A gunshot detection system includes gunshot sensor units with microphones for detecting gunshots and capturing audio data depicting the detected gunshots and other ambient sounds, an environmental board with various environmental sensors for generating environmental data indicating environmental conditions. The audio data, environmental data, and position information can be stored locally on local nonvolatile storage of the gunshot sensor unit for later retrieval by law enforcement entities. In one embodiment, the gunshot sensor units include a wired and/or wireless data transfer interface for transferring the audio data, environmental data and/or position information to handheld units of law enforcement entities. The gunshot sensor unit can also stream live captured audio data for live monitoring by a control panel, and might also include speakers for providing audio playback of audio data from the control panel.

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.

Methods, systems, computer-readable media, and apparatuses for processing alarm signals are presented. In some embodiments, a mobile device may be registered with a security system that is installed at a premises. Subsequently, an alarm trigger associated with the security system may be received. Based on receiving the alarm trigger, the location of the mobile device may be determined. A response to the alarm trigger then may be determined based on the location of the mobile device.

Embodiments of a central security monitoring device for reducing incidences of false alarms in a security system is disclosed. In one embodiment, a method is described, comprising receiving an alarm signal from an occupancy sensor via a receiver, receiving a second alarm signal from a barrier alarm device after receiving the alarm signal, determining, by a processor, an elapsed time from when the alarm signal from the occupancy sensor was received to when the second alarm signal from the barrier alarm device was received, transmitting, by the processor via a network interface, a message to a personal communication device indicating that a false alarm has occurred when the elapsed time is less than the predetermined time.

A method and apparatus for monitoring a door or a window is disclosed. In one embodiment, a method is described, comprising receiving, by a processor, an electronic signal from a motion sensor in response to movement of the door or window, determining a direction of movement of the door or window from the electronic signal by the processor, comparing the direction of movement to a predetermined direction by the processor, detecting, by the processor, an alarm condition of the door or window if the electronic signal indicates that the door or window is being opened, and transmitting, by a transmitter coupled to the processor, an alarm signal when the alarm condition has been detected.

A method may include receiving an event message from a home security edge device, including image data. The method may include determining whether the image data represents a false trigger event based on inputting the image data into an artificial intelligence model and/or receiving a user input. The user input may be responsive to a presentation of the image data. If the image data represents the false trigger event, the method may include generating training data for retraining the artificial model. The training data may include a portion of the image data. The method may include updating a local dataset to include the training data and training the artificial intelligence model. The method may include transmitting the training data to a central database. If the image data does not represent a false trigger event, the method may include providing a security alert for display on one or more user devices.

A method may include receiving an event message from a home security edge device, including image data. The method may include determining whether the image data represents a false trigger event based on inputting the image data into an artificial intelligence model and/or receiving a user input. The user input may be responsive to a presentation of the image data. If the image data represents the false trigger event, the method may include generating training data for retraining the artificial model. The training data may include a portion of the image data. The method may include updating a local dataset to include the training data and training the artificial intelligence model. The method may include transmitting the training data to a central database. If the image data does not represent a false trigger event, the method may include providing a security alert for display on one or more user devices.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for reduction of false detections using an ultrasound emitter. One of the methods includes obtaining sensor data captured by a sensor of a property monitoring system; detecting an object represented by the sensor data; determining that the object represented by the sensor data is likely a non-object of interest and being detected as an object of interest; and in response to determining that the object represented by the sensor data is likely the non-object of interest and being detected as the object of interest, sending, to an ultrasound emitter, a command to cause the ultrasound emitter to emit ultrasonic sound around the sensor.

A security system of a building includes a processing circuit. The processing circuit is configured to detect, based on data of security equipment of the building, that a security alarm of the building is a false alarm and search, responsive to the detection of the false alarm, a database to identify a past corrective action accepted for implementation and at least one false alarm occurring after the past corrective action was accepted and before detection of the false alarm. The processing circuits is configured to generate a corrective action to reduce an occurrence of the false alarm based on a result of the search and implement the corrective action to update operation of the security equipment to reduce the occurrence of the false alarm.

A method and system for cross-verification of alarms in real-time comprising identifying primary variables and secondary variables causing the event, labelling the primary variables and the secondary variables by primary engine and secondary engine based on Artificial Intelligence based predictive model building, predicting the labels by one or more inference engine based on previous history and data patterns, triggering secondary engine for cross-verification of alarms whenever there is a prediction from the primary engine, identifying the correlation between the labels from the primary engine and the secondary engine by validation engine, identifying alarm type based on correlation, recommending predictive maintenance and displaying on dashboard the cross-verification status of the alarms. The method reduces misclassification of alarm types based on predictive or preventive maintenance, reduces the maintenance costs of assets, and helps in prioritizing the critical alarms based on the alert type.