Patent Publication Number: US-2021182931-A1

Title: Automatic ordering of consumable items

Description:
TECHNICAL FIELD 
     Embodiments of the present disclosure relate generally to automatically ordering consumable items for an account, but not by way of limitation, to generating an enhanced user interface for displaying an automatically placed order for a consumable item and for specification of a schedule of future automatic orders for the consumable item. 
     BACKGROUND 
     Consumable items, such as milk, vegetables, cereal, chips, or cans of soda. are consumed at various rates or purchased in various amounts by different people or families. Currently, certain e-commerce operators provide subscription services to user who would like to periodically purchase goods from these e-commerce operators. The subscription services offered by these e-commerce operators allow user to set up recurring orders for various consumable items. For example, a user may purchase, via a subscription, vitamins every three months, or milk every week. 
     Unfortunately, such subscription services require a lot of interaction by the user with the e-commerce operator&#39;s platform when the user would like to modify or cancel orders or subscriptions. For example, when the user is on vacation or does not consume a product, the user has to log into the e-commerce operator&#39;s system and cancel the order or change the subscription for the product. These required interactions by the user with the e-commerce operator&#39;s system are time consuming for the user. In addition, these user interactions increase the demand for data storage and diminish data processing speeds of the e-commerce operator&#39;s system. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Various ones of the appended drawings merely illustrate example embodiments of the present disclosure and cannot be considered as limiting its scope. 
         FIG. 1  is a block diagram illustrating a networked system, according to some example embodiments. 
         FIG. 2  illustrates user interfaces for displaying automatically placed orders for consumable items, according to some example embodiments. 
         FIG. 3  is a block diagram illustrating components of an item ordering system, according to some example embodiments. 
         FIG. 4  is a flow diagram illustrating a method for automatically placing an order for a consumable item, according to some example embodiments. 
         FIG. 5  is a flow diagram illustrating a method for automatically placing an order for a consumable item representing additional steps of the method illustrated in  FIG. 4 , and representing step  410  of the method illustrated in  FIG. 4  in more detail, according to some example embodiments. 
         FIG. 6  is a flow diagram illustrating a method for automatically placing an order for a consumable item, representing an additional step of the method illustrated in  FIG. 4 , and representing step  410  of the method illustrated in  FIG. 4  in more detail, according to some example embodiments. 
         FIG. 7  is a block diagram illustrating an example of a software architecture that may be installed on a machine, according to some example embodiments. 
         FIG. 8  illustrates a diagrammatic representation of a machine in the form of a computer system within which a set of instructions may be executed for causing the machine to perform any one or more of the methodologies discussed herein, according to an example embodiment. 
     
    
    
     The headings provided herein are merely for convenience and do not necessarily affect the scope or meaning of the terms used. 
     DETAILED DESCRIPTION 
     The description that follows includes systems, methods, techniques, instruction sequences, and computing machine program products that embody illustrative embodiments of the disclosure. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide an understanding of various embodiments of the inventive subject matter. It will be evident, however, to those skilled in the art, that embodiments of the inventive subject matter may be practiced without these specific details. In general, well-known instruction instances, protocols, structures, and techniques are not necessarily shown in detail. 
     According to some example embodiments, an item ordering system that automatically identifies a level of consumption of a consumable item, for an account, and, based on the level of consumption, automatically orders the consumable items for the account provides a technical solution to the technical problems of increased demand for data storage and diminished data processing speeds faced by the e-commerce systems that currently provide subscription services for consumable items. The item ordering system accesses (e.g., receives or obtains) image input associated with a consumable item. The image input may be accessed from a client device associated with a user or an account that represents the user. In some example embodiments, the client device is a computer associated with the user or the account. In various example embodiments, the client device is a smart appliance (e.g., a refrigerator) associated with the user or the account. 
     A consumable item may be a commodity that is intended to be used relatively quickly, such as milk, soda, bread, cereal, or vegetables. The image input may include at least one of a video or a photograph. The image input may be recorded by a camera associated with the client device. For example, a camera installed in the kitchen of a user (e.g., in the refrigerator or in a pantry) captures photographic images or records video of the inside of a food storage location (e.g., a refrigerator, a pantry, or a kitchen cabinet) at various times or continuously. The camera may transmit, via a client device, the captured image input to the item ordering system. In some instances, the camera is included in (e.g., is part of) the client device. 
     The item ordering system identifies an account based on an identifier of the client device, and determines a level of consumption of the consumable item for the account based on the image input. The item ordering system may utilize image analysis and image recognition techniques to determine the level of consumption of the consumable item. 
     Based on the level of consumption of the consumable item, the item ordering system automatically places an order for the consumable item, for the account. In some example embodiments, the user associated with the account, when setting up the account, provides permission to the item ordering system to place automatic orders for consumable items, for the account, based on a determination, by the item ordering system, that the consumable item should be reordered. In some example embodiments, the item ordering system  300  allows the user to preview the order before the order for the consumable item is placed. The preview can be in the form of a Short Message Service (SMS) message, email message, or some other type of notification. Once the user approves the order, the item ordering system  300  places the order. The item ordering system  300  may also give the user a selectable option, in the user interface, to request that the item ordering system  300  stop asking the user to preview future orders and instead proceed with automatic ordering of consumable items. 
     The item ordering system, in response to the automatic placing of the order for the consumable item, causes display of a notification describing the automatically placed order for the consumable item in a user interface of the client device associated with the account. A selection, by the user associated with the account, of the notification describing the automatically placed order for the consumable item enhances (e.g., improves or updates) the user interface to display an automatically generated request to specify a schedule of future automatic orders for the consumable item. The schedule of future automatic orders may be automatically generated by the item ordering system based on a pattern of consumption of the consumable item by the users associated with the account (e.g., the user or the family represented by the account), and may be displayed in the enhanced user interface. The item ordering system may determine the pattern of consumption of the consumable items based on analysis of image input associated with the consumable item over a period of time, and may predict future consumption of the consumable item for the account using machine learning techniques. 
     In some example embodiments, after the item ordering system places automatic orders for a plurality of consumable items located in a plurality of locations (e.g., a first consumable item is stored in the refrigerator and a second consumable item is stored in the kitchen pantry), the item ordering system displays the orders for the plurality of consumable items merged on a single page presented in the notification. In certain example embodiments, after the item ordering system places automatic orders for a plurality of consumable items located in a plurality of locations, the item ordering system displays the orders for the plurality of consumable items in a paginated form on multiple pages presented in the notification. In some example embodiments, the item ordering system provides metrics of user consumption of the consumable items to sellers of the consumable items. For example, the metrics of the level of consumption of milk in a geographic area over a period of time may be presented in a report or a dashboard displayed in a client device associated with a seller of milk. The report or dashboard may help sellers manage their inventories of consumable items, project sales of the consumable items, and make accurate orders from wholesalers. 
