not-in-class raw scans, which include blocks of sensor data from scan of regions without in-class objects. The example includes applying the AI classifier to sample raw scans in the training set, measuring errors in the results, and updating classifier parameters based on the errors, until detecting a training completion state.

Embodiments are generally directed to identification of objects for three-dimensional depth imaging. An embodiment of an apparatus includes one or more processors to process image data and control operation of the apparatus; an image sensor to collect image data; and a receiver and transmitter for communication of data, wherein the apparatus is to receive a notification of a first device entering a physical space, transmit a request to the device for a light signal to identify the device, detect the light signal from the device, determine a location of the device, and store an identification for the first device and the determined location of the first device in a database.

A building management system of a building includes one or more memory devices configured to store instructions thereon, that, when executed by one or more processors, cause the one or more processors to generate agents, each agent of the agents paired with one entity of a plurality of entities of an entity database, wherein the entity database includes relationships between the entities, wherein the entities represent physical building entities of the building comprising building equipment or building spaces. The instructions cause the one or more processors to communicate, by the plurality of agents, data of the physical building entities via a plurality of agent communication channels and perform, by the plurality of agents, one or more operations for the plurality of entities based on the data.

A bio-sensor device, integrated with a display portion, includes a surface for touching by a body part, such as a finger. A light source, such as an array of LEDs, emit light through the surface so as to be reflected and partially absorbed by the body part An array of photodetectors detects light reflected back by the body part and generates signals corresponding to an image of the light reflection, which corresponds to the light absorption pattern in the body part. The light absorption pattern may correlate to a fingerprint, a blood vessel pattern, blood movement within the blood vessels, combinations thereof, or other biometric feature. A processor receives the signals from the photodetectors and analyzes the signals to determine a characteristic of the body part. The characteristic may be used to authenticate the user of the bio-sensor device by comparing the detected characteristic to a stored characteristic.

Computer vision systems for segmenting scenes into semantic components identify a differential within the physiological readings from the user. The differential corresponds to a semantic boundary associated with the user's gaze. Based upon data gathered by a gaze tracking device, the computer vision system identifies a relative location of the user's gaze at the time of the identified differential. The computer vision system then associates the relative location of the user's gaze with a semantic boundary.

Embodiments disclose a device for testing biological specimen. The device includes a sample carrier and a detachable cover. The sample carrier includes a specimen holding area. The detachable cover is placed on top of the specimen holding area. The detachable cover includes a magnifying component configured to align with the specimen holding area. The focal length of the magnifying component is from 0.1 mm to 8.5 mm. The magnifying component has a linear magnification ratio of at least 1.

Methods, structures and computer program products for digital sample rate conversion are presented. An input digital sample with a first frequency is converted to an output sample with a second frequency. A sample rate conversion circuit is provided which provides an enhanced transposed farrow structure that enables an optimised trade-off between noise levels and computational complexity. Each output sample is derived by convolution of a continuous time interpolation kernel with a continuous time step function representing the input sample stream. In a sample rate conversion structure, there is a trade-off between the quality and the computational complexity. The quality is defined as a ratio between the (wanted) signal power and the (unwanted) noise power. The computational complexity may be defined as the average number of arithmetic operations that are required to generate one output sample. A higher computational complexity will generally lead to a higher power consumption and larger footprint.

A rehabilitation system includes: a rehabilitation robot configured to execute corresponding actions according to motion instructions; a brain wave detector configured to detect brain wave signals of a user; and control device configured to generate motion instructions according to brain wave signals to control the rehabilitation robot to execute corresponding actions.

A fall detection system includes first sensing devices, second sensing devices, positioning modules, a data server and a display device. The first sensing device is configured to detect a posture of a body part of a user for obtaining body part posture data. The positioning modules are configured to detect positions of the first and second sensing devices, so as to obtain corresponding body part position data. Each of the second sensing devices is disposed on a shoe to detect a posture of a user's feet and to measure a distance from an ambient object for obtaining feet posture data and distance measurement data. The data server is configured to receive the body part posture data, the body part position data, the feet posture data and the distance measurement data to determine if the user falls down.