System and method for detection of pre-drowning and drowning events based on underwater images are disclosed.

An access management system includes a mobile device with a processor and a memory and a software platform including at least a processor and a memory. The software platform is configured to analyze data obtained from the mobile device and other devices connected to the software platform. Specifically, the software platform is operable to determine if an access key received, read, or captured by a mobile device matches an access key for an authorized account, object, device, or space for the mobile device, and to provide access to the mobile device if the access key received, read, or captured by the mobile device matches the authorized access key.

A device for acoustic monitoring of a monitoring area includes first and second sensor systems which have first and second acoustic sensors, processors, and transmitter, respectively, and which may be mounted at different locations of the monitoring area. The first and second processors may be configured to classify first and second audio signals detected by the first and second acoustic sensors so as to obtain first and second classification results, respectively. The first and second transmitter may be configured to transmit the first and second classification results to a central evaluator, respectively. In addition, the device may include the central evaluator, which may be configured to receive the first classification result and to receive the second classification result, and to generate a monitoring output for the monitoring area as a function of the first classification result and the second classification result.

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.

The present disclosure relates to system(s) and method(s) for alerting one or more service providers based on analysis of real-time sensor data. The system is configured to receive real-time sensor data and historical sensor data captured by one or more agent devices. Further, the system is configured to determine an anomaly corresponding to a target agent device from the one or more agent devices, based on comparison of the real-time sensor data and one or more predefined threshold parameters. The system is further configured to generate an alert corresponding to the anomaly and identify one or more service providers, affected by the anomaly, based on analysis of the historical sensor data and the anomaly. Further, the system is configured to transmit the alert to the one or more service providers, thereby alerting the one or more service providers.

A detector is configured to be mounted to a container. The detector has a housing and a mounting arrangement for mounting the housing to a container. A sensor arrangement includes a sensor to monitor the container and to generate a sensor output signal in response to a sensed container event. A processor executes a machine learning algorithm trained to determine a class of the sensed container event for determining occupancy of the container from the sensor output signal, where the control system is configured to provide an output based on the class of sensed container event determined by the machine learning algorithm.

According to one aspect, a computer-implemented method for detecting an earthquake includes detecting vibrations in a trackpad of a computing device using an inductive element and force sensing circuitry of the trackpad and, processing, by a microcontroller of the computing device, the vibrations for detection of an earthquake vibration signal. In response to detecting the earthquake vibration signal, communicating, by the computing device, the earthquake vibration signal to a remote server and receiving, at the computing device, an earthquake alert from the remote server.

Examples described herein generally relate to a system for monitoring tags in a retail environment. The system includes an exit system including one or more sensors that read a tag to obtain exit system measurements associated with a tag detection event. The system includes a memory and a processor configured to execute instructions to receive a selection of a base configuration, the base configuration including weighting values for a plurality of exit system measurements. The processor may classify a tag detection event into a first tag status for the tag detection event based on application of the weighting values to exit system measurements associated with the tag detection event. The processor may determine a second tag status of the tag after the tag detection event. The processor may update the weighting values using a machine-learning algorithm based on at least the first tag status and the second tag status.

System and method for detection of pre-drowning and drowning events based on underwater images are disclosed.

An apparatus and a method for controlling an interior of a vehicle are disclosed. The apparatus for controlling the interior of the vehicle may include an interface configured to receive, at predetermined cycles, information on at least one of video of an inside of the vehicle collected by a camera or sound of the inside of the vehicle collected from a microphone, and a processor configured to determine a relationship between passengers in the vehicle based on the information, and control the interior of the vehicle based on the relationship between the passengers. When determining the relationship between passengers, a passenger relationship estimation algorithm used may be a neural network model generated through machine learning, and may be stored in a memory in the apparatus for controlling the interior of the vehicle, or may be provided via a server in an artificial intelligence environment through a 5G network.