     In some example embodiments, the item ordering system, based on determined levels of consumption of a consumable item by users in a certain geographic area and based on consumer item purchase data associated with a seller, predicts a number of consumable items that may be purchased from the seller within a period of time. The item ordering system may cause the display, via a user interface of a client device associated with the seller, of a dashboard that illustrates a pattern of use or a pattern of purchase of the consumable item over a period of time by one or more users. For example, the dashboard may indicate that buyers tend to buy more milk on the weekend. Based on knowledge of patterns of purchase or patterns of use, a seller may provide incentives to buyers to persuade the buyers to purchase milk from the seller. 
     According to another example, the dashboard includes a communication to the seller, such as “Our system predicts that X gallons of milk may be purchased from you in the next fifteen days.” The item ordering system may also generate and display, in the dashboard, a graph of past or predicted cumulative user consumption of the consumable item, or a graph of potential orders over a particular period of time for the seller or for the market in the geographic area (e.g., all sellers of the consumable item in San Jose, Calif.). For example, one or more graphs displayed in the dashboard indicate that fifty gallons of milk were purchased from a first seller, and that the market in the geographic area is five hundred gallons. 
     Conventional user interfaces have many deficits relating to the efficient functioning of the computer, requiring a user of a conventional user interface to scroll around and switch views many times to find the right data associated with an item, especially when the conventional user interface is displayed on a small screen. Because small screens tend to need data and functionality divided into many layers or views, conventional user interfaces require users to drill down through many layers to get to desired data or functionality. That process can seem slow, complex, and difficult to learn, particularly to novice users. Further, that process decreases data processing speeds, and is often associated with higher data storage requirements. 
     In some example embodiments, an item ordering system that provides a notification describing the automatically placed order for the consumable item in the user interface of the client device associated with the account improves conventional user interfaces by identifying and presenting missing consumable items in the user interface, and presenting an option to specify or modify a schedule of future automatic orders for the consumable item according to a recommendation generated based on an automatically determined pattern of consumption of the consumable item by the user associated with the account. The providing of the notification describing the automatically placed order for the consumable item also enhances the efficiency of electronic devices by improving data processing speeds and data storage efficiency. 
     With reference to  FIG. 1 , an example embodiment of a high-level client-server-based network architecture  100  is shown. A networked system  102  provides server-side functionality via a network  104  (e.g., the Internet or wide area network (WAN)) to one or more client devices  110 .  FIG. 1  illustrates, for example, a web client  112  (e.g., a browser, such as the Internet Explorer® browser developed by Microsoft® Corporation of Redmond, Wash. State), a client application  114 , and a programmatic client  116  executing on a client device  110 . 
     The client device  110  may comprise, but is not limited to, mobile phones, desktop computers, laptops, portable digital assistants (PDAs), smart phones, tablets, ultra books, netbooks, multi-processor systems, microprocessor-based or programmable consumer electronics, game consoles, set-top boxes, wearable devices, smart watches, or any other communication devices that a user may utilize to access the networked system  102 . In some embodiments, the client device  110  may comprise a display module to display information (e.g., in the form of user interfaces). In further embodiments, the client device  110  comprises one or more of a touch screens, accelerometers, gyroscopes, cameras, microphones, global positioning system (GPS) devices, and so forth. The client device  110  is a device of a user that can be used to capture image input pertaining to consumable items that are within a storage area. In some example embodiments, the networked system  102  comprises a network-based marketplace (also referred to as “online marketplace”) that responds to requests for product listings, publishes publications comprising item listings of products or services available on the network-based marketplace, and manages payments for these marketplace transactions. One or more portions of network  104  may be an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), a metropolitan area network (MAN), a portion of the Internet, a portion of the Public Switched Telephone Network (PSTN), a cellular telephone network, a wireless network, a WiFi network, a WiMax network, another type of network, or a combination of two or more such networks. 
     The client device  110  includes one or more applications (also referred to as “apps”) such as, but not limited to, a web browser, messaging application, electronic mail (email) application, an e-commerce site application (also referred to as a marketplace application), and the like. In some embodiments, if the e-commerce site application is included in the client device  110 , then this application is configured to locally provide the user interface and at least some of the functionalities with the application configured to communicate with the networked system  102 , on an as needed basis, for data or processing capabilities not locally available (e.g., to access to a database of items available for sale, to authenticate a user, to verify a method of payment, etc.). Conversely, if the e-commerce site application is not included in the client device  110 , the client device  110  uses its web browser to access the e-commerce site (or a variant thereof) hosted on the networked system  102 . 
     One or more users  106  may be a person, a machine, or other means of interacting with the client device  110 . In example embodiments, the user  106  is not part of the network architecture  100 , but may interact with the network architecture  100  via the client device  110  or other means. For instance, the user  106  provides input (e.g., touch screen input or alphanumeric input) to the client device  110  and the input is communicated to the networked system  102  via the network  104 . In this instance, the networked system  102 , in response to receiving the input from the user  106 , communicates information to the client device  110  via the network  104  to be presented to the user  106 . In this way, the user  106  can interact with the networked system  102  using the client device  110 . 
     An application program interface (API) server  120  and a web server  122  are coupled to, and provide programmatic and web interfaces respectively to, one or more application servers  140 . The application servers  140  may host an item ordering system  300  and a payment system  144 , each of which may comprise one or more modules or applications and each of which may be embodied as hardware, software, firmware, or any combination thereof. The application servers  140  are, in turn, shown to be coupled to one or more database servers  124  that facilitate access to one or more information storage repositories or databases  126 . In an example embodiment, the databases  126  are storage devices that store information (e.g., publications, listings, digital content items, product descriptions, images of products, etc.) to be utilized by the item ordering system  300 . The databases  126  may also store digital item information, in accordance with example embodiments. 
     Additionally, a third party application  132 , executing on one or more third party servers  130 , is shown as having programmatic access to the networked system  102  via the programmatic interface provided by the API server  120 . For example, the third party application  132 , utilizing information retrieved from the networked system  102 , supports one or more features or functions on a website hosted by the third party. The third party website, for example, provides one or more promotional, marketplace, or payment functions that are supported by the relevant applications of the networked system  102 . 
