A system and method may detect one or more shooting sounds and provide guidance to one or more evacuating people when an active shooting event has occurred indoors, thereby minimizing a secondary damage. The system comprises: a plurality of stations configured to detect one or more shooting sounds and transmit detection of the one or more shooting sounds; and a response server configured to receive the detection of one or more shooting sounds over a communication network, to generate action commands, respectively corresponding to each of the stations, based on the detection of the one or more shooting sounds, and to transmit the respective action commands to the each of the corresponding stations over the communication network.

Various aspects of the disclosure relate to monitoring a physical location to determine and/or predict anomalous activities. One or more machine learning algorithms may be used to analyze inputs from one or more sensors, cameras, audio recording equipment, and/or any other types of sensors to detect anomalous measurements/patterns. Notifications may be sent one or more devices in a network based on the detection.

The present disclosure is the only product of its kind that incorporates an advanced technology in keeper boxes to enhance protection protocols and sale security in retail locations. This disclosed product is uniquely designed with durable materials to ensure sustainability and a sound alarm to notify authorities and/or near by staff securities, if the device is being moved, tampered with or broken into, immediately. The disclosure includes an electronic security box made of a metal and comprising five contiguous sides and defining an open sixth side. The disclosure also includes a metal lid configured to fit the sixth side of the metal box and create an enclosure. The disclosure further includes a base configured to electronically interact with the metal lid and with the metal box via a proximity thereto.

Provided are a logistics device that is carried together with freight to detect a state, a logistics control system, and a theft prevention method of the same, wherein thee logistics device which is carried together with freight to detect a state includes a body carried together with freight and a controller configured to measure a speed of the body and vibrations applied to the body and determine whether the freight is stolen using the speed and the vibrations.

In one implementation, a method for using a mobile computing device as a security system component includes receiving, from a mobile device and by a security system gateway, mobile device sensor information associated with sensor data captured by the mobile device at a premises monitored by the security system gateway; identifying, based on the received sensor information, a mobile device sensor information rule; identifying an action to perform in the mobile device sensor information rule; and automatically performing the identified action, by the security system gateway, in response to receiving the sensor information from the mobile device.

In one implementation, a method for using a mobile computing device as a security system component includes receiving, from a mobile device and by a security system gateway, mobile device sensor information associated with sensor data captured by the mobile device at a premises monitored by the security system gateway; identifying, based on the received sensor information, a mobile device sensor information rule; identifying an action to perform in the mobile device sensor information rule; and automatically performing the identified action, by the security system gateway, in response to receiving the sensor information from the mobile device.

According to some embodiments, a control device for a premises security system that is configured to monitor a premises using a plurality of premises devices is provided. The control device is configured to obtain a plurality of acoustic samples for the premises, detect a sound anomaly in at least one of the plurality of acoustic samples, obtain a verification that the sound anomaly is expected, generate an acoustic model for the premises based at least on the plurality of acoustic samples and the verification that the sound anomaly is expected, receive data representing a detected sound during monitoring of the premises, compare the detected sound with the acoustic model for the premises to determine that the detected sound is unexpected, and initiate a premises security system alert based at least on the detected sound being unexpected.

An exemplary method and system is disclosed that facilitates a readily-re-deployable and self-enclosed geofencing and proximity-based intrusion sensing and alerting system in a roadway or construction work zone. The sensing and alerting system is configured in the form factor of a safety cone, barricade or drum to sense and uses acoustic-echoes or LiDAR-based sensing to detect intruders that are in proximity to the sensing and alerting system to generate a siren or loud audible alert, as well as flashing lights, to warn workers of such intrusion.

Various aspects of the disclosure relate to monitoring a physical location to determine and/or predict anomalous activities. One or more machine learning algorithms may be used to analyze inputs from one or more sensors, cameras, audio recording equipment, and/or any other types of sensors to detect anomalous measurements/patterns. Notifications may be sent one or more devices in a network based on the detection.

Various aspects of the disclosure relate to monitoring a physical location to determine and/or predict anomalous activities. One or more machine learning algorithms may be used to analyze inputs from one or more sensors, cameras, audio recording equipment, and/or any other types of sensors to detect anomalous measurements/patterns. Notifications may be sent one or more devices in a network based on the detection.