METHOD, COMPUTER PROGRAM PRODUCT, AND SYSTEM FOR PROVIDING A SENSOR-BASED ENVIRONMENT

Abstract

Method, computer program product, and system of providing rewards to a person based on item interactions during a transaction in an environment, where the person is associated with a personal profile. The method includes generating, based on information in the personal profile, one or more tasks for the person to complete during the transaction, each task including at least one item interaction. The method further includes presenting, using an output device within the environment, the one or more tasks to the person, analyzing image information acquired by one or more visual sensors within the environment to evaluate the person's performance of the one or more tasks, and awarding, based on the evaluation, an amount of rewards to the person.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims benefit of United States provisional patent application Ser. No. 62/064,323, filed Oct. 15, 2014, entitled “Integrated Shopping Environment,” which is herein incorporated by reference.

BACKGROUND

The present disclosure relates to a sensor-based environment, and more specifically, to techniques for identification of items selected by a person in the environment using visual identification and using personal profile information associated with the person.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 illustrates an exemplary environment including a plurality of items, according to one embodiment.

FIG. 2 illustrates an exemplary system of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment.

FIG. 3 is a block diagram illustrating operation of a system of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment.

FIG. 4 illustrates a method 400 of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment.

FIG. 5 illustrates a method 500 of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment.

FIG. 6 illustrates a method 600 of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment.

FIG. 7 illustrates a method 700 of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment.

FIG. 8 illustrates a method 800 of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment.

To facilitate understanding, identical reference numerals have been used, where possible, to designate identical elements that are common to the figures. It is contemplated that elements disclosed in one embodiment may be beneficially utilized on other embodiments without specific recitation. The illustrations referred to here should not be understood as being drawn to scale unless specifically noted. Also, the drawings are often simplified and details or components omitted for clarity of presentation and explanation. The drawings and discussion serve to explain principles discussed below, where like designations denote like elements.

DETAILED DESCRIPTION

Aspects of the current disclosure relate to an integrated environment capable of providing a personalized, automated, and adaptive experience for a person within the environment. A number of different sensor devices may be employed within the environment, and networked with various computing devices such as point-of-sale (POS) terminals, digital signage, servers, and mobile or handheld computing devices to provide a seamless integration of mobile technologies and e-commerce into traditional experiences.

Using a system having one or more visual sensors within the environment, a retailer or other provider may compile and process environmental data related to a person's transaction within the environment. The environmental data may be used to identify interactions of the person with various items in the environment, which may include selecting items for presentation during a subsequent checkout transaction. The identification of the interactions and items may be based on an analysis of static imagery—such as an image of contents of the person's shopping cart at a particular time—and/or dynamic imagery (e.g., using a continuous video feed). The identification may occur at different times and places during the transaction within the environment, such as while the person browses items, while scanning items during a checkout transaction, and so forth.

A rewards program may be administered within an environment, incentivizing certain tasks performed by persons such as customers. Rewards programs may be implemented in various forms, such as games or other tasks for the person to perform during the transaction, which are incentivized as appropriate. Generally, the benefits provided through rewards programs may keep customers more engaged during their transactions, and therefore more likely to return for subsequent transactions. Performing the rewards tasks may benefit the individual customers—offering monetary discounts or other incentives—but may also benefit the environment administrators (e.g., retailers) and/or item manufacturers due to the increased visibility of items and possibility of increased sales. In some cases, the rewards tasks may further benefit the environment administrators through customers' willing participation in otherwise menial tasks, which may allow for a better distribution of employees to provide service to customers. All in all, rewards programs may provide a better experience for customers, individually as well as in the aggregate.

However, not all tasks are equally appealing or interesting to all customers. In various embodiments, personal profile information that is compiled for an individual person may be used to adapt the tasks to the personal interests of the person. The personal profile information may include an item history, preferences, as well as other information. By using the personal profile information to make the tasks more relevant and interesting to the person, the chances of willing participation by the person in the rewards program are increased.

While generally discussed within the context of a shopping environment, such as a retail store or commercial environment, it is contemplated that the techniques disclosed herein may be applied to other environments (some non-limiting examples include libraries, museums, classrooms, hospitals, etc.) to provide a similar experience for persons included therein.

