The present disclosure describes a system and method designed to protect the contents of a region or space within a facility (e.g., building, home, vehicle, outdoor space, etc.). The system is configured to identify an area to be protected (e.g., nightstand, medicine cabinet, safe), monitor surroundings, and manage and deploy response(s) to threats to the region or space under protection. The system may also be configured to provide incremental warnings, interventions, or countermeasures to deter people or animals from accessing the Protected Space.

Systems and methods for alerting personnel (e.g., workers, emergency responders, pedestrians, observers, etc.) that a vehicle (e.g., car, truck, watercraft, etc.) has entered into, or crossed a boundary of, a protected area or zone.

Systems and methods for alerting personnel (e.g., workers, emergency responders, pedestrians, observers, etc.) that a vehicle (e.g., car, truck, watercraft, etc.) has entered into, or crossed a boundary of, a protected area or zone.

A vehicle theft-prevention apparatus can include at least one computing device couple to a plurality of sensors and a wireless transceiver. The plurality of sensors can be configured to sense measurements proximate to a vehicle. The at least one computing device can be configured to read a plurality of first measurements of a first sensor of the plurality of sensors. Based on the plurality of first measurements from the first sensor, the at least one computing device can determine that a key fob moved outside of a range of the first sensor. In response to the key fob moving outside of the range of the first sensor, the at least one computing device can transition to an armed state. The at least one computing device can read a plurality of second measurements from a subset of the plurality of sensors. Based on the plurality of second measurements, the at least one computing device can determine that a person has entered the vehicle.

An information processing program causes a computer to execute a process including: specifying, from an image that is captured by a camera, a person and a plurality of objects, generating, by inputting the image of the person into a machine learning model, skeleton information on the person, identifying, based on the plurality of objects and the skeleton information, a first feature value associated with one or more first motions of the person who retrieves an object from among the plurality of objects, identifying a second feature value associated with one or more objects registered to a first terminal by the person from among the plurality of object, and generating, based on a difference between the first feature value and the second feature value, an alert indicates that an object retrieved by the person is not registered in the first terminal.

A system and method for intelligently evaluating and automatically mitigating detected security activities includes implementing an on-premise security device that detects a potential security activity at a property of a subscriber; establishing a security channel between the on-premise security device and a remote machine learning-based security module operating in a cloud computing environment if the potential security activity satisfies escalation criteria; automatically transmitting, via the security channel, sensor data from the on-premise security device to the remote machine learning-based security module; computing, by the remote machine learning-based security module, a threat severity inference based on the sensor data; deriving device control instructions based on the threat severity inference; transmitting, via the security channel, the device control instructions to the on-premise security device; and mitigating the potential security activity by executing the device control instructions at the on-premise device.

A system and method for intelligently evaluating and automatically mitigating detected security activities includes implementing an on-premise security device that detects a potential security activity at a property of a subscriber; establishing a security channel between the on-premise security device and a remote machine learning-based security module operating in a cloud computing environment if the potential security activity satisfies escalation criteria; automatically transmitting, via the security channel, sensor data from the on-premise security device to the remote machine learning-based security module; computing, by the remote machine learning-based security module, a threat severity inference based on the sensor data; deriving device control instructions based on the threat severity inference; transmitting, via the security channel, the device control instructions to the on-premise security device; and mitigating the potential security activity by executing the device control instructions at the on-premise device.

Methods and systems for managing a premises are disclosed. The premises may comprise a premises management device. The premises management device may be in communication with a security system. The premises management device may manage consumption by maintaining or disabling components associated with the premise management device.

Methods and systems for managing a premises are disclosed. The premises may comprise a premises management device. The premises management device may be in communication with a security system. The premises management device may manage consumption by maintaining or disabling components associated with the premise management device.

A system is provided that includes a computer implemented method for the automated purchasing of a security system having a plurality of security equipment components for use and installation on a unique geo-coordinate referenced location (i.e., a property). The system also includes a computer implemented method for installing the security equipment on the property that was purchased using the automated purchasing system.