     The item ordering system  300  provides a number of publication functions and services to users  106  that access the networked system  102 . For example, the item ordering system  300  facilitates the automatic ordering of consumable items for an account, and generating an enhanced user interface for displaying automatically placed orders for consumable items and for specification of schedules of future automatic orders for the consumable item. The payment system  144  provides a number of functions to perform or facilitate payments and transactions. While the item ordering system  300  and payment system  144  are shown in  FIG. 1  to both form part of the networked system  102 , it will be appreciated that, in alternative embodiments, each of the item ordering system  300  and payment system  144  may form part of a service that is separate and distinct from the networked system  102 . In some embodiments, the payment system  144  may form part of the item ordering system  300 . 
     Further, while the client-server-based network architecture  100  shown in  FIG. 1  employs a client-server architecture, the present inventive subject matter is of course not limited to such an architecture, and could equally well find application in a distributed, or peer-to-peer, architecture system, for example. The item ordering system  300  and payment system  144  could also be implemented as standalone software programs, which do not necessarily have networking capabilities. 
     The web client  112  accesses the item ordering system  300  or the payment system  144  via the web interface supported by the web server  122 . Similarly, the programmatic client  116  accesses the various services and functions provided by the item ordering system  300  or the payment system  144  via the programmatic interface provided by the API server  120 . The programmatic client  116  may, for example, be a seller application (e.g., the Turbo Lister application developed by eBay® Inc., of San Jose, Calif.) to enable sellers to author and manage listings on the networked system  102  in an off-line manner, and to perform batch-mode communications between the programmatic client  116  and the networked system  102 . 
       FIG. 2  illustrates user interfaces for displaying automatically placed orders for consumable items, according to some example embodiments. As shown in  FIG. 2 , user interface  202  displays an image input that shows a plurality of consumable items including consumable item  206  (e.g., a container of organic oats). In some example embodiments, the item ordering system  300  allows the user to provide feedback pertaining to the consumable items that are shown in the image input. For example, the user may type in comments pertaining to consumable item  206 , as shown in user interface area  208  of the user interface  202 . According to another example, the user may use his or her phone to capture the image input pertaining to the consumable item  206  while making a hand gesture of approval (e.g., a thumbs-up gesture) in association with the consumable item  206  to indicate a five-star review (or feedback) for the consumable item  206 , as shown in user interface area  208  of the user interface  202 . 
     The item ordering system  300  also allows the user to unsubscribe from a subscription for a consumable item using gestures. For example, the user may use his or her phone to capture the image input pertaining to a consumable item  210  while making another hand gesture of (e.g., a thumbs-down gesture) in association with the consumable item  210  to indicate a request to unsubscribe from automatic ordering of the consumable item  210 , as shown in user interface area  212  of the user interface  202 . In some example embodiments, if the image captures more than one consumable item, the user can indicate (e.g., on the touchscreen of his or her phone) the item they want to rate or for which they want to end a subscription. 
       FIG. 2  also shows user interface  204  that illustrates image input that shows that consumable item  206  has been detected, by the item ordering system  300 , to be missing from the location associated with the consumable item  206 , as shown in area  214  of the user interface  204 . The item ordering system  300  automatically places an order for the consumable item  206 , for the account, based on the determining that the consumable item is absent for a certain period of time (e.g., one hour or one day) from the location automatically determined to be a usual location of the consumable item, and provides a notification pertaining to the automatic placing of the order for the consumable item  206 , as shown in area  216  of the user interface  204 . 
     As shown in area  218  of the user interface  204 , the item ordering system  300  allows the user to specify a schedule of future automatic orders for the consumable item  206  by selecting the box user interface element associated with the suggested schedule of automatic ordering (e.g., monthly). Alternatively, the user may change the frequency of the future automatic orders of the consumable item  206  by clicking on the suggested schedule. In some instances, the user interface  204  allows the user to make other changes to the future automatic orders, such as specifying a different brand of the consumable item  206 . 
     Further, the user interface  204  illustrates options associated with specifying future automatic orders for a different consumable item  220  (e.g., Belgian chocolate). The item ordering system  300  allows the user to specify a schedule of future automatic orders for the consumable item  220  by selecting a box user interface element associated with the suggested schedule of automatic ordering (e.g., every two months). Alternatively, the user may change the frequency of the future automatic orders of the consumable item  220  by clicking on the suggested schedule. In some instances, the user interface  204  displays an indicator of how the consumption of a particular consumable item, by the users associated with the account, compares to the consumption of the particular consumable item, by the users associated with other accounts (e.g., “your consumption is in the 90 th  percentile range”), and a recommendation of the frequency of automatically ordering the consumable item (e.g., “a three-pack is recommended every two months”). 
     In some example embodiments, the user interface  204  provides one or more additional user interface elements  222 ,  224 ,  226 , or  228  that enhance the functionality of the user interface  204  by allowing the user to buy selected consumable items by clicking on user interface element  222 , to buy all the consumable items that are listed in the user interface  204  by clicking on user interface element  224 , to subscribe to selected consumable items that are listed in the user interface  204  by clicking on user interface element  226 , or to subscribe to all consumable items that are listed in the user interface  204  by clicking on user interface element  228 . 
       FIG. 3  is a block diagram illustrating components of the item ordering system  300 , according to some example embodiments. As shown in  FIG. 3 , the item ordering system  300  includes an access module  302 , an identifying module  304 , an analysis module  306 , an ordering module  308 , and a presentation module  310 , all configured to communicate with each other (e.g., via a bus, shared memory, or a switch). 
     According to some example embodiments, the access module  302  accesses (e.g., receives, obtains, or is provided) image input associated with a consumable item. The image input may be accessed from a record of a database. The image input may be provided to the item ordering system  300  by a client device. The image input may be recorded by a camera associated with the client device, and may include at least one of a video or a photograph. The image input may depict one or more consumable items. The one or more consumable items, in some instances, are stored in a refrigerator or a pantry of the user. For example, a refrigerator of the user is associated with (e.g., includes) a camera that records images (e.g., photographs or video) of the one or more consumable items over a period of time. A series of images taken at different times of the period of time may indicate that some or all of the consumable items that appear in the images are partially or fully consumed (or depleted). In some instances, the one or more consumable items are stored in a refrigerator or a pantry of a store (e.g., a grocery store). 
     The identifying module  304  identifies an account based on an identifier (e.g., a phone number, a Unique Device Identifier (UDID), a mobile equipment identifier (MEID), Internet Protocol (IP) address, a media access control (MAC) address, etc.) of the client device. 
