Virtual sensor technology, in which a camera is controlled to capture at least one configuration image of an area monitored by a monitoring system and input is received that defines one or more characteristics of the at least one configuration image that enable sensing of an event in the area. Based on the received input, configuration data used in sensing the event is generated and stored. After storage of the configuration data, the camera is controlled to capture one or more images of the area, the one or more images are analyzed based on the configuration data, and occurrence of the event is detected based on the analysis of the one or more images. Based on detecting occurrence of the event, a transmitting device is controlled to send, to a controller of the monitoring system, a signal that indicates the detection of the occurrence of the event.

A system for monitoring event related data including a sensor data analyzer, an event analyzer and an actuator is disclosed. The sensor data analyzer detects events based on sensor data, the event analyzer couples to the sensor data analyzer and estimates the size of the detected entire events based on event related data of the detected events from the sensor data analyzer, and the actuator couples to the sensor data analyzer and the event analyzer and actuates a predetermined device based on the estimated size of the detected entire events.

A dynamic alarm priority system includes plural kinds of alarm devices, an alarm signal being generated when the alarm device is triggered; a plurality of image capture devices, correspondingly coupled to the alarm devices respectively, the triggered alarm device activating the corresponding image capture device to capture an alarm image; an interface device that receives the alarm signal; an assignment device coupled to receive the alarm signals, which are assigned priorities in order of time, thereby generating an initial alarm signal sequence; and an object detection device that performs object detection on the alarm image to determine whether an associated object is detected in the alarm image. The assignment device dynamically modifies the initial alarm signal sequence according to an object detection result from the object detection device, thereby generating an updated alarm signal sequence.

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.

A system for monitoring event related data including a sensor data analyzer, an event analyzer and an actuator is disclosed. The sensor data analyzer detects events based on sensor data, the event analyzer couples to the sensor data analyzer and estimates the size of the detected entire events based on event related data of the detected events from the sensor data analyzer, and the actuator couples to the sensor data analyzer and the event analyzer and actuates a predetermined device based on the estimated size of the detected entire events.

Various embodiments of the present invention relate to remote fire extinguishing equipment and remote crime prevention and extermination equipment, and the technical problem to solve is to provide remote fire extinguishing equipment and remote crime prevention and extermination equipment which remotely detect fire or trespassing so as to extinguish the region of the fire or eject a trespasser. To this end, disclosed are remote fire extinguishing equipment and remote crime prevention and extermination equipment, the remote fire extinguishing equipment comprising: a flame detecting sensor which detects a flame when a fire occurs and transmits a flame detection signal through a communication network; a smart phone which, when receiving the flame detection signal through the communication network, transmits, through the communication network, a photographing signal with respect to a fire occurring region; an IP camera unit which, when receiving the photographing signal from the smart phone, photographs the fire occurring region and transmits, through the communication network, a photographed image to the smart phone; and a smart plug which, when receiving, through the communication network, a user control signal of the smart phone, sprays a fire extinguishing material to the fire occurring region.

The present disclosure relates to a fire detection system based on AI and a fire detection method based on Ai, which detects fire by using deep learning. The fire detection system includes a camera part generating video images, an object extraction part extracting a motion object from the video images, a video image conversion part generating a first background removal image, an image division part dividing the first background removal image with a plurality of division lines, and an analyzing part generating an abnormal signal and a normal signal.

This invention embodies a 24-7 fire protection system for fires originating outside of a structure. The invention integrates stand-alone, facility-based fire protection systems, control module and video and thermal sensors with offsite control functionality at the offsite Fire Defense Center (FDC). through multiple, redundant communications systems. Trained operators use sensor input and additional data streams to monitor fire threat in real time and deploy onsite optimized structure defense systems at the optimum time. System can be deployed onsite, remotely by an authorized facility owner/manager (via mobile application or Internet connection) or, by an autonomous control system in pre-set specified emergencies. This invention embodies the mapping, pipe and valve layout, and devices to cover the structure and, if desired, surrounding defensible spaces with a gel-water mix. The invention's gel-water mix provides protection for 48 hours, depending on humidity, more than enough for a fire front to pass the structure.

A system includes a processing device and memory device storing instructions that result in accessing a first dataset including aerial imagery data, accessing a second dataset including property boundary data, and identifying property boundaries associated with a geographic area. A plurality of artificial-intelligence (AI) models are applied to the datasets to identify and compute information of interest. Based on the first dataset and constrained by the property boundaries, a building detection model can be applied to identify a building footprint, and a tree detection model can be applied to identify one or more trees. An estimated distance can be determined between each of the trees and a nearest portion of the building footprint as separation data, which can be compared to a defensible space guideline to determine a defensible space adherence score. A wildfire risk map can be generated, including the defensible space adherence score associated with the geographic area.

A computer-implemented method, comprising: obtaining motion indicators for a plurality of samples of a video stream; obtaining an anomaly state for each of a plurality of time windows of the video stream, each of the time windows spanning a subset of the samples, by (i) obtaining estimated statistical parameters for the given time window based on measured statistical parameters characterizing the motion indicators for the samples in at least one time window of the video stream that precedes the given time window and (ii) determining the anomaly state for the given time window based on the plurality of motion indicators obtained for the samples in the given time window and the estimated statistical parameters; and processing the video stream based on the anomaly state for various ones of the time windows.