FIG. 1 illustrates an exemplary environment including a plurality of items, according to one embodiment. The environment 100 includes a plurality of sensor modules 105 disposed in the ceiling 110 of the environment. The sensor modules 105 may each include one or more types of sensors, such as video sensors (e.g., cameras), audio sensors (e.g., microphones), and so forth. Sensor modules 105 may also include actuating devices for providing a desired position and/or orientation of the included sensor(s). Generally, the sensor modules or individual sensors may be disposed at any suitable location within the environment 100. Some non-limiting examples of alternative locations include below, within, or above a floor 115 of the environment, within other structural components of the environment 100 such as a shelving unit 120 or walls, and so forth. In some embodiments, sensors may be disposed on, within, or near item display areas such as the shelving unit 120. The sensors may be oriented toward expected locations of personal interactions with items in order to acquire better data about the person's interactions, such as determining the person's field of view relative to certain items, updating a virtual cart or transaction record for the person's transaction in the environment, and so forth.

Environment 100 also includes a number of computer-based terminals (or kiosks) 125. Generally, terminals 125 may be configured for performing customer checkout and/or other functions, such as providing information to a customer or employee. Each terminal 125 may each include a discrete computing device or portions of a computing system, and may include various I/O devices, such as visual displays, audio speakers, cameras, microphones, etc. for interacting with various persons such as customers and/or employees. In some embodiments, a person 130 in the environment may have a mobile computing device, such as a smartphone 135, that communicatively couples with the terminal 125 for completing a checkout transaction. For example, the person's smartphone 135 may include payment information, identification information, etc. that facilitate completion of the checkout transaction. In one embodiment, the mobile computing device may execute a store application that connects with the computing system of the environment (e.g., to store servers or other computing devices through the Internet). In one embodiment, the mobile computing device may be directly connected with kiosk 125 through wireless networks established within the environment (e.g., over Wi-Fi or Bluetooth). In one embodiment, the mobile computing device may couple with the kiosk 125 when brought within range, e.g., using Bluetooth or near-field communication (NFC).

Environment 100 also includes one or more shelving units 120 having shelves 140 that support various store items 145. Though not shown, multiple shelving units 120 may be disposed in a particular arrangement in the environment 100, with the space between adjacent shelving units forming aisles through which customers and employees may travel. For example, customers may navigate the aisles and/or approach the shelving units 120 to view items 145 included therein, to handle the items, to select the items, etc. In another example, employees may navigate the aisles and/or approach the shelving units 120 to view stock levels of the items 145, to determine out-of-place items, etc. In some embodiments, shelving units 120 may include visual sensors or other sensor devices or I/O devices. The sensors or devices may couple with the person's smartphone 135 and/or other networked computing devices (including terminals 125 and/or servers) that are associated with the environment 100. For example, the front portions 150 of shelves 140 may include video sensors oriented outward from the shelving unit 120 (i.e., toward the aisle) to acquire image information for a person's interactions with items 145 on the shelving unit 120, with the image information provided to back-end servers for storage and/or analysis. In some cases, some or all of the image information may also be accessible by a person's mobile computing device. In some embodiments, portions of the shelving unit 120 (such as the front portions 150 of shelves 140) may include indicator lights or other visual display devices or audio output devices that are able to communicate with a person.

During an exemplary transaction in the environment, the person 130 may have a shopping receptacle in which the person places items after they are selected for purchase. Examples of shopping receptacles include shopping carts, baskets, or other containers that may be carried or otherwise transported by the person during the transaction. Upon completion of the transaction—for example, the person has selected all of the desired items—the person may approach one of the terminals 125 or a designated checkout area to perform a checkout transaction.

In some cases, the checkout transaction may have “touchless” aspects or may be entirely touchless. For example, visual sensors included in the environment and/or within the approached terminal 125 may acquire image information that is usable to identify the person, items included within the shopping receptacle, etc. and that streamlines or otherwise facilitates the checkout transaction. As will be discussed further herein, logic may be applied to enhance the analysis of the image information using personal profile information associated with the person conducting the transaction. Application of the personal profile information may result in item identification processes having greater accuracy and/or confidence levels, as well as being performed more quickly. The improved accuracy and speed may help the person to spend a shorter time completing their checkout transaction, which can improve their overall transaction experience. Reducing time for checkout transactions also increases the collective throughput at the checkout area. In some cases, a person may be able to complete a checkout transaction simply as part of departing the environment, without requiring the person to stop at a checkout terminal or in the checkout area. In some cases, the person's time in the checkout area may be significantly reduced, such as only a momentary pause at a checkout terminal.