     An analysis module  306  determines a level of consumption of the consumable item for the account based on the image input. In some example embodiments, the determining of the level of consumption of the consumable item for the account based on the image input includes identifying a first image input associated with a first timestamp, identifying a second image input associated with a second timestamp that is subsequent to the first timestamp, and determining, based on comparing the first image input and the second image input, a change in the second image input. In some example embodiments, the change in the second image input indicates a decrease in the consumable item. In various example embodiments, the change in the second image input indicates a change in the appearance of the consumable item (e.g., a vegetable changes its shape, color, or texture as it becomes spoilt). In various example embodiments, the change in the second image indicates that the consumable item is being replaced (e.g., a new, empty garbage bag replaces an old, full garbage bag). 
     An ordering module  308 , based on the level of consumption of the consumable item, automatically places an order for the consumable item, for the account. In some example embodiments, the automatic placing of the order for the consumable item includes, using payment data previously provided by the user associated with the account, generating an order for the consumable item on behalf of the user from an e-commerce platform. 
     A presentation module  310 , in response to the automatic placing of the order for the consumable item, causes display of a notification describing the automatically placed order for the consumable item in a user interface of the client device associated with the account. A selection, by the user, of the notification describing the automatically placed order for the consumable item via the user interface of the client device causes display of an automatically generated request to specify a schedule of future automatic orders for the consumable item. 
     To perform one or more of its functionalities, the item ordering system  300  communicates with one or more other systems. For example, an integration engine (not shown) may integrate the item ordering system  300  with one or more email server(s), web server(s), one or more databases, or other servers, systems, or repositories. 
     Any one or more of the modules described herein may be implemented using hardware (e.g., one or more processors of a machine) or a combination of hardware and software. For example, any module described herein may configure a processor (e.g., among one or more processors of a machine) to perform the operations described herein for that module. In some example embodiments, any one or more of the modules described herein may comprise one or more hardware processors and may be configured to perform the operations described herein. In certain example embodiments, one or more hardware processors are configured to include any one or more of the modules described herein. 
     Moreover, any two or more of these modules may be combined into a single module, and the functions described herein for a single module may be subdivided among multiple modules. Furthermore, according to various example embodiments, modules described herein as being implemented within a single machine, database, or device may be distributed across multiple machines, databases, or devices. The multiple machines, databases, or devices are communicatively coupled to enable communications between the multiple machines, databases, or devices. The modules themselves are communicatively coupled (e.g., via appropriate interfaces) to each other and to various data sources to allow information to be passed between the applications and to allow the applications to share and access common data. Furthermore, the modules may access database  126 . 
       FIGS. 4-6  are flowcharts illustrating a method for automatically placing an order for a consumable item, according to some example embodiments. Operations in method  400  illustrated in  FIG. 4  may be performed using modules described above with respect to  FIG. 3 . As shown in  FIG. 4 , method  400  may include one or more of method operations  402 ,  404 ,  406 ,  408 , and  410 , according to example embodiments. 
     At operation  402 , the access module  302  accesses image input associated with a consumable item. The image input is recorded by a camera associated with a client device. The image input includes at least one of a video or a photograph of one or more consumable items within a storage area. 
     At operation  404 , the identifying module  304  identifies an account based on an identifier of the client device. The identifying may be performed based on matching the identifier of the client device, received from the client device, to an identifier included in the data associated with the account in a database record. 
     At operation  406 , the analysis module  306  determines a level of consumption of the consumable item for the account based on the image input. 
     In some example embodiments, the determining of the level of consumption of the consumable item for the account based on the image input includes: identifying a first image input associated with a first timestamp; identifying a second image input associated with a second timestamp that is subsequent to the first timestamp; and determining, based on comparing the first image input and the second image input, a change in the second image input that indicates a decrease in the consumable item. For example, the first image input taken on Monday at 9 a.m. shows that a third of a bottle of milk stored in the refrigerator has been consumed. The second image input taken on Tuesday at 9 a.m. shows that two thirds of the bottle of milk stored in the refrigerator has been consumed. Based on comparing the first image input and the second image input, the analysis module  306  determines the level of consumption of the consumable item for the account to be a third of a bottle of milk per day (or, specifically, between 9 a.m. on Monday and 9 a.m. on Tuesday). 
     In some example embodiments, the account includes transaction data associated with the consumable item, and the determining of the level of consumption of the consumable item is further based on the transaction data (e.g., records of previous purchases associated with the account). For example, the analysis module  306 , using records of previous purchases of the consumable item over a period of time (e.g., a month, six months, or a year), may determine a level of consumption of the consumable item over the period of time. The analysis module  306  may also determine whether a recent level of consumption (e.g., in the last month) of the consumable item has increased or decreased in comparison with the level of consumption of the consumable item during a different period of time (e.g., December 2019 vs. December 2018). 
     At operation  408 , the ordering module  308  automatically places an order for the consumable item, for the account. The automatic placing of the order for the consumable item, for the account is based on the level of consumption of the consumable item determined in operation  406 . 
     In some example embodiments, the automatic placing of the order for the consumable item, for the account, is further based on determining that the level of consumption of the consumable item is equal to or exceeds a threshold value. For example, the threshold value is three quarters of a gallon of milk. Based on a determination, by the analysis module  306 , that the level of consumption of milk, for the account, has exceeded three quarters of the gallon of milk, the ordering module  308  automatically places an order for milk, for the account. According to another example, the threshold value is four cans in a six-pack of cans (e.g., cans of soda). Based on a determination, by the analysis module  306 , that the level of consumption of soda, for the account, is equal to four cans, the ordering module  308  automatically places an order for soda, for the account. In some example embodiments, the amount of automatically ordered consumable item is based on a determined pattern of consumption of the consumable item for the account. 
     In various example embodiments, the automatic placing of the order for the consumable item, for the account, is further based on determining that the consumable item is absent from a location automatically determined to be a usual location of the consumable item. 
     At operation  410 , the presentation module  310  causes display of a notification describing the automatically placed order for the consumable item in a user interface of the client device associated with the account. The causing display is performed in response to the automatic placing of the order for the consumable item. A selection of the notification describing the automatically placed order for the consumable item may cause display of an automatically generated request to specify a schedule of future automatic orders for the consumable item. The selection may be made by the user via the user interface of the client device. 
     Further details with respect to the method operations of method  400  are described below with respect to  FIGS. 5 and 6 . 
     As shown in  FIG. 5 , method  400  includes one or more of operations  502 ,  504 , and  506 , according to some embodiments. Operation  502  may be performed after operation  408 , in which the ordering module  308  automatically places an order for the consumable item, for the account. 
