Identifying and automating a device type using image data

Abstract

Techniques for identifying a type of an electronic device using image data corresponding to the electronic device are provided. For example, a method may include receiving image data and textual data corresponding to an electronic device. The image data and textual data may be analyzed, and a type of the electronic device can be identified based on the analysis. Usage data associated with other electronic devices of the same type may be analyzed, and further processing may be performed based on the analysis of the usage data. In some embodiments, the further processing may include transmitting a message to a user device, the message including content related to usage of the electronic device.

1 . (canceled) 
     
     
         2 . A system comprising:
 one or more processing devices; and   memory having instructions stored thereon, which when executed by the one or more processing devices, cause the one or more processing devices to perform operations comprising:
 receiving, via a network, data that is indicative of usage of plurality of electronic devices on a plurality of other networks, where:
 the plurality of electronic devices and the plurality of other networks are remote from the network; 
 the data is based on usage data that is collected as relating to the usage of the plurality of electronic devices over time; 
 the plurality of electronic devices comprises electronic devices of a first type of electronic device; 
 
 receiving image data associated with an image of an electronic device on the network, where:
 the electronic device is associated with a user, and 
 the image data was captured at an access device associated with the user; 
 
 analyzing the image data; 
 identifying a type of the electronic device based on the analysis of the image data; 
 determining that the identified type of the electronic device corresponds to the first type of electronic device; 
 using the data that is indicative of usage of the plurality of electronic devices on the plurality of other networks to determine one or more automation parameters for the type of the electronic device; and 
 applying the automation parameters to the electronic device. 
   
     
     
         3 . The system as recited in  claim 2 , where the data that is indicative of usage of the plurality of electronic devices on the plurality of other networks corresponds to one or more automation rules particularized to the first type of electronic device. 
     
     
         4 . The system as recited in  claim 2 , where the identified type of the electronic device is the first type of electronic device. 
     
     
         5 . The system as recited in  claim 2 , where the identified type of the electronic device is a second type of electronic device that is different from the first type of electronic. 
     
     
         6 . The system as recited in  claim 5 , where the data that is indicative of usage of the plurality of electronic devices on the plurality of other networks corresponds to one or more automation rules particularized to the first type of electronic device and the second type of electronic device. 
     
     
         7 . The system as recited in  claim 2 , where the one or more automation rules are selected based at least in part on a ranking of automation rules according to frequency, duration, recency, or proximity. 
     
     
         8 . The system as recited in  claim 2 , where the analyzing the image data comprising image processing and comparing at least part of the image data to other image data, and the identifying the type of the electronic device based on the analysis of the image data is based on the comparing. 
     
     
         9 . One or more non-transitory, machine-readable media having machine-readable instructions thereon which, when executed by one or more processors, cause the one or more processors to perform operations comprising:
 receiving, via a network, data that is indicative of usage of plurality of electronic devices on a plurality of other networks, where:
 the plurality of electronic devices and the plurality of other networks are remote from the network; 
 the data is based on usage data that is collected as relating to the usage of the plurality of electronic devices over time; 
 the plurality of electronic devices comprises electronic devices of a first type of electronic device; 
   receiving image data associated with an image of an electronic device on the network, where:
 the electronic device is associated with a user, and 
 the image data was captured at an access device associated with the user; 
   analyzing the image data;   identifying a type of the electronic device based on the analysis of the image data;   determining that the identified type of the electronic device corresponds to the first type of electronic device;   using the data that is indicative of usage of the plurality of electronic devices on the plurality of other networks to determine one or more automation parameters for the type of the electronic device; and   applying the automation parameters to the electronic device.   
     
     
         10 . The one or more non-transitory, machine-readable media as recited in  claim 9 , where the data that is indicative of usage of the plurality of electronic devices on the plurality of other networks corresponds to one or more automation rules particularized to the first type of electronic device. 
     
     
         11 . The one or more non-transitory, machine-readable media as recited in  claim 9 , where the identified type of the electronic device is the first type of electronic device. 
     
     
         12 . The one or more non-transitory, machine-readable media as recited in  claim 9 , where the identified type of the electronic device is a second type of electronic device that is different from the first type of electronic. 
     
     
         13 . The one or more non-transitory, machine-readable media as recited in  claim 12 , where the data that is indicative of usage of the plurality of electronic devices on the plurality of other networks corresponds to one or more automation rules particularized to the first type of electronic device and the second type of electronic device. 
     
     
         14 . The one or more non-transitory, machine-readable media as recited in  claim 9 , where the one or more automation rules are selected based at least in part on a ranking of automation rules according to frequency, duration, recency, or proximity. 
     
     
         15 . The one or more non-transitory, machine-readable media as recited in  claim 9 , where the analyzing the image data comprising image processing and comparing at least part of the image data to other image data, and the identifying the type of the electronic device based on the analysis of the image data is based on the comparing. 
     
     
         16 . A method comprising:
 receiving, at a computing device on a network, data that is indicative of usage of plurality of electronic devices on a plurality of other networks, where:
 the plurality of electronic devices and the plurality of other networks are remote from the network; 
 the data is based on usage data that is collected as relating to the usage of the plurality of electronic devices over time; 
 the plurality of electronic devices comprises electronic devices of a first type of electronic device; 
   receiving, at the computing device, image data associated with an image of an electronic device on the network, where:
 the electronic device is associated with a user, and 
 the image data was captured at an access device associated with the user; 
   analyzing the image data;   identifying a type of the electronic device based on the analysis of the image data;   determining that the identified type of the electronic device corresponds to the first type of electronic device;   using the data that is indicative of usage of the plurality of electronic devices on the plurality of other networks to determine one or more automation parameters for the type of the electronic device; and   applying the automation parameters to the electronic device.   
     
     
         17 . The method as recited in  claim 16 , where the data that is indicative of usage of the plurality of electronic devices on the plurality of other networks corresponds to one or more automation rules particularized to the first type of electronic device. 
     
     
         18 . The method as recited in  claim 16 , where the identified type of the electronic device is the first type of electronic device. 
     
     
         19 . The method as recited in  claim 16 , where the identified type of the electronic device is a second type of electronic device that is different from the first type of electronic. 
     
     
         20 . The method as recited in  claim 19 , where the data that is indicative of usage of the plurality of electronic devices on the plurality of other networks corresponds to one or more automation rules particularized to the first type of electronic device and the second type of electronic device. 
     
     
         21 . The method as recited in  claim 16 , where the one or more automation rules are selected based at least in part on a ranking of automation rules according to frequency, duration, recency, or proximity.