FIG. 2 illustrates an exemplary system of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment. The system 200 includes a number of components that are disposed within the environment 100. The system may also include components that are outside the environment—for example, a server 265 may be located remotely or proximately disposed to the environment (such as within a back room in the same building that is not accessible by customers).

Components within the environment include one or more sensors 205 of various types, such as visual sensors 210, audio sensors 215, and weight sensors 220. The sensors 205 may also include other sensors 225 capable of providing meaningful information about personal interactions within the environment, e.g., location sensors. The sensors 205 may be discrete sensor devices deployed throughout the environment 100 in fixed and/or movable locations. Sensors 205 may be statically included in walls, floors, ceilings, displays, or other non-sensor devices, or may be included in shopping receptacles capable of being transported through the environment. For example, weight sensors 220 may be disposed in fixed locations within the environment, such as within the floor or within a surface of a checkout terminal, and may also include load cells or other sensors disposed in a basket portion of a shopping receptacle. In one embodiment, sensors 205 may include adjustable-position sensor devices, such as motorized cameras (i.e., an example of visual sensors 210) attached to a rail, wire, or frame. In one embodiment, sensors 205 may be included on one or more unmanned vehicles configured to travel through some or all of the environment 100, such as unmanned ground vehicles (UGVs) or unmanned aerial vehicles (UAVs or “drones”). Sensors 205 may also include sensor devices that are included in computing devices associated with the environment 100, such as personal devices 230, employee devices 235, and terminals 240. In some cases, the computing devices (or the component sensor devices) may be implemented as body-worn or carried devices.

Personal devices 230 and employee devices 235 may each include passive or actively-powered devices capable of communicating with at least one of the networked devices of system 200. One example of a passive device (which may be worn or carried) is a NFC tag. Active devices may include mobile computing devices, such as smartphones or tablets, or wearable devices such as a Google Glass™ interactive eyepiece (Glass is a trademark of Google Inc.). The personal devices 230 generally denotes ownership or possession of the devices by customers within the environment 100, while the employee devices 235 denotes ownership or possession by the retailer or other administrator of the environment 100. In some cases, employee devices 235 may be carried by employees and used in the course of their employment. Personal devices 230 and employee devices 235 may execute applications or other program code that generally enables various functions and features accessible using server 265 and/or other networked computing devices. In some embodiments, sensor devices that are included with the personal devices 230 or employee devices 235 may be included in the sensors 205.

System 200 includes a plurality of terminals 240 within the environment 100. Terminals 240 generally include any structure that is capable of receiving input from and/or producing output to people (e.g., customers, employees) within the environment 100. The terminals 240 may include computing systems, portions of computing systems, or devices controllable by computing systems. In one example, a terminal 240 may include a computing device that is communicatively coupled with a visual display and audio speaker(s), as well as being communicatively coupled with one or more input devices. In another example, a terminal 240 may include a visual display and associated driver hardware, but a computing device coupled to the terminal and providing data for display is disposed separately from the terminal. In some embodiments, terminals 240 may be implemented as standalone devices, such as a kiosk disposed on the store floor or monolithic device disposed on a shelf or platform. In some embodiments, terminals 240 may be integrated partially or wholly with other components of the environment 100, such as input or output devices included with shelving or other structural components in the environment (e.g., components used for product display or storage). In some embodiments, terminals 240 may be modular and may be easily attachable and detachable to elements of the environment 100, such as the structural components.

Generally, terminals 240 may be distributed throughout the environment 100 and may enhance various phases of the person's transactions within the environment. For example, terminals 240 may include digital signage (i.e., included as an example of other terminals 255) disposed throughout the environment, such as included in or near aisles, endcaps, displays, and/or shelving in the environment. A person during a transaction may view and/or interact with the digital signage as he or she moves throughout the environment. The digital signage may be included in a static display or may be movable, such as including digital signage within a shopping receptacle. Terminals 240 may also include one or more types of terminals usable for completing checkout transactions, such as employee-manned POS terminals 245 and self-checkout terminals 250. In some cases, the terminals 240 that provide checkout functionality may be disposed within a designated checkout area within the environment 100.

