Abstract: A computing system is described. The computing system is configured to receive, from a portal device of a premises monitoring system, a first request for a list of compatible pipelines for a premises analytics device of the premises monitoring system, identify a plurality of pipelines that are compatible with the premises analytics device based on a parameter, and transmit the list of compatible pipelines to the portal device. The computing system is further configured to receive, from the portal device, a second request to deploy a user selected pipeline of the plurality of pipelines referenced in the list of compatible pipelines, transmit a command, to a third-party system, to obtain a pipeline deployment based on the user selected pipeline, and receive, from the third-party system, the pipeline deployment based on the user selected pipeline. The pipeline deployment is transmitted to the premises analytics device.

Abstract: A control device in a premises security system for a premises is provided. The control device is configured to receive video surveillance data associated with an area of the premises, identify, using at least one machine learning model, a triggering event based at least in part on the video surveillance data, identify, using the at least one machine learning model, and based at least in part on the video surveillance data, a person associated with the triggering event, identify, using the at least one machine learning model, at least one characteristic of the person associated with the triggering event, generate an audio message comprising content based at least in part on the at least one characteristic of the person associated with the triggering event, and cause playback of the audio message in the area of the premises.

Abstract: A management node is described. A method implemented in a management node configured for training and testing one or more machine learning (ML) models. The method comprises training a first ML model using a plurality of image modalities as training data. The plurality of image modalities comprises a first image modality and a second image modality different from the first image modality. The first image modality has a first image modality parameter and the second image modality has a second image modality parameter. The method further includes modifying one or both of the first image modality parameter and the second image modality parameter, training a second ML model using the plurality of image modalities and the modified one or both of the first image modality parameter and the second image modality parameter, and testing the first ML model and the second ML model based on an accuracy threshold.

Abstract: A management node is described. A method implemented in a management node is described. The method comprises receiving a video segment and selecting a plurality of subsegments of the video segment based on a selection criteria. The selection criteria comprise rules based on at least one of a selection characteristic, a subsegment characteristic, a video segment characteristic, or a system characteristic. The method further includes training a machine learning (ML) model using the plurality of subsegments selected based on the selection criteria.

Abstract: A computing system is described. The computing system is configured to receive, from a portal device of a premises monitoring system, a first request for a list of compatible pipelines for a premises analytics device of the premises monitoring system, identify a plurality of pipelines that are compatible with the premises analytics device based on a parameter, and transmit the list of compatible pipelines to the portal device. The computing system is further configured to receive, from the portal device, a second request to deploy a user selected pipeline of the plurality of pipelines referenced in the list of compatible pipelines, transmit a command, to a third-party system, to obtain a pipeline deployment based on the user selected pipeline, and receive, from the third-party system, the pipeline deployment based on the user selected pipeline. The pipeline deployment is transmitted to the premises analytics device.

Abstract: A computing system is described. The computing system is configured to receive, from a portal device of a premises monitoring system, a first request for a list of compatible pipelines for a premises analytics device of the premises monitoring system, identify a plurality of pipelines that are compatible with the premises analytics device based on a parameter, and transmit the list of compatible pipelines to the portal device. The computing system is further configured to receive, from the portal device, a second request to deploy a user selected pipeline of the plurality of pipelines referenced in the list of compatible pipelines, transmit a command, to a third-party system, to obtain a pipeline deployment based on the user selected pipeline, and receive, from the third-party system, the pipeline deployment based on the user selected pipeline. The pipeline deployment is transmitted to the premises analytics device.

Abstract: A control device in a premises security system for a premises is provided. The control device is configured to receive video surveillance data associated with an area of the premises, identify, using at least one machine learning model, a triggering event based at least in part on the video surveillance data, identify, using the at least one machine learning model, and based at least in part on the video surveillance data, a person associated with the triggering event, identify, using the at least one machine learning model, at least one characteristic of the person associated with the triggering event, generate an audio message comprising content based at least in part on the at least one characteristic of the person associated with the triggering event, and cause playback of the audio message in the area of the premises.