     At operation  502 , the analysis module  306  automatically determines, for the account, a pattern of use of the consumable item over a period of time. The automatic determining of the pattern of use is based on automatic detecting of a change associated with the consumable item in a plurality of image inputs associated with a plurality of timestamps. The plurality of timestamps are automatically associated with the plurality of image inputs at a plurality of times of generating the plurality of image inputs. 
     For example, a first image input (e.g., a first image or photograph) of a bottle of milk in the refrigerator is captured, by a camera, at a first time (e.g., in the morning of a particular day). A second image input (e.g., a second image or photograph) of the bottle of milk in the refrigerator is captured, by a camera, at a second time (e.g., in the evening of the particular day). The first image input and the second image input are transmitted to the item ordering system  300 . The analysis module  306  of the item ordering system  300  compares the first image input and the second image input, and automatically detects a change associated with the bottle of milk in the second image input based on the comparison to the first image input. The system  300  may utilize image analysis and image recognition techniques to detect changes associated with a plurality of image inputs. 
     In some example embodiments, the change associated with the bottle of milk may include a decrease in the volume of milk. In various example embodiments, the change associated with the bottle of milk may include an absence of the bottle of milk in a location of the refrigerator where the bottle of milk is usually located. The absence of the bottle of milk from its usual location in the refrigerator may indicate that the milk was fully consumed. In some instances, to increase the confidence that the milk was fully consumed and to not place an order for milk prematurely, the system  300  utilizes additional image inputs (e.g., image inputs of the bottle of milk&#39;s usual location captured at later times, image inputs of additional areas of the refrigerator, or image inputs of one or more areas of a house, such as a kitchen table or a kitchen counter) to make a determination that the absence of the bottle of milk from its usual location in the refrigerator indicates the milk was fully consumed. 
     In some example embodiments, the analysis module  306  determines, based on analyzing image inputs associated with a first timestamp (t 1 ), a second timestamp (t 2 ), a third timestamp (t 3 ), and a fourth timestamp (t 4 ), that there was more consumption of the consumable item between t 1  and t 2 , and less consumption of the consumable item between t 2  and t 3 . For example, the analysis module  306  compares the image inputs of the bottle of milk that are captured at t 1 , t 2 , t 3 , and t 4 , and can determine that there is more consumption of milk between t 1  and t 2 , and less consumption of milk between t 2  and t 3 . The analysis module  306  predicts, using machine learning algorithms that perform pattern analysis, when the user will run out of milk, and the item ordering system  300  may communicate this information to the user. 
     At operation  504 , the analysis module  306  automatically predicts, for the account, a frequency of ordering the consumable item based on the automatically determined pattern of use of the consumable item. In some example embodiments, the automatic predicting, for the account, of the frequency of ordering the consumable item is further based on one or more calendar events (e.g., an upcoming birthday or Christmas) included in a calendar associated with the account. The predicting of the frequency of ordering of the consumable item may be performed using machine learning algorithms that perform pattern analysis of data associated with the account including image inputs associated with the consumable item, shopping history, subscription data, calendar data, etc. 
     Operation  506  may be performed as part (e.g., a precursor task, a subroutine, or a portion) of operation  410 , in which the presentation module  310  causes display of a notification describing the automatically placed order for the consumable item in a user interface of the client device associated with the account. At operation  506 , the causing display of the automatically generated request to specify the schedule of future automatic orders for the consumable item includes causing display of a recommendation for future automatic ordering of the consumable item at the automatically predicted frequency. For example, the recommendation includes options such as “order one gallon of milk, as previously ordered,” or “order two gallons of milk based on you increased consumption of milk.” 
     As shown in  FIG. 6 , method  400  includes one or more of operations  602  and  604 , according to some embodiments. Operation  602  may be performed after operation  408 , in which the ordering module  308  automatically places an order for the consumable item, for the account. 
     At operation  602 , the analysis module  306  compares the level of consumption of the consumable item, over a period of time, for the account and one or more levels of consumption of the consumable item, over the period of time, for one or more other accounts. For example, the analysis module  306  compares the level of consumption of milk, during November 2019, for the user or users associated with the account and one or more levels of consumption of milk, during November 2019, for the user or users associated with one or more other accounts. The comparing of the level of consumption of the consumable item for the account and the one or more levels of consumption of the consumable item for the one or more other accounts results in generation of an account comparison result. 
     Operation  604  may be performed as part (e.g., a precursor task, a subroutine, or a portion) of operation  410 , in which the presentation module  310  causes display of a notification describing the automatically placed order for the consumable item in a user interface of the client device associated with the account. At operation  604 , the causing display of the notification describing the automatically placed order for the consumable item in the user interface includes causing display of an indication of the account comparison result. For example, the indication of the account comparison result may include metrics that show how the consumption of the consumable item by the user associated with the account compares to the consumption of the consumable item by one or more other accounts (e.g., one or more other anonymous families). 
     Certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code embodied on a machine-readable medium) or hardware modules. A “hardware module” is a tangible unit capable of performing certain operations and may be configured or arranged in a certain physical manner. In various example embodiments, one or more computer systems (e.g., a standalone computer system, a client computer system, or a server computer system) or one or more hardware modules of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware module that operates to perform certain operations as described herein. 
     In some embodiments, a hardware module may be implemented mechanically, electronically, or any suitable combination thereof. For example, a hardware module may include dedicated circuitry or logic that is permanently configured to perform certain operations. For example, a hardware module may be a special-purpose processor, such as a Field-Programmable Gate Array (FPGA) or an Application Specific Integrated Circuit (ASIC). A hardware module may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware module may include software executed by a general-purpose processor or other programmable processor. Once configured by such software, hardware modules become specific machines (or specific components of a machine) uniquely tailored to perform the configured functions and are no longer general-purpose processors. It will be appreciated that the decision to implement a hardware module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations. 
     Accordingly, the phrase “hardware module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. As used herein, “hardware-implemented module” refers to a hardware module. Considering embodiments in which hardware modules are temporarily configured (e.g., programmed), each of the hardware modules need not be configured or instantiated at any one instance in time. For example, where a hardware module comprises a general-purpose processor configured by software to become a special-purpose processor, the general-purpose processor may be configured as respectively different special-purpose processors (e.g., comprising different hardware modules) at different times. Software accordingly configures a particular processor or processors, for example, to constitute a particular hardware module at one instance of time and to constitute a different hardware module at a different instance of time. 
     Hardware modules can provide information to, and receive information from, other hardware modules. Accordingly, the described hardware modules may be regarded as being communicatively coupled. Where multiple hardware modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) between or among two or more of the hardware modules. In embodiments in which multiple hardware modules are configured or instantiated at different times, communications between such hardware modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware modules have access. For example, one hardware module may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information). 