In some embodiments, terminals 240 may provide an integrated functionality. For example, terminals 240 may function in a first mode as digital signage, and when engaged by a person (i.e., receiving input from the person), the terminals function in a second mode as a self-checkout terminal or other type of terminal.

Server 265 generally includes processor(s), memory, and communications capabilities and may perform various computing tasks to support the operation of the environment 100. Server 265 may communicate using various wired and/or wireless communications methods with terminals 240, sensors 205, and with other networked devices such as personal devices 230 and employee devices 235. Server 265 generally executes computer program code in which input data is received from networked devices, the input data is processed and/or stored by the servers, and output data is provided to networked devices for operation of the environment 100.

Network 260 may include one or more networks of various types, including a local area or local access network (LAN), a general wide area network (WAN), and/or a public network (e.g., the Internet). In one embodiment, various networked computing devices of the system 200 are interconnected using a LAN, and one or more computing devices (e.g., server 265, personal devices 230) include connections to the Internet.

FIG. 3 is a block diagram illustrating operation of a system of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment. Specifically, the arrangement 300 illustrates operation of the system 200. Arrangement 300 includes a number of processors 305, memory 310, and input/output 315, which are interconnected using one or more connections 320. In one embodiment, the arrangement 300 may be implemented as a singular computing device and connection 320 may represent a common bus. In other embodiments, arrangement 300 is distributed and includes a plurality of discrete computing devices that are connected through wired or wireless networking. The processors 305 may include any processing element suitable for performing functions described herein, and may include single or multiple core processors, as well as combinations thereof. Processors 305 may be included in a single computing device, or may represent an aggregation of processing elements included across a number of networked devices such as the personal devices 230, terminals 240, etc. discussed above.

Input/output (I/O) 315 includes one or more output devices 370 and one or more sensors 205. Output devices 370 include one or more devices for presenting information to customers and generally include audio output devices 371 and/or visual output devices 372. The audio output devices 371 may include conventional audio speakers having any suitable form factor (e.g., standalone, integrated in a stereo, headphones, etc.), as well as devices using alternative methods of producing sound perceptible by a person such as a customer or employee, such as bone conduction transducers in a worn device. Visual output devices 372 may include visual displays and various visual indicators such as light emitting diodes (LEDs). In some embodiments, the terminals 240, personal devices 230, and employee devices 235 of FIG. 2 may include the output devices 370, such as visual devices 372 (e.g., visual displays, indicators) and/or audio devices 371 (e.g., speakers) for communicating with persons during their transactions. Other output devices 373 may provide information to customers through tactile feedback (e.g., haptic devices) or using other sensory stimuli. Sensors 305 may include visual sensors 210 which may be carried or worn sensors 374, and distributed sensors 376 that are disposed throughout the environment. In one embodiment, the distributed sensors 376 are disposed in a static arrangement in the environment. In one embodiment, at least some of the distributed sensors 376 are movable. For example, the distributed sensors 376 may be included on movable product displays or structures, and/or unmanned vehicles (e.g., aerial or ground-based vehicles). Other sensors 378 may also be included that are suitable for collecting information about a person and his/her interactions within the environment. Examples of other sensors 378 include without limitation infrared (IR) sensors, thermal sensors, weight sensors, capacitive sensors, magnetic sensors, sonar sensors, radar sensors, lidar sensors, and so forth.

I/O 315 may also include input devices 368 suitable for receiving input from persons, such as cameras, keyboards or keypads, touchscreens, buttons, inertial sensors, etc. I/O 315 may further include wired or wireless connections to an external network (e.g., network 260) using I/O adapter circuitry.

The visual sensors 210 may be used to capture image information 346 including the person and/or the environment, which may include views from various perspectives (e.g., a customer-worn visual sensor, static or movable visual sensors at various locations in the environment). The image information 346 may be stored in memory 310, and may be individually or collectively processed by processors 305 to determine information about persons within the environment and their respective interactions with items in the environment.

