This invention relates to a method for users localization and guidance of the movements of the users through a building adapted in relation to an event, along paths leading to one or more given target places, with connected objects (T, T′) in communication link with a remote resource server which is a control server (S) accessible by a communication network, comprising the following steps: on the basis of a digital model of the building (BIM, CIM), nodes (N) and edges (A) are computed; a user waiting list is assigned to each passage node; a Directed Acyclic Graph (DAG) of movement toward the target places (“E”, “S”, “W”) is automatically computed with the nodes and the edges (A); the actual location of an event is detected; the actual position of each user located in the building is computed; as a function of the profile of the user, of the user's location in real time in the building causing the inaccessibility of certain nodes of the Directed Acyclic Graph (DAG), the so-called ‘updated’ Directed Acyclic Graph (DAG′) of moving toward the target places; and a sub-graph DODAG′ are computed.

In some embodiments, apparatuses and methods are provided herein useful to detecting inbound and outbound traffic. In some embodiments, there is provided a system for detecting inbound and outbound traffic at a facility including a video camera and a control circuit configured to detect a human and estimate a location of the human; determine whether the detected human is inbound or outbound the facility based on a relative movement of the detected human within a first region, a second region, and a third region; and transmit data based on the determination.

Disclosed herein are systems and methods for detecting an event associated with a swimmer and generating a detection signal associated with the event.

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.

A detecting method for detecting a dynamic status in a space, wherein at least two wireless communication devices are deployed in the space and capable of performing a channel state detection to obtain a channel state information, the detecting method comprising: controlling the at least two wireless communication devices to perform the channel state detection in a registration stage to obtain a plurality of registration-stage channel state information; determining an environmental data of the space according to the plurality of registration-stage channel state information; controlling the at least two wireless communication devices to perform the channel state detection in a detection stage to obtain a plurality of detection-stage channel state information; and determining an intrusion situation of the space according to the environmental data and the plurality of detection-stage channel state information.

Systems and methods for operating a security system. The methods comprise: monitoring an area for a presence of an individual or vehicle using wireless signals of a first type that are received by a first radio of the security system; operating the first radio as a wireless sensor for generating sensor data; determining whether the individual or vehicle is exhibiting an unusual behavior using the sensor data and pre-programmed or machine learned patterns of unusual behavior; changing an operating frequency of the first radio when a determination is made that the individual or vehicle is exhibiting unusual behavior; and communicating a wireless signal of a second type from the first radio when the individual or vehicle is exhibiting unusual behavior, where the second type is different than the first type.

This disclosure includes technologies for action recognition in general. The disclosed system may automatically detect various types of actions in a video, including reportable actions that cause shrinkage in a practical application for loss prevention in the retail industry. Further, appropriate responses may be invoked if a reportable action is recognized. In some embodiments, a three-branch architecture may be used in a machine learning model for action and/or activity recognition. The three-branch architecture may include a main branch for action recognition, an auxiliary branch for learning/identifying an actor (e.g., human parsing) related to an action, and an auxiliary branch for learning/identifying a scene related to an action. In this three-branch architecture, the knowledge of the actor and the scene may be integrated in two different levels for action and/or activity recognition.

A method for artificial intelligence (AI) event response includes receiving an event alert or a communication associated with an event alert from a communication device. The method includes an AI system collecting additional information about at least one of the event alert, the communication device, or a user of the communication device. The method includes the AI system categorizing the event alert into one category of multiple categories based on the collected additional information. The method includes prioritizing subsequent handling of the event alert among other event alerts based on the category.

A machine learning system passively monitors sensor data from the living space of a patient. The sensor data may include audio data. Audio features are generated. A trained machine learning model is used to detect a change in condition. In some implementations, the machine learning model is trained in a learning phase based on training data that includes questionnaires completed by caregivers and identified audio features.

A camera orientation control system for changing one or more camera orientations of one or more cameras towards a potential incident that is not currently in a field of view of the one or more cameras. The camera control system processes image frames for head orientation extraction, determines an amount of synchronous alignment in a proportion of head objects of the head objects to computationally assess that they are towards a new direction, and controls at least one camera to move the field of view of at least one camera of the one or more cameras towards the new direction. The system is useful for incident detection and extending or augmenting the capabilities of CCTV infrastructure.