     The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions described herein. As used herein, “processor-implemented module” refers to a hardware module implemented using one or more processors. 
     Similarly, the methods described herein may be at least partially processor-implemented, with a particular processor or processors being an example of hardware. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented modules. Moreover, the one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), with these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., an Application Program Interface (API)). 
     The performance of certain of the operations may be distributed among the processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processors or processor-implemented modules may be located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the processors or processor-implemented modules may be distributed across a number of geographic locations. 
     The modules, methods, applications and so forth described in conjunction with  FIGS. 7 and 8  are implemented in some embodiments in the context of a machine and associated software architecture. The sections below describe representative software architecture(s) and machine (e.g., hardware) architecture that are suitable for use with the disclosed embodiments. 
     Software architectures are used in conjunction with hardware architectures to create devices and machines tailored to particular purposes. For example, a particular hardware architecture coupled with a particular software architecture will create a mobile device, such as a mobile phone, tablet device, or so forth. A slightly different hardware and software architecture may yield a smart device for use in the “internet of things.” While yet another combination produces a server computer for use within a cloud computing architecture. Not all combinations of such software and hardware architectures are presented here as those of skill in the art can readily understand how to implement the invention in different contexts from the disclosure contained herein. 
       FIG. 7  is a block diagram  700  illustrating a representative software architecture  702 , which may be used in conjunction with various hardware architectures herein described.  FIG. 7  is merely a non-limiting example of a software architecture and it will be appreciated that many other architectures may be implemented to facilitate the functionality described herein. The software architecture  702  may be executing on hardware such as machine  800  of  FIG. 8  that includes, among other things, processors  810 , memory  830 , and I/O components  850 . A representative hardware layer  704  is illustrated and can represent, for example, the machine  800  of  FIG. 8 . The representative hardware layer  704  comprises one or more processing units  706  having associated executable instructions  708 . Executable instructions  708  represent the executable instructions of the software architecture  702 , including implementation of the methods, modules and so forth of  FIGS. 1-6 . Hardware layer  704  also includes memory and/or storage modules  710 , which also have executable instructions  708 . Hardware layer  704  may also comprise other hardware as indicated by  712  which represents any other hardware of the hardware layer  704 , such as the other hardware illustrated as part of machine  800 . 
     In the example architecture of  FIG. 7 , the software  702  may be conceptualized as a stack of layers where each layer provides particular functionality. For example, the software  702  may include layers such as an operating system  714 , libraries  716 , frameworks/middleware  718 , applications  720  and presentation layer  760 . Operationally, the applications  720  and/or other components within the layers may invoke application programming interface (API) calls  724  through the software stack and receive a response, returned values, and so forth illustrated as messages  726  in response to the API calls  724 . The layers illustrated are representative in nature, and not all software architectures have all layers. For example, some mobile or special purpose operating systems may not provide a frameworks/middleware layer  718 , while others may provide such a layer. Other software architectures may include additional or different layers. 
     The operating system  714  may manage hardware resources and provide common services. The operating system  714  may include, for example, a kernel  728 , services  730 , and drivers  732 . The kernel  728  may act as an abstraction layer between the hardware and the other software layers. For example, the kernel  728  may be responsible for memory management, processor management (e.g., scheduling), component management, networking, security settings, and so on. The services  730  may provide other common services for the other software layers. The drivers  732  may be responsible for controlling or interfacing with the underlying hardware. For instance, the drivers  732  may include display drivers, camera drivers, Bluetooth® drivers, flash memory drivers, serial communication drivers (e.g., Universal Serial Bus (USB) drivers), Wi-Fi® drivers, audio drivers, power management drivers, and so forth depending on the hardware configuration. 
     The libraries  716  may provide a common infrastructure that may be utilized by the applications  720  and/or other components and/or layers. The libraries  716  typically provide functionality that allows other software modules to perform tasks in an easier fashion than to interface directly with the underlying operating system  714  functionality (e.g., kernel  728 , services  730  and/or drivers  732 ). The libraries  716  may include system  734  libraries (e.g., C standard library) that may provide functions such as memory allocation functions, string manipulation functions, mathematic functions, and the like. In addition, the libraries  716  may include API libraries  736  such as media libraries (e.g., libraries to support presentation and manipulation of various media format such as MPREG4, H.264, MP3, AAC, AMR, JPG, PNG), graphics libraries (e.g., an OpenGL framework that may be used to render 2D and 3D in a graphic content on a display), database libraries (e.g., SQLite that may provide various relational database functions), web libraries (e.g., WebKit that may provide web browsing functionality), and the like. The libraries  716  may also include a wide variety of other libraries  738  to provide many other APIs to the applications  720  and other software components/modules. 
     The frameworks  718  (also sometimes referred to as middleware) may provide a higher-level common infrastructure that may be utilized by the applications  720  and/or other software components/modules. For example, the frameworks  718  may provide various graphic user interface (GUI) functions, high-level resource management, high-level location services, and so forth. The frameworks  718  may provide a broad spectrum of other APIs that may be utilized by the applications  720  and/or other software components/modules, some of which may be specific to a particular operating system or platform. 
     The applications  720  include built-in applications  740 , third party applications  742 , and item ordering modules  744  (e.g., access module  302 , identifying module  304 , analysis module  306 , ordering module  308 , or presentation module  310 ). Examples of representative built-in applications  740  may include, but are not limited to, a contacts application, a browser application, a book reader application, a location application, a media application, a messaging application, and/or a game application. Third party applications  742  may include any of the built in applications as well as a broad assortment of other applications. In a specific example, the third party application  742  (e.g., an application developed using the Android™ or iOS™ software development kit (SDK) by an entity other than the vendor of the particular platform) may be mobile software running on a mobile operating system such as iOS™, Android™, Windows® Phone, or other mobile operating systems. In this example, the third party application  742  may invoke the API calls  724  provided by the mobile operating system such as operating system  714  to facilitate functionality described herein. 
     The applications  720  may utilize built in operating system functions (e.g., kernel  728 , services  730  and/or drivers  732 ), libraries (e.g., system  734 , APIs  736 , and other libraries  738 ), frameworks/middleware  718  to create user interfaces to interact with users of the system. Alternatively, or additionally, in some systems interactions with a user may occur through a presentation layer, such as presentation layer  760 . In these systems, the application/module “logic” can be separated from the aspects of the application/module that interact with a user. 