Memory 310 may include a variety of computer-readable media selected for their size, relative performance, or other capabilities: volatile and/or non-volatile media, removable and/or non-removable media, etc. Memory 310 may include cache, random access memory (RAM), storage, etc. Storage included as part of memory 310 may typically provide a non-volatile memory for the networked computing devices (e.g., server 265), and may include one or more different storage elements such as Flash memory, a hard disk drive, a solid state drive, an optical storage device, and/or a magnetic storage device. Memory 310 may be included in a single computing device or may represent an aggregation of memory included in networked devices. Memory 310 may include a plurality of modules for performing various functions described herein. The modules generally include program code that is executable by one or more of the processors 305. As shown, modules include an image analysis module 348, a rewards module 350, and an inventory management module 358. The modules may also interact to perform certain functions. For example, rewards module 350 may make calls to the image analysis module 348 to evaluate using image information 346 a person's performance of a presented task. The person of ordinary skill will recognize that the modules provided here are merely non-exclusive examples; different functions and/or groupings of functions may be included as desired to suitably operate the environment.

Memory 310 includes a plurality of personal profiles 322 corresponding to the different persons. In some cases, the personal profiles 322 may be associated with a loyalty program administered in the environment. During operation of the system 200, the personal profiles 322 may be associated with a current transaction for a person after identifying the person using the person's portable computing device (e.g., a login using a mobile computing app), a visual scan of the person's loyalty card or the person's face or other identifying features, etc. In one embodiment, the personal profiles 322 and at least some of the image information 346 may be stored on the server 265 or on a separate database.

The personal profiles 322 include a number of different types of information that may be useful to augment visual identification of items. An item interaction history 324 may reflect the person's interactions with various items in the environment, which may have occurred during previous transactions and/or earlier during the current transaction. The item interaction history 324 may be adaptively updated as image information is acquired and the person's identified interactions are added into the virtual transaction record 349. Some non-limiting examples of item interactions include viewing items 325, handling items 326, and purchasing items 327. The item interactions may be directly observed and/or deduced using visual sensors 210 in the environment. In one example of direct observation, a person wears a forward-looking visual sensor that generally represents their field of view (i.e., including viewed items) at a given time. In one example of a deduced observation, a gaze-tracking camera tracks the eye movement of the person, but its information alone may be unable to discern what items the person is viewing. However, using image information to determine the person's position within the environment and the relative orientation of their head, and perhaps referenced with item location information, the system may be able to determine what items are being viewed by the person and add this information into the viewing items 325 portion of the item interaction history 324.

Personal profiles 322 also include personal preferences 328 reflecting preferences that are explicitly specified by the person (explicit preferences 329), or that may be deduced by the system based on other information included in the personal profile 322 (deduced preferences 330), such as the person's item interaction history 324. The person may specify preferences using a personal computing device (e.g., through a mobile computing device app) or through terminals or other computing devices accessible in the environment. Personal preferences 328 may reflect preferences of one item in relation to another (e.g., apples tend to be purchased at the same time as oranges), one grouping of items in relation to another (e.g., junk food preferred over vegetables), transaction preferences, and so forth. In one example, a person may prefer to purchase their fresh produce during a certain transaction that occurs with some regularity, say every couple of weeks. Therefore, when a first item is selected that is positively identified as a fresh vegetable, it is likely that a significant number of other items in the same transaction will also be fruits and/or vegetables. This information may be used to help identify items detected by the image analysis.

Personal profiles 322 may also include health information 332 for the person. For example, a person could specify that they have certain allergies or other medical conditions 333. For example, a person may have allergic reactions to certain items such as nuts, shellfish, eggs, etc. The other medical conditions, while perhaps not as serious as an allergic reaction, may still cause discomfort to the person. For example, oils in mango skin may cause dermatitis for persons who are sensitive to poison ivy. Items that are related to the allergies and other conditions 333 are generally less likely to be selected by the person during a transaction. In some embodiments, the allergies and other conditions 333 may be used to remove certain possible items from consideration while performing item identification, as it would be highly unlikely that the person would be selecting an item to which they are allergic. Health information 332 may also include one or more nutrition goals 334 and fitness goals 335 for the person.

For example, nutrition goals 334 may include a set of values representing various nutrients (calories, vitamins, minerals, etc.), which may be provided as daily recommendations or perhaps indicated as part of a specific diet plan for the person. The nutrition goals 334 may interact with or may partially overlap with the fitness goals 335 (e.g., caloric content related to weight loss).

