A system, wearable device and management device provided for predicting a flashover event. According to one aspect of the disclosure, a wearable device for predicting a flashover event is provided. The wearable device includes at least one thermal sensor configured to generate thermal data associated with an environment, and processing circuitry configured to: determine a risk of ignition of at least one combustible gas in the environment based on the thermal data, and trigger at least one action based on the determined risk of ignition.

The present invention provides a smoke detection method with visual depth, which uses an image camera and a depth camera to extract surrounding images and surrounding depth information. A vehicle is used to patrol an area, such as the area of a processing factory, for receiving the surrounding environment information and detecting existence of burning objects or smoke. Then a processor adopting the clustering algorithm is used to estimate the smoke distribution or the location of fire source of burning objects, and uses an alarm to provide alarm information. Thereby, the rescue crew can prepare in advance and respond immediately. By providing the correct information to the firemen in the fire scenes, the time to control the fire can be shortened and the time for evacuation can be increased.

A thermographic detector device for a fire alarm control system is described herein. In some examples, one or more embodiments include a thermography camera configured to capture a thermal image within a field of view of the thermographic detector device, a memory and a processor to execute instructions stored in the memory to detect a fault associated with the thermographic detector device, wherein the fault includes at least one of a field of view fault, an operating parameter fault, and an internal fault, generate a fault signal upon detecting the fault, and provide a notification of the fault using the fault signal.

Disclosed herein is a system for facilitating managing incidents occurring in areas monitored by low data-rate monitoring devices using the low data-rate monitoring devices, in accordance with some embodiments. Accordingly, the system comprises a processor, a device server, and a data visualization device. Further, a camera of a low data-rate monitoring device is configured for capturing video of an area. Further, the processor comprises a machine learning (ML) hardware accelerator configured for performing machine learning processing of the video. Further, the processor is configured for generating processed data. Further, the device server is configured for receiving the processed data based on the transmitting of the processed data from a low data-rate transceiver of the low data-rate monitoring device and transmitting a notification to a device. Further, the data visualization device is configured for visualizing the processed data, identifying an incident in the area, and generating the notification for the incident.

Provided are a system and method for estimating a location of a forest fire. The system for estimating the location of the forest fire may include an artificial intelligence-based forest fire detection module that detects a forest fire from a captured image using an artificial intelligence model; a monitoring camera configured to monitor a predetermined area; a direction estimation module configured to estimate a direction of the forest fire on a map, using a forest fire detection image provided from the artificial intelligence-based forest fire detection module and data of the monitoring camera; and a location estimation module configured to estimate the location of the forest fire, using an altitude map table configured to provide altitude of a corresponding location from latitude and longitude of the monitoring camera, based on the estimated direction of the forest fire.

The present invention relates to methods and apparatus for detection of fire states in the presence of welding activities. In some examples, the welding detection system may algorithmically calculate a risk of a fire state developing. In some embodiments, the welding fire detection and prevention system may communicate warning states to users, supervisors, equipment and/or building monitoring systems.

An image signal is received from a camera and a signal is received from each of a number of sensors. For each sensor, a position of a signal source is estimated based on the signal from the sensor. For each sensor, information on a situation expression expressing a situation is extracted based on the signal from the sensor. The situation expression for each sensor is superimposed on a captured image by the camera and the captured image superimposed with the situation expression for each sensor is output. In a case in which the sensors are located at different positions and the situation expression for each sensor overlap at least partially on the captured image, an overlapping order of the situation expressions for the sensors superimposed on the captured image is determined based on a distance between the camera and each sensor.

Systems and methods are provided for automatically performing an action based on video content. One example method includes receiving, at a first computing device, a video and determining, with a content determination engine, content of the video. An action to perform at the first computing device and/or at a second computing device is generated, based on the content of the video. If the action is to be performed at the second computing device, the action is transmitted to the second computing device. The action is performed at the respective first and/or second computing device.

An apparatus to locally monitor, and report to a remote monitoring system, specific physical conditions of equipment that provide early indication of failure conditions, including but not limited to: temperature, level of fluids, pressure, temperature, the presence of gases or airborne particulate, and signs leaks.

An emergency sensor system comprising: a plurality of environmental sensors; a local monitoring station (LMS) connected to each of the plurality of environmental sensors, the LMS comprising a transceiver, a processor, and a memory having stored thereon instructions that, when executed by the processor, control the processor to execute a method comprising: receiving, from at least one of the plurality of environmental sensors, sensor data indicative of an environmental state proximate the at least one environmental sensor, analyze the sensor data, and output, to a remote responder system, an alert based on the sensor data.