     Some software architectures utilize virtual machines. In the example of  FIG. 7 , this is illustrated by virtual machine  748 . A virtual machine creates a software environment where applications/modules can execute as if they were executing on a hardware machine (such as the machine of  FIG. 8 , for example). A virtual machine is hosted by a host operating system (operating system  714  in  FIG. 8 ) and typically, although not always, has a virtual machine monitor  746 , which manages the operation of the virtual machine as well as the interface with the host operating system (i.e., operating system  714 ). A software architecture executes within the virtual machine such as an operating system  750 , libraries  752 , frameworks/middleware  754 , applications  756  and/or presentation layer  760 . These layers of software architecture executing within the virtual machine  748  can be the same as corresponding layers previously described or may be different. 
       FIG. 8  is a block diagram illustrating components of a machine  800 , according to some example embodiments, able to read instructions from a machine-readable medium (e.g., a machine-readable storage medium) and perform any one or more of the methodologies discussed herein. Specifically,  FIG. 8  shows a diagrammatic representation of the machine  800  in the example form of a computer system, within which instructions  816  (e.g., software, a program, an application, an applet, an app, or other executable code) for causing the machine  800  to perform any one or more of the methodologies discussed herein may be executed. For example the instructions may cause the machine to execute the flow diagrams of  FIGS. 4-6 . Additionally, or alternatively, the instructions may implement the access module  302 , the identifying module  304 , the analysis module  306 , the ordering module  308 , and the presentation module  310 . The instructions transform the general, non-programmed machine into a particular machine programmed to carry out the described and illustrated functions in the manner described. In alternative embodiments, the machine  800  operates as a standalone device or may be coupled (e.g., networked) to other machines. In a networked deployment, the machine  800  may operate in the capacity of a server machine or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine  800  may comprise, but not be limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a personal digital assistant (PDA), an entertainment media system, a cellular telephone, a smart phone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a web appliance, a network router, a network switch, a network bridge, or any machine capable of executing the instructions  816 , sequentially or otherwise, that specify actions to be taken by machine  800 . Further, while only a single machine  800  is illustrated, the term “machine” shall also be taken to include a collection of machines  800  that individually or jointly execute the instructions  816  to perform any one or more of the methodologies discussed herein. 
     The machine  800  may include processors  810 , memory  830 , and I/O components  850 , which may be configured to communicate with each other such as via a bus  802 . In an example embodiment, the processors  810  (e.g., a Central Processing Unit (CPU), a Reduced Instruction Set Computing (RISC) processor, a Complex Instruction Set Computing (CISC) processor, a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Radio-Frequency Integrated Circuit (RFIC), another processor, or any suitable combination thereof) may include, for example, processor  812  and processor  814  that may execute instructions  816 . The term “processor” is intended to include multi-core processor that may comprise two or more independent processors (sometimes referred to as “cores”) that may execute instructions contemporaneously. Although  FIG. 8  shows multiple processors, the machine  800  may include a single processor with a single core, a single processor with multiple cores (e.g., a multi-core process), multiple processors with a single core, multiple processors with multiples cores, or any combination thereof. 
     The memory/storage  830  may include a memory  832 , such as a main memory, or other memory storage, and a storage unit  836 , both accessible to the processors  810  such as via the bus  802 . The storage unit  836  and memory  832  store the instructions  816  embodying any one or more of the methodologies or functions described herein. The instructions  816  may also reside, completely or partially, within the memory  832 , within the storage unit  836 , within at least one of the processors  810  (e.g., within the processor&#39;s cache memory), or any suitable combination thereof, during execution thereof by the machine  800 . Accordingly, the memory  832 , the storage unit  836 , and the memory of processors  810  are examples of machine-readable media. 
     As used herein, “machine-readable medium” means a device able to store instructions and data temporarily or permanently and may include, but is not be limited to, random-access memory (RAM), read-only memory (ROM), buffer memory, flash memory, optical media, magnetic media, cache memory, other types of storage (e.g., Erasable Programmable Read-Only Memory (EEPROM)) and/or any suitable combination thereof. The term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) able to store instructions  816 . The term “machine-readable medium” shall also be taken to include any medium, or combination of multiple media, that is capable of storing instructions (e.g., instructions  816 ) for execution by a machine (e.g., machine  800 ), such that the instructions, when executed by one or more processors of the machine  800  (e.g., processors  810 ), cause the machine  800  to perform any one or more of the methodologies described herein. Accordingly, a “machine-readable medium” refers to a single storage apparatus or device, as well as “cloud-based” storage systems or storage networks that include multiple storage apparatus or devices. The term “machine-readable medium” excludes signals per se. 
     The I/O components  850  may include a wide variety of components to receive input, provide output, produce output, transmit information, exchange information, capture measurements, and so on. The specific I/O components  850  that are included in a particular machine will depend on the type of machine. For example, portable machines such as mobile phones will likely include a touch input device or other such input mechanisms, while a headless server machine will likely not include such a touch input device. It will be appreciated that the I/O components  850  may include many other components that are not shown in  FIG. 8 . The I/O components  850  are grouped according to functionality merely for simplifying the following discussion and the grouping is in no way limiting. In various example embodiments, the I/O components  850  may include output components  852  and input components  854 . The output components  852  may include visual components (e.g., a display such as a plasma display panel (PDP), a light emitting diode (LED) display, a liquid crystal display (LCD), a projector, or a cathode ray tube (CRT)), acoustic components (e.g., speakers), haptic components (e.g., a vibratory motor, resistance mechanisms), other signal generators, and so forth. The input components  854  may include alphanumeric input components (e.g., a keyboard, a touch screen configured to receive alphanumeric input, a photo-optical keyboard, or other alphanumeric input components), point based input components (e.g., a mouse, a touchpad, a trackball, a joystick, a motion sensor, or other pointing instrument), tactile input components (e.g., a physical button, a touch screen that provides location and/or force of touches or touch gestures, or other tactile input components), audio input components (e.g., a microphone), and the like. 
     In further example embodiments, the I/O components  850  may include biometric components  856 , motion components  858 , environmental components  860 , or position components  862  among a wide array of other components. For example, the biometric components  856  may include components to detect expressions (e.g., hand expressions, facial expressions, vocal expressions, body gestures, or eye tracking), measure biosignals (e.g., blood pressure, heart rate, body temperature, perspiration, or brain waves), identify a person (e.g., voice identification, retinal identification, facial identification, fingerprint identification, or electroencephalogram based identification), and the like. The motion components  858  may include acceleration sensor components (e.g., accelerometer), gravitation sensor components, rotation sensor components (e.g., gyroscope), and so forth. The environmental components  860  may include, for example, illumination sensor components (e.g., photometer), temperature sensor components (e.g., one or more thermometer that detect ambient temperature), humidity sensor components, pressure sensor components (e.g., barometer), acoustic sensor components (e.g., one or more microphones that detect background noise), proximity sensor components (e.g., infrared sensors that detect nearby objects), gas sensors (e.g., gas detection sensors to detection concentrations of hazardous gases for safety or to measure pollutants in the atmosphere), or other components that may provide indications, measurements, or signals corresponding to a surrounding physical environment. The position components  862  may include location sensor components (e.g., a Global Position System (GPS) receiver component), altitude sensor components (e.g., altimeters or barometers that detect air pressure from which altitude may be derived), orientation sensor components (e.g., magnetometers), and the like. 