Personal profiles 322 may also include prospective item information 336 that suggests that a person may select a particular type of item during the transaction. The prospective item information 336 may be indicated by the person or deduced. For example, the person may enter a shopping list or wish list 337 using a mobile computing device app, and the items listed therein are very likely to be selected by the person during the transaction. In another example, a recipe 338 is entered by the person in the mobile computing device app (e.g., the person wishes to purchase the component ingredients to prepare the recipe). Alternatively, recipes may be accessed by the system 200 responsive to a number of items previous identified during the transaction. For example, say a person selects containers of peanut butter and of jelly during a particular transaction. The system may search for recipes that include both of those ingredients—one of which is a peanut butter and jelly sandwich. Based on the information in this recipe 338, it is more likely that the person will also select bread during the transaction. Accordingly, a visually detected item with physical attributes roughly corresponding to a loaf of bread (e.g., having an approximate size and shape as the loaf) may be more easily identified as the loaf of bread, without the need for full image processing.

Memory 310 includes a virtual transaction record 349 reflecting the person's item interactions, which may be determined using acquired image information 346. In some embodiments, the virtual transaction record 349 is included in the personal profile 322; in some embodiments, the two may be separately maintained in memory 310. The person's interactions with different items may be identified using image information, and those interactions stored in the virtual transaction record 349. When items are identified as being selected by the person, the selected items may be added to item lists (e.g., a virtual cart) within the virtual transaction record 349. The item lists are then used as part of completing the checkout transaction. In some cases, as the virtual transaction record 349 is updated, corresponding portions of the item interaction history 324 are also updated.

Image information 346 is generally acquired using the visual sensors 210. The image information 346 may be maintained in any form suitable for performing image analysis—one or more still images, video, and so forth. In some cases, the image information 346 does not include labeling (such as a universal product code (UPC) or quick response (QR) code) or other encoded information that is sufficient to uniquely identify the item. In some cases, the image information 346 includes some encoded information, but not enough to positively identify the corresponding item (e.g., the barcode is partially obscured). In some embodiments, partial encoded identification information may be used to narrow a set of possible items for item identification.

Image analysis module 348 is configured to receive image information 346 as inputs, and to perform analysis according to any suitable techniques. Generally, the image analysis module 348 may perform edge detection or comparable techniques to define areas within the image information 346 that correspond to different items. The image analysis module 348 may further compare the image information 346 with reference image information 343 to attempt to identify the detected items. In some cases, reference image information 343 may be intentionally simplified, such as acquiring the reference image information under controlled conditions, including only a singular item within the reference image information, and so forth.

The image analysis module 348 may further be able to detect predefined gestures or other behaviors by a person relative to particular items. In some embodiments, an item interaction represents a determined behavior of the person relative to an identified item. Some non-limiting examples of item interactions include viewing items 325, handling items 326, and purchasing items 327. In some embodiments, the image analysis module 348 is configured to output item interactions to the virtual transaction record 349 and/or to the rewards module 350. In some embodiments, the identified items and behaviors are output to the virtual transaction record 349, where the item interactions are determined (i.e., association of items with behaviors). The virtual transaction record 349 may then provide the determined item interactions to the rewards module 350.

The item interactions (including identified items and behaviors) from the image analysis module 348 may be provided as inputs to the rewards module 350. Rewards module 350 is generally configured to administer the rewards component of the system 200, which incentivizes a person for performing certain tasks within the environment. The incentives may be provided to the person in any suitable form, such as money, points, discounts, coupons, promotions, giveaways, etc. In some cases, a rewards component of an environment may be completely responsive, with the incentives determined based on actions the person has already taken within the environment. In various embodiments described herein, the rewards component may include proactive aspects, providing specific tasks for the person to perform during their transaction within the environment. While a person's participation in the provided rewards tasks is not guaranteed, determining suitable tasks and appropriate incentives for the tasks increases the chance that the person will participate. The rewards module 350 includes a number of functional sub-modules 351, which include task generation 352, evaluation 354, and award 356. The rewards module 350 may further include one or more predefined games 353 that provide a context or cohesive theme for the individually generated tasks. The addition of context, such as animated characters, a story or narrative, or other audiovisual elements, may increase a level of interest or engagement for the person, further encouraging the person's participation in the rewards tasks.

