Methods, systems, and apparatus, including computer programs encoded on a storage device, for monitoring a property using drone beacons. In one aspect, a monitoring system is disclosed that includes a drone, a drone beacon, a component, a processor, and a computer storage media storing instructions that, when executed by the processor, cause the processor to perform operations. The operations may include obtaining drone beacon data generated by the drone beacon, determining a location of the drone beacon based on the drone beacon data, after determining the location of the drone beacon, transmitting, to the drone, a first instruction to navigate towards the location of the drone beacon, after deploying the drone, obtaining component data generated by the component, and after obtaining the component data, transmitting, to the drone, a second instruction to navigate towards a different location than the location of the drone beacon based on the component data.

A UAV data processing and management system is provided including an encoder broadcaster and data manager which provides end users with a single interface for searching and sharing any video or imagery source, from any device with no client software required. Data inputs to the resource can include UAV video, photos, traffic cameras, fixed surveillance systems, iOS and Android device pictures, and other data (e.g., texts, emails) and inputs from all forms of social media, such as Twitter, Instagram, Facebook, etc. The cloud based manager is built with collaboration and sharing in mind while at the same time maintaining data privacy, security protection, chain-of-custody control and audit trail maintenance. Analytic tools are integrated accordingly as “plug-ins” or as a store of available app resources which are easily removed, added and customized based on user needs and system requirements and cost constraints.

Systems and methods for geofence information delivery are disclosed. A multiplicity of devices constructed and configured in network communication in a region of interest via a peer-to-peer network. The multiplicity of devices store cached geofence information for the region of interest. The multiplicity of devices on the peer-to-peer network are operable to convert between an IP address and a geographic location. Each of the multiplicity of devices is operable to query peer devices on the peer-to-peer network for geofences associated with an IP address or a geographic location. At least one peer device is operable to deliver one or more geofences associated with the IP address to the querying device via zero-configuration networking or web service.

Techniques are described for detecting and handling unauthenticated commands in a property monitoring system. In some implementations, a monitoring system may include sensors located throughout a property, a monitoring control unit, and an input device. The monitoring control unit may be configured to receive data collected by the sensors, as well as an input command detected by the input device. For an input command that does not include authentication information, the monitoring control unit may generate property state information based on the sensor data, then analyze the property state data and the input command against one or more rules that relate to authorization of unauthenticated commands. Based on the analysis, the monitoring control unit may determine whether to perform the action corresponding to the input command or whether to perform another action, for example, generating and providing a notification or authorization request to a user.

A method for facial analytics includes capturing a series of images of individuals from a camera into a circular buffer and selecting a plurality of images from the buffer for analysis in response to a trigger event, wherein the plurality of images are chronologically proximate before and/or after the trigger event in time. The method includes analyzing the plurality of images to determine image quality and selecting one of the plurality of images based on image quality to form a cropped facial image most likely to result in positive facial recognition matching. Methods of signaling to control the pedestrian traffic flow can maximize the individuals' facial alignment to the capturing camera's field of view. Non-relevant facial images associated with individuals outside a given region of interest can be discarded. Facial recognition is run on the resultant cropped facial image. Output can be displayed with information from the facial recognition.

Methods, systems, and apparatus, including computer programs encoded on a storage device, for using a drone to test monitoring system sensors. In one aspect, the drone perform operations that include navigating from a first location of a property towards a second location of the property, detecting a sensor that is installed at the property, interrupting, by the drone, navigation through the property from the first location of the property towards the second location of the property to initiate a test of the detected sensor and (ii) determining a sensor test type for the detected sensor, administering a sensor test to the detected sensor, wherein the sensor test is based on the determined sensor test type, evaluating results of the administered test, storing data describing the results of the administered test, and continuing navigation through the property towards the second location of the property or towards another location of the property.

Methods, systems, and apparatus, including computer programs encoded on a storage device, for using a drone to pre-surveil a portion of a property. In one aspect, a system may include a monitoring unit. The monitoring unit may include a network interface, a processor, and a storage device that includes instructions to cause the processor to perform operations. The operations may include obtaining data that is indicative of one or more acts of an occupant of the property, applying the obtained data that is indicative of one or more acts of the occupant of the property to a pre-surveillance rule, determining that the pre-surveillance rule is satisfied, determining a drone navigation path that is associated with the pre-surveillance rule, transmitting, to a drone, an instruction to perform pre-surveillance of the portion of the one or more properties using the drone navigation path.

A distributed microphones signal server includes a network interface circuit that communicates with mobile terminals and a plurality of microphones that are geographically distributed. The server receives an audio request message containing a location of the mobile terminal, and selects a microphone from among the plurality of microphones responsive to the location of the mobile terminal. The server obtains an audio stream from the selected microphone, and communicates the audio stream to the mobile terminal. Related methods by a distributed microphones signal server are disclosed. Related computer program products and methods by a mobile terminal are disclosed.

Methods, systems, and apparatus, including computer programs encoded on a storage device, for enabling drone activity in a property monitored by a property monitoring system without triggering a false alarm. In one aspect, the method includes actions of obtaining a location of the drone, identifying a first sensor installed at the property that is within a predetermined distance of the drone, detecting first sensor data generated by the first sensor that is within a predetermined distance of the drone, wherein the first sensor data includes data that is indicative of an event, determining whether a second sensor that is mounted to the drone is generating second sensor data that corroborates the event indicated by the first sensor data, and disregarding, by the property monitoring system, the first sensor data in determining whether to trigger an alarm.

In a monitoring area such as a resort house area that a user cannot directly monitor, a vehicle owned by the user performs patrol driving to capture an image of a surrounding state and transmits the image to a user terminal and a monitoring server as imaging data. The monitoring server analyzes the imaging data transmitted from the vehicle to determine whether an abnormality occurs in the monitoring area or not, and notifies the user terminal and the vehicle of a determination result. When the vehicle receives an abnormality notice from the monitoring server, the vehicle notifies outside that the abnormality occurs by light or sound.