This document describes techniques, apparatuses, and systems for batch size adjustment using latency-critical event recognition. The techniques described herein enable an electronic device (e.g., security camera) to determine the likelihood of an event of interest (e.g., latency-critical event) occurring in data (e.g., audio and/or video) captured by the electronic device. To make such a determination, the electronic device may switch upload modes to upload the data, using a different batch size to reduce latency, to another device for user access, based on the likelihood of an event of interest occurring in the data. In this way, the techniques, apparatuses, and systems for batch size adjustment using latency-critical event recognition provide an efficient way to provide all-day security monitoring.

Methods, systems, and apparatus, including computer programs encoded on a storage device, for using a drone to monitor a community. The drone may include a processor and a storage device storing instructions that, when executed by the processor, cause the one or more processors to perform operations. The operations may include receiving an instruction to deploy based on a determination, by a community monitoring system that an event was detected at a property of the community, navigating towards the property along an initial navigation path, obtaining local monitoring system data from a local monitoring system of a property of the community, generating based on the local monitoring system data a navigational model that identifies a location of each of one or more surveillance objectives, determining an adjusted navigation path to a location of a surveillance objective of the one or more surveillance objectives, and navigating along the adjusted navigation path.

Described herein are systems and methods for generating a watch list of users who pose specific security threats to a store. The method can include retrieving, by a computer system from a data store, case files that document activity that poses a security threat by a user at the store, predicting, based on applying prediction models to the case files, future activity associated with the case files, determining threat scores for the case files based on the predicted future activity, ranking the case files into a candidate list from highest to lowest threat score, generating a watch list for the store that includes a subset of the ranked case files based on which case files pose a greatest current threat to the store, generating summary videos for each case file in the watch list, and transmitting the watch list and summary videos to a user device.

An analytical recognition system includes a video camera, an antenna, and a data analytics module. The video camera is configured to capture video data. In some embodiments, the video camera is at least one of a traffic camera or an aerial drone camera. The antenna is configured to capture mobile communication device data. The data analytics module is configured to correlate the video data and the mobile communication device data to generate a profile of a person associated with the video data and the mobile communication device data. The profile has profile data including any one or a combination of the captured video data and the captured mobile communication device data.

A gateway of a surveillance system, the gateway includes: a communication module configured to communicate with a plurality of network cameras including a first network camera and a second network camera; and a processor configured to recognize a motion of a subject based on event information transmitted by the first network camera and to transmit subject information generated based on the motion of the subject to the second network camera.

An event of interest may be tracked using a distributed intelligence video surveillance system. The distributed intelligence video surveillance system includes a lead video camera and a plurality of child video cameras that are configured to communicate with the lead video camera. One of the plurality of child video cameras may receive a video image and perform analytics and event generation for any events of interest found within the video image. The child video camera extracts metadata for any found events of interest and communicates the extracted metadata to the lead video camera. The lead video camera communicates the extracted metadata to others of the plurality of child video cameras so that the others of the plurality of child video cameras can be alerted to track the found events of interest.

In a monitoring system, the management device causes a display device to display an image generated by capturing by the camera whose direction has been controlled; accepts designation of at least one tracking target, the at least one tracking target being designated from among moving objects in the displayed image by an operator; and performs tracking control comprising controlling a photographing range of the camera in such a way that the designated at least one tracking target is kept captured by the camera.

Parcel theft deterrence for audio/video (A/V) recording and communication devices, such as video doorbells and security cameras. When an A/V recording and communication device captures image data that includes a parcel, a parcel boundary may be created for monitoring the parcel within. In various embodiments, when the parcel is removed from the parcel boundary, a user alert may be generated to notify a user of a client device associated with the A/V recording and communication device that the parcel has been removed.

A first camera and a second camera are installed in a facility. An analyzing apparatus detects the same person from a first captured image generated by the first camera and a second captured image generated by the second camera. The analyzing apparatus computes a movement time which is required for the detected person to move between a captured area of the first camera and a captured area of the second camera. The analyzing apparatus determines an attributed of the person using at least one of the first captured image and the second captured image. The analyzing apparatus acquires a reference value corresponding to the determined attribute, compares the computed movement time with the acquired reference value, and outputs output information based on a result of the comparison.

One or more computing devices, systems, and/or methods are provided. One or more first signals received from one or more first devices may be monitored. One or more first threat indicators within a first signal of the one or more first signals may be detected. One or more second signals may be analyzed to determine a probability of a threat event. One or more second devices of a plurality of devices may be selected, based upon the probability, for transmission of one or more messages associated with the threat event.