The task generation sub-module 352 determines one or more tasks for the person to perform within the environment during their transaction. Each task may include one or more specific item interactions for the person to perform. Generally, the task generation sub-module 352 may use information associated with the person, such as the personal profile 322 and the virtual transaction record 349, to generate tasks that are tailored to the person's interests or that are otherwise intended to influence the person's actions during the transaction.

The task generation sub-module 352 may also use item information 342 to determine the one or more tasks to be performed. Item information 342 includes location information 344, which may be used to select appropriate items to be included in the tasks. For example, based on the person's location in the environment, remaining items on his or her shopping list 337, etc., the task generation sub-module 352 may select items that are relatively close (e.g., within several feet, along the same aisle, etc.) to the location or to anticipated locations of the person. In this way, the tasks may be perceived as less inconvenient for the person. Generally, less inconvenience in the tasks may correlate to greater participation of persons in the rewards tasks.

In additional to personal information and item information, the tasks generated by the task generation sub-module 352 may also reflect other competing considerations, such as inventory information, incentive information, and initiatives. For example, an inventory management module 358 may operate to track inventory levels for the various items on display in the environment, as well as additional item inventory (say, located in nearby store rooms, warehouses, etc.) for restocking the environment, and ordering information to timely acquire additional items. The inventory management module 358 may include item expiration information 359 that may be used for item restocking, rotation, replacement, etc. as necessary. For example, the item expiration information 359 may be used to generate prompts for employees to locate and sort out expired or near expiring items from the rest of the items on display.

One or more incentives 360 may be available for promoting various items. Incentives 360 may have any suitable form, such as discounts, offers, rebates, etc. for the associated items. Incentives may originate from different sources, such as from the item manufacturer 361 and from the environment 362 (e.g., store-specific). In some cases, incentives may be available from different sources corresponding to the same item. To resolve any incompatibility between the different incentives, the incentives may be prioritized according to the source, the amount, etc. For example, incentives provided at the environment level may override any conflicting incentives from the item manufacturer. In another example, the “better” (i.e., greater amount) of the incentives may be given priority regardless of source.

One or more initiatives 364 may be used to promote various features associated with the environment. In one embodiment, a website initiative 365 may encourage a person to access a website related to the environment using their personal computing device. An example operation of a website initiative 365 is discussed below with respect to FIG. 7. The initiatives 364 may include one or more other features 366 that promote any desired aspects (virtual or physical) associated with the environment. For one example initiative, a corresponding task may require that the person access item information using a mobile computing app associated with the environment. In another example initiative, corresponding tasks may direct shoppers to visit a newly-remodeled section of the environment.

The generated tasks may be presented to the person using a suitable output device 370 located within the environment. For example, the tasks may be transmitted to a personal computing device that belongs to the person, or to a computer-based terminal disposed within the environment and suitably close to the person's location or along the person's anticipated route within the environment. The generated tasks may be presented to the person in a direct or an indirect manner. A direct presentation of the task could ask the person to interact with the specific item—for example, locate item x. However, an indirect presentation of the task may use descriptive information about the particular item, requiring the person to consider the descriptive information or to search a plurality of different items to find the particular item. For example, a task may require a person to locate an item having particular nutrition information 345. In some cases, the descriptive information may be in the form of a riddle or puzzle to be solved by the person prior to completion of the task. In some cases, using an indirect approach may increase the person's engagement with the rewards tasks and increase their overall willingness to participate.

In addition to associated items and behaviors, the generated tasks may also specify one or more criteria for task completion or for rewards scoring. Criteria may include a time element (e.g., perform this task within three minutes) and/or specific aspects of task execution (e.g., locate the item and capture an image of the associated labeling, barcode, etc.).

The evaluation sub-module 354 receives as input one or more of the generated tasks, as well as performance information based on acquired image information 346, and scores the performance of the tasks based on the performance information. In some embodiments, the evaluation sub-module 354 associates item and behavior information received from the image analysis module 348 to determine the item interaction. In other embodiments, the image analysis module 348 or the virtual transaction record 349 provides the determined item interaction to the evaluation sub-module 354. The determined item interaction is compared with the generated tasks to determine whether a particular task was completed, as well as whether it was performed according to prescribed criteria. The evaluation sub-module 354 may use any suitable algorithm(s) for scoring performance of the tasks.