     Communication may be implemented using a wide variety of technologies. The I/O components  850  may include communication components  864  operable to couple the machine  800  to a network  880  or devices  870  via coupling  882  and coupling  872  respectively. For example, the communication components  864  may include a network interface component or other suitable device to interface with the network  880 . In further examples, communication components  864  may include wired communication components, wireless communication components, cellular communication components, Near Field Communication (NFC) components, Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and other communication components to provide communication via other modalities. The devices  870  may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device coupled via a Universal Serial Bus (USB)). 
     Moreover, the communication components  864  may detect identifiers or include components operable to detect identifiers. For example, the communication components  864  may include Radio Frequency Identification (RFID) tag reader components, NFC smart tag detection components, optical reader components (e.g., an optical sensor to detect one-dimensional bar codes such as Universal Product Code (UPC) bar code, multi-dimensional bar codes such as Quick Response (QR) code, Aztec code, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2D bar code, and other optical codes), or acoustic detection components (e.g., microphones to identify tagged audio signals). In addition, a variety of information may be derived via the communication components  864 , such as, location via Internet Protocol (IP) geo-location, location via Wi-Fi® signal triangulation, location via detecting an NFC beacon signal that may indicate a particular location, and so forth. 
     In various example embodiments, one or more portions of the network  880  may be an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), a metropolitan area network (MAN), the Internet, a portion of the Internet, a portion of the Public Switched Telephone Network (PSTN), a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, a Wi-Fi® network, another type of network, or a combination of two or more such networks. For example, the network  880  or a portion of the network  880  may include a wireless or cellular network and the coupling  882  may be a Code Division Multiple Access (CDMA) connection, a Global System for Mobile communications (GSM) connection, or other type of cellular or wireless coupling. In this example, the coupling  882  may implement any of a variety of types of data transfer technology, such as Single Carrier Radio Transmission Technology (1×RTT), Evolution-Data Optimized (EVDO) technology, General Packet Radio Service (GPRS) technology, Enhanced Data rates for GSM Evolution (EDGE) technology, third Generation Partnership Project (3GPP) including 3G, fourth generation wireless (4G) networks, Universal Mobile Telecommunications System (UMTS), High Speed Packet Access (HSPA), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) standard, others defined by various standard setting organizations, other long range protocols, or other data transfer technology. 
     The instructions  816  may be transmitted or received over the network  880  using a transmission medium via a network interface device (e.g., a network interface component included in the communication components  864 ) and utilizing any one of a number of well-known transfer protocols (e.g., hypertext transfer protocol (HTTP)). Similarly, the instructions  816  may be transmitted or received using a transmission medium via the coupling  872  (e.g., a peer-to-peer coupling) to devices  870 . The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding, or carrying instructions  816  for execution by the machine  800 , and includes digital or analog communications signals or other intangible medium to facilitate communication of such software. 
     Executable Instructions and Machine-Storage Medium 
     The various memories (i.e.,  830 ,  832 , and/or memory of the processor(s)  810 ) and/or storage unit  836  may store one or more sets of instructions and data structures (e.g., software)  816  embodying or utilized by any one or more of the methodologies or functions described herein. These instructions, when executed by processor(s)  810  cause various operations to implement the disclosed embodiments. 
     As used herein, the terms “machine-storage medium,” “device-storage medium,” “computer-storage medium” (referred to collectively as “machine-storage medium”) mean the same thing and may be used interchangeably in this disclosure. The terms refer to a single or multiple storage devices and/or media (e.g., a centralized or distributed database, and/or associated caches and servers) that store executable instructions and/or data, as well as cloud-based storage systems or storage networks that include multiple storage apparatus or devices. The terms shall accordingly be taken to include, but not be limited to, solid-state memories, and optical and magnetic media, including memory internal or external to processors. Specific examples of machine-storage media, computer-storage media, and/or device-storage media include non-volatile memory, including by way of example semiconductor memory devices, e.g., erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), FPGA, and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The terms machine-storage media, computer-storage media, and device-storage media specifically exclude carrier waves, modulated data signals, and other such media, at least some of which are covered under the term “signal medium” discussed below. In this context, the machine-storage medium is non-transitory. 
     Signal Medium 
     The term “signal medium” or “transmission medium” shall be taken to include any form of modulated data signal, carrier wave, and so forth. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a matter as to encode information in the signal. 
     Computer Readable Medium 
     The terms “machine-readable medium,” “computer-readable medium” and “device-readable medium” mean the same thing and may be used interchangeably in this disclosure. The terms are defined to include both machine-storage media and signal media. Thus, the terms include both storage devices/media and carrier waves/modulated data signals. 
     Language 
     Throughout this specification, plural instances may implement components, operations, or structures described as a single instance. Although individual operations of one or more methods are illustrated and described as separate operations, one or more of the individual operations may be performed concurrently, and nothing requires that the operations be performed in the order illustrated. Structures and functionality presented as separate components in example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter herein. 
     Although an overview of the inventive subject matter has been described with reference to specific example embodiments, various modifications and changes may be made to these embodiments without departing from the broader scope of embodiments of the present disclosure. Such embodiments of the inventive subject matter may be referred to herein, individually or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single disclosure or inventive concept if more than one is, in fact, disclosed. 
     The embodiments illustrated herein are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed. Other embodiments may be used and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. The Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled. 
     As used herein, the term “or” may be construed in either an inclusive or exclusive sense. Moreover, plural instances may be provided for resources, operations, or structures described herein as a single instance. Additionally, boundaries between various resources, operations, modules, engines, and data stores are somewhat arbitrary, and particular operations are illustrated in a context of specific illustrative configurations. Other allocations of functionality are envisioned and may fall within a scope of various embodiments of the present disclosure. In general, structures and functionality presented as separate resources in the example configurations may be implemented as a combined structure or resource. Similarly, structures and functionality presented as a single resource may be implemented as separate resources. These and other variations, modifications, additions, and improvements fall within a scope of embodiments of the present disclosure as represented by the appended claims. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.