A system for remote detection of a fire condition includes a plurality of remote sensors and a central hub connected to each sensor to create a localized network capable of detecting changes in environmental conditioned within a geographic area defined by the locations of the sensors. The sensors may be configured to detect conditions such as changes in temperature, levels of carbon dioxide, smoke or other fire related particulates and report sensor readings back to the connected hub. The hub processes received sensor data from each sensor and generates an alert if the processed data meets any predetermined condition such as one associated with a fire. The alert may be transmitted to a tracking station with a geographic indication of where the alert was generated and a drone may be sent to the location of the geographic indication to acquire additional data to help determine if further action is required.

A method includes 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.

The network enabled fire sensor and fire extinguishing system is a fire-fighting apparatus comprising a plurality of extinguisher modules. The plurality of extinguisher modules forms a wireless communication link between: a) the plurality of extinguisher modules, and, b) with an appropriate authority. When triggered by fire, the individual extinguisher module: c) releases a fire extinguishing chemical; and, d) transmits an alert message to both the appropriate authority and to the individual extinguisher modules remaining in the plurality of extinguisher modules containing the GPS coordinates of the transmitting individual extinguisher module. Each selected individual extinguisher module compares the GPS coordinates of the selected individual extinguisher mode to the GPS coordinates of the module alert message. If the span of the distance between the two coordinates is less than a previously determined span of distance, than the selected individual extinguisher module releases a fire retardant chemical.

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.

Disclosed is a method and system for determining an area of fire and a method and system for estimating progression of a fire in the determined area of fire. The method for determining the area of fire comprises receiving sensor data from a plurality of sensor modules and determining the area of fire based on relative locations of the sensor modules with respect to each other. The method for estimating progression of a fire comprises receiving first and second sensor data from at least one sensor module and devising a plurality of fire scenarios for each of the sensor data. The method further comprises determining a likelihood of each of the plurality of fire scenarios to identify a potential combination of fire scenarios to estimate the progression of the fire.

A transformer monitoring device has one or more voltage sensors and/or one or more current sensors integral with a housing for detecting voltage and/or current of a power cable of a transformer. The transformer monitoring device can be configured to monitor voltage data, current data, voltage imbalance, phase angle, outage detection and restoration detection, and/or transformer temperature changes, etc., and cause alerts to be issued directly and/or by a remote central computing device if voltage levels drop and/or spike beyond operator-established tolerance(s), and/or if transformer temperature changes occur outside of operator-established tolerance(s), and/or if a power outage or power restoration occurs, and/or if voltage imbalance occurs, along with additional alert messaging capabilities to be provided by the transformer monitoring device where utility operator personnel would find value. The transformer monitoring device further has one or more onboard, and/or external wired and/or wireless environmental and/or transformer conditions sensor(s) and/or sensor packs, including a smoke sensor, ambient temperature sensor, external transformer temperature sensor, a fire/wildfire sensor (e.g., infrared camera, etc.), a humidity sensor, a noxious gases sensor, a nuclear radiation sensor, a seismic or vibration sensor, and/or a surface and/or ground temperature sensor (e.g., infrared camera, etc.) configured to detect smoke, and/or temperature change indicators, and/or other environmental changes in an area surrounding the transformer and/or associated with the transformer, and a processor configured to monitor the smoke sensor, temperature sensors, and/or other environmental change sensors, and/or associated transformer sensors; the processor being configured to transmit data indicative of conditions concerning the transformer and/or surrounding the transformer, and/or issue an alert or critical alert if certain smoke, temperature and/or other environmental conditions are detected surrounding the transformer and/or occurring at or near the transformer. The transformer monitoring device, when used for voltage drops and/or voltage spikes monitoring or detection indicative of broken, down, and/or faulty conductors (e.g., high-impedance faults), and/or when coupled with one or more environmental surroundings sensors (i.e., internal and/or external to the transformer monitoring device), wired and/or wirelessly coupled to the transformer monitoring device, and/or for monitoring transformer and/or intra-grid conditions, becomes a fire mitigation device. The fire mitigation device(s) is used singly or in aggregate to help detect public safety events and/or fire/wild

A remote fire detection system includes a plurality of sensor nodes, each comprising a smoke sensor, a temperature sensor, a gas sensor, and a processor having inputs coupled to the outputs of the sensors. The processor processes the sensor signals to generate at least one of smoke, temperature, or gas metric information, and determines a unique time window within a reporting period. A transmitter transmits report generated by the processor during the unique time window within the reporting period. A personnel node includes a location processor that generates location information of the personnel node and a transmitter that transmits the location information. A gateway node includes a receiver that receives reports generated by the plurality of sensor nodes during the unique time window within the reporting period. A processor generates a waveform comprising synchronization pulses during the reporting period and processing the received reports generated by the plurality of sensor nodes to generate an uplink message in response to the at least some of the sensor metric information. A transmitter transmits the waveform and the uplink message. A server node receives the uplink message and determines a probability of a fire at a location based on sensor metric information of the received uplink message.

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.

Systems and methods for utility infrastructure condition monitoring, detection, and response are disclosed. One exemplary system includes a sensor package and a monitoring and control module. The sensor package includes a plurality of sensors such as, for example, an image sensor, a video sensor, and a LiDAR sensor. The sensors may each be configured to capture data indicative of one or more conditions (e.g., an environmental condition, a structural condition, etc.) in the vicinity of the utility infrastructure. The monitoring and control includes a detection module and an alert module. The detection module is configured to receive data captured by each sensor and, based on the captured data, determine one or more conditions in the vicinity of the utility infrastructure. The detection module may be configured to then, based on the determined conditions, provide an alert for the condition using the alert module.

Methods, apparatuses, and systems for wildfire detection using power infrastructure are described. One or more aspects of the techniques described include determining (e.g., quantifying) the impact of wildfires on power structures and transmission line sensors. Determination of measurable changes in transmission line temperature and transmission line sag, that result from early onset fires, are used to detect heat events. Therefore, real-time monitoring of transmission line temperature and transmission line sag (e.g., using sensors that are already deployed in some power grid infrastructures) may efficiently detect the early onset of wildfires according to techniques described herein.