Abstract: Systems and methods for identifying user-customized relevant individuals in an ambient image at a doorbell device are provided. Such systems and methods can include receiving user input that includes image information, using the image information to compile a custom image database containing a plurality of images that depict such relevant individuals, and storing the custom image database in local memory of the doorbell device. Then, such systems and methods can include capturing an ambient image with a camera of the doorbell device, determining whether any person depicted in the ambient image matches any of the relevant individuals by comparing the ambient image to the plurality of images at the doorbell device, and generating an alert when any person depicted in the ambient image matches any of the relevant individuals.

Abstract: Disclosed systems and methods can include capturing the sequence of images of a monitored region that includes a sub-region of interest, processing the sequence of images using heuristics and rules of an artificial intelligence model to identify the plurality of discrete parts that are associated with a type of a unified entity, and processing the sequence of images using the heuristics and the rules of the artificial intelligence model to virtually link together a group of the plurality of discrete parts that correspond to a specific embodiment of the unified entity that is present in the sub-region of interest, wherein the heuristics and the rules of the artificial intelligence model can be developed from a training process that includes the artificial intelligence model receiving sample images delineating exemplary discrete parts on exemplary embodiments of the unified entity.

Abstract: Systems and methods for building and using a false alarm predicting model to determine whether to alert a user and/or relevant authorities about an alarm signal from a security system are provided. Such systems and methods can include a learning module receiving the alarm signal and additional information associated with the alarm signal, using the false alarm predicting model to process a combination of the alarm signal and the additional information to determine whether the combination represents a false alarm or a valid alarm, and transmitting a status signal indicative of whether the combination represents the false alarm or the valid alarm to an automated dispatcher module, and the automated dispatcher module using the status signal to automatically determine whether to alert the user and/or the relevant authorities about the alarm signal.

Abstract: Systems and methods for building and using a false alarm predicting model to determine whether to alert a user and/or relevant authorities about an alarm signal from a security system are provided. Such systems and methods can include a learning module receiving the alarm signal and additional information associated with the alarm signal, using the false alarm predicting model to process a combination of the alarm signal and the additional information to determine whether the combination represents a false alarm or a valid alarm, and transmitting a status signal indicative of whether the combination represents the false alarm or the valid alarm to an automated dispatcher module, and the automated dispatcher module using the status signal to automatically determine whether to alert the user and/or the relevant authorities about the alarm signal.

Abstract: Systems and methods for broadcasting an audio or visual alert that includes a description of features associated with a person extracted from an image captured by a camera are provided. Such systems and methods can include the camera capturing the image when the person is within a field of view of the camera and a processor receiving the image from the camera, processing the image with an artificial intelligence model to identify and extract details of the features associated with the person, and initiating a broadcast of the audio or visual alert by an alert device associated with the camera, wherein the audio or visual alert can include the description of the features associated with the person.

Abstract: Disclosed systems and methods can include capturing the sequence of images of a monitored region that includes a sub-region of interest, processing the sequence of images using heuristics and rules of an artificial intelligence model to identify the plurality of discrete parts that are associated with a type of a unified entity, and processing the sequence of images using the heuristics and the rules of the artificial intelligence model to virtually link together a group of the plurality of discrete parts that correspond to a specific embodiment of the unified entity that is present in the sub-region of interest, wherein the heuristics and the rules of the artificial intelligence model can be developed from a training process that includes the artificial intelligence model receiving sample images delineating exemplary discrete parts on exemplary embodiments of the unified entity.

Abstract: Systems and methods for converting low resolution images into high resolution images are provided and can include (1) processing a compressed version of images with a first set of heuristics and rules of an artificial intelligence model to produce an intermediate version of the images with an intermediate resolution that is greater than the compressed resolution by first enhancing the images and subsequently upscaling the images as enhanced from the compressed resolution to the intermediate resolution and (2) processing the intermediate version of the images with a second set of heuristics and rules of the artificial intelligence model to produce a final version of the images with a final resolution that is greater than the initial resolution and the intermediate resolution by first upscaling the images from the intermediate resolution to the final resolution and subsequently enhancing the images as upscaled to produce the final version of the images.

Abstract: Systems and methods for broadcasting an audio or visual alert that includes a description of features of an ambient object extracted from an image captured by a camera of a doorbell device are provided. Such systems and methods can include the camera capturing the image when the ambient object is within a field of view of the camera and a processor receiving the image from the camera, processing the image with an artificial intelligence model to identify and extract details of the features of the ambient object, and initiating a broadcast of the audio or visual alert by an alert device associated with the camera, wherein the audio or visual alert can include the description of the features of the ambient object.

Abstract: Systems and methods for building and using a false alarm predicting model to determine whether to alert a user and/or relevant authorities about an alarm signal from a security system are provided. Such systems and methods can include a learning module receiving the alarm signal and additional information associated with the alarm signal, using the false alarm predicting model to process a combination of the alarm signal and the additional information to determine whether the combination represents a false alarm or a valid alarm, and transmitting a status signal indicative of whether the combination represents the false alarm or the valid alarm to an automated dispatcher module, and the automated dispatcher module using the status signal to automatically determine whether to alert the user and/or the relevant authorities about the alarm signal.

