A hub device including a housing defining an interior, a plurality of sensors, and a controller module. The plurality of sensors being provided within the interior or along a portion of the housing. The controller module having access to a memory comprising a set of preloaded software and a set of additional software. At least one of least one of the set of preloaded software or the set of additional software is configured to allow the hub device to be communicatively couplable to at least one additional hardware.

A method and apparatus for monitoring a human or animal subject in a room using video imaging of the subject and analysis of the video image to detect and quantify movement of the subject and to derive an estimate of vital signs such as heart rate or breathing rate. The method includes techniques for de-correlating global intensity variations such as sunlight changes, compensating for noise, eliminating areas not of interest in the image, and quickly and automatically finding regions of interest for detecting subject movement and estimating vital signs. A logic machine is used for interpreting detected movement of the subject, and an artificial neural network is used to calculate a confidence measure for the vital signs estimates from signal quality indices. The confidence measure may be used with a normal density filter to output estimates of the vital signs.

A monitoring system a user activity sensor to determine patterns of activity based upon the user activity occurring over time.

A method and apparatus for monitoring a human or animal subject in a room using video imaging of the subject and analysis of the video image to detect and quantify movement of the subject and to derive an estimate of vital signs such as heart rate or breathing rate. The method includes techniques for de-correlating global intensity variations such as sunlight changes, compensating for noise, eliminating areas not of interest in the image, and quickly and automatically finding regions of interest for detecting subject movement and estimating vital signs. A logic machine is used for interpreting detected movement of the subject, and an artificial neural network is used to calculate a confidence measure for the vital signs estimates from signal quality indices. The confidence measure may be used with a normal density filter to output estimates of the vital signs.

An acquisition imaging system is described herein that acquires multiple images from multiple imagers where each are sent to a single processor/controller, resulting in a single, resultant image providing a detailed field of view. The system is comprised of multiple sets of images taken by multiple sensors, strategically placed to acquire multiple perspectives of an image field. Each sensor is packaged with digitization, compression and communication components in an imager to allow for the transfer of the image to a processor/controller system controller. The system's controller acts as the network interface, power supply and centralized management for processing information, specifically the analytics. The present invention has applications in surveillance, event classification systems, indexed archival storage, real-time and post facto image content analytics, future filtering vectors; ad hoc querying, automatic queries, and multiple query languages.

Systems and methods for improved operations of ski lifts increase skier safety at on-boarding and off-boarding locations by providing an always-on, always-alert system that “watches” these locations, identifies developing problem situations, and initiates mitigation actions. One or more video cameras feed live video to a video processing module. The video processing module feeds resulting sequences of images to an artificial intelligence (AI) engine. The AI engine makes an inference regarding existence of a potential problem situation based on the sequence of images. This inference is fed to an inference processing module, which determines if the inference processing module should send an alert or interact with the lift motor controller to slow or stop the lift.

It is provided a method for controlling camera-based supervision of a physical space. The method is performed in a supervision controller and comprises the steps of: determining that a person enters the physical space; deactivating camera-based supervision of the physical space based on the person entering the physical space, by turning off a video feed of the camera-based supervision; determining that a person exits the physical space; and activating camera-based supervision of the physical space based on the person exiting the physical space.

A fall prevention system includes an image capturing unit that captures an image of a space to be monitored; a skeleton model generating unit that generates a skeleton model representing a person in the image captured by the image capturing unit; a determination unit that determines a state of a person corresponding to the skeleton model generated by the skeleton model generating unit, by distinguishing between the person standing up and the person sitting down, based on the skeleton model; and an operation processing unit capable of executing a fall prevention process that is a process according to a determination result by the determination unit, and that prevents the person from falling over, based on the determination result.

The purpose of the present invention is to provide a fall risk evaluation system whereby risk of falling of an elderly person or other person to be managed can be easily evaluated on the basis of a captured image of daily life, instead of by a physical therapist, etc. To achieve this purpose, the present invention is a fall risk evaluation system comprising a stereo camera and a fall risk evaluation device, the fall risk evaluation device being provided with: a person authentication unit for authenticating a person to be managed who has been imaged by the stereo camera; a person tracking unit for tracking the person to be managed who is authenticated by the person authentication unit; an action extraction unit for extracting walking by the person to be managed; a feature value calculation unit for calculating a feature value of the walking extracted by the action extraction unit; an integration unit for generating integrated data obtained by integrating the outputs of the person authentication unit, the person tracking unit, the action extraction unit, and the feature value calculation unit; a fall index calculation unit for calculating a fall index value of the person to be managed, on the basis of a plurality of integrated data generated by the integration unit; and a fall risk evaluation unit for comparing the fall index value calculated by the fall index calculation unit and a threshold value to evaluate the risk of falling of the person to be managed.

An information processing apparatus includes a setting unit configured to set an imaging condition under which an imaging apparatus captures a video, a region determination unit configured to determine a detectable region in which a detection target is detectable in the video, based on the imaging condition, an acquisition unit configured to acquire a desired detection condition under which a user desires detection for the detection target to be executed, and a condition determination unit configured to determine a detection condition under which the detection target is detected from the video, based on the desired detection condition and the detectable region determined based on at least one imaging condition.