Abstract: Disclosed systems and methods can include capturing the sequence of images of a monitored region that includes a sub-region of interest, processing the sequence of images using heuristics and rules of an artificial intelligence model to identify the plurality of discrete parts that are associated with a type of a unified entity, and processing the sequence of images using the heuristics and the rules of the artificial intelligence model to virtually link together a group of the plurality of discrete parts that correspond to a specific embodiment of the unified entity that is present in the sub-region of interest, wherein the heuristics and the rules of the artificial intelligence model can be developed from a training process that includes the artificial intelligence model receiving sample images delineating exemplary discrete parts on exemplary embodiments of the unified entity.

Abstract: Systems and methods for building and using a false alarm predicting model to determine whether to alert a user and/or relevant authorities about an alarm signal from a security system are provided. Such systems and methods can include a learning module receiving the alarm signal and additional information associated with the alarm signal, using the false alarm predicting model to process a combination of the alarm signal and the additional information to determine whether the combination represents a false alarm or a valid alarm, and transmitting a status signal indicative of whether the combination represents the false alarm or the valid alarm to an automated dispatcher module, and the automated dispatcher module using the status signal to automatically determine whether to alert the user and/or the relevant authorities about the alarm signal.

Abstract: Disclosed systems and methods can include capturing the sequence of images of a monitored region that includes a sub-region of interest, processing the sequence of images using heuristics and rules of an artificial intelligence model to identify the plurality of discrete parts that are associated with a type of a unified entity, and processing the sequence of images using the heuristics and the rules of the artificial intelligence model to virtually link together a group of the plurality of discrete parts that correspond to a specific embodiment of the unified entity that is present in the sub-region of interest, wherein the heuristics and the rules of the artificial intelligence model can be developed from a training process that includes the artificial intelligence model receiving sample images delineating exemplary discrete parts on exemplary embodiments of the unified entity.

Abstract: Systems and methods for identifying user-customized relevant individuals in an ambient image at a doorbell device are provided. Such systems and methods can include receiving user input that includes image information, using the image information to compile a custom image database containing a plurality of images that depict such relevant individuals, and storing the custom image database in local memory of the doorbell device. Then, such systems and methods can include capturing an ambient image with a camera of the doorbell device, determining whether any person depicted in the ambient image matches any of the relevant individuals by comparing the ambient image to the plurality of images at the doorbell device, and generating an alert when any person depicted in the ambient image matches any of the relevant individuals.

Abstract: Systems and methods for broadcasting an audio or visual alert that includes a description of features of an ambient object extracted from an image captured by a camera of a doorbell device are provided. Such systems and methods can include the camera capturing the image when the ambient object is within a field of view of the camera and a processor receiving the image from the camera, processing the image with an artificial intelligence model to identify and extract details of the features of the ambient object, and initiating a broadcast of the audio or visual alert by an alert device associated with the camera, wherein the audio or visual alert can include the description of the features of the ambient object.

Abstract: Systems and methods for converting low resolution images into high resolution images are provided and can include (1) processing a compressed version of images with a first set of heuristics and rules of an artificial intelligence model to produce an intermediate version of the images with an intermediate resolution that is greater than the compressed resolution by first enhancing the images and subsequently upscaling the images as enhanced from the compressed resolution to the intermediate resolution and (2) processing the intermediate version of the images with a second set of heuristics and rules of the artificial intelligence model to produce a final version of the images with a final resolution that is greater than the initial resolution and the intermediate resolution by first upscaing the images from the intermediate resolution to the final resolution and subsequently enhancing the images as upscaled to produce the final version of the images.

Abstract: Systems and methods for building and using a false alarm predicting model to determine whether to alert a user and/or relevant authorities about an alarm signal from a security system are provided. Such systems and methods can include a learning module receiving the alarm signal and additional information associated with the alarm signal, using the false alarm predicting model to process a combination of the alarm signal and the additional information to determine whether the combination represents a false alarm or a valid alarm, and transmitting a status signal indicative of whether the combination represents the false alarm or the valid alarm to an automated dispatcher module, and the automated dispatcher module using the status signal to automatically determine whether to alert the user and/or the relevant authorities about the alarm signal.

Abstract: Systems and methods for building and using a false alarm predicting model to determine whether to alert a user and/or relevant authorities about an alarm signal from a security system are provided. Such systems and methods can include a learning module receiving the alarm signal and additional information associated with the alarm signal, using the false alarm predicting model to process a combination of the alarm signal and the additional information to determine whether the combination represents a false alarm or a valid alarm, and transmitting a status signal indicative of whether the combination represents the false alarm or the valid alarm to an automated dispatcher module, and the automated dispatcher module using the status signal to automatically determine whether to alert the user and/or the relevant authorities about the alarm signal.