The award sub-module 356 receives scoring information from the evaluation sub-module 354 assessing the person's performance of the task. The scoring information may be provided in any suitable fashion—an overall score of the task performance, component scores related to the prescribed performance criteria, and so forth. The award sub-module 356 receives the scoring information and determines a corresponding amount of awards to reward to the person's account. The particular task and the performance score may be combined in a predefined relationship to determine the amount of rewards, for example, according to any suitable equation. In some cases, the tasks may be given different weights depending on their relative importance, which may be determined using inventory information (e.g., a need to quickly sell the associated item), incentive information, initiative information, and so forth.

The award sub-module 356 may associate the determined amount of rewards with the person using the personal profile 322 and/or the virtual transaction record 349. The rewards may be applied by the person during the current transaction, or may accumulate for application during a later transaction. In some cases, the rewards may be tied to promotions outside the transaction and/or environment, such as a mailed rebate or an electronic promotion to an event.

FIG. 4 illustrates a method 400 of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment. The method 400 may generally be used in conjunction with the arrangement 300 described above.

Method 400 begins at block 405, where one or more tasks are generated for the person to complete during the transaction. The tasks are generated based on information included in the personal profile associated with the person, such as an item interaction history, personal preference information, health information, and prospective item information. Each task may relate to one or more item interactions, which associate items in the environment with certain predetermined behaviors.

At block 415, the one or more tasks are presented to the person using an output device within the environment. In some embodiments, the presentation may be provided to a personal computing device associated with the person (such as a smartphone or tablet). In some embodiments, the presentation may be provided to a computing device disposed within the environment, such as a terminal in the proximity of the person or along an anticipated path of the person through the environment.

At block 425, acquired image information is analyzed to evaluate the person's performance of the one or more presented tasks. The image information is acquired using one or more visual sensors disposed within the environment. In one or more embodiments, the analysis may be further based on input provided by other sensor devices or by the person through a user interface. In some embodiments, the evaluation may be binary—that is, does the image information (as represented in the determined item interaction) indicate that the person completed the task? In other embodiments, the evaluation may be based on one or more criteria—for example, performing the task correctly, performing the task within a prescribed window of time, within a predetermined time limit, and so forth.

At block 435, an amount of rewards is awarded to the person based on the evaluation. In some embodiments, the rewards are associated with the person's personal profile and/or the virtual transaction record (associated with the person's current transaction). The rewards may be redeemed during the current transaction or during a later transaction, consistent with the overall rewards system and the person's preferences (e.g., accumulating rewards for a later transaction).

FIG. 5 illustrates a method 500 of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment. The method 500 represents one possible implementation of the method 400, and may generally be used in conjunction with the arrangement 300 described above. In one embodiment, the method 500 represents an item-matching game available within the environment.

At block 505, at least one item is selected for a prospective task. In some embodiments, selection of the item is based on location information 510, such as person location information 512 and/or item location information 344. The person location information 512 may be provided directly or determined through image analysis of image information 346. Selecting an item closer to the person's location may cause the associated task to be perceived as less inconvenient by the person. In some embodiments, selection of the item may also be based on personal profile 322 information, such as the person's preferences 328 or prospective item information 336. For example, the system may more frequently select items with which the person has interacted or has a relative preference. In some embodiments, the prospective item information 336 may be used to suggest alternative items (e.g., a different brand of an item included on a shopping list, or a suitable substitute item) to the person.

At block 515, descriptive information for the item is selected. In some cases, the descriptive information may include merely identification information (i.e., a unique name, size, etc.) for the item. In some cases, however, descriptive information may include attributes or other qualities of the item, such as nutrition information, without providing unique identification information. In some embodiments, the amount of descriptive information included with a task is adaptive, based on the person's preferences and/or other task generation considerations such as incentives, inventory, initiatives, and so forth. Blocks 505 and 515 may be repeated as desired—e.g., as part of determining a plurality of tasks for the person to perform.

At block 525, a task including the selected descriptive information is presented to the person. In some embodiments, a single task is presented at block 525. In other embodiments, more than one task is presented (e.g., a checklist). The presented task may be selected from a plurality of determined tasks for the person. In some embodiments, the task is presented to the person using a personal computing device. In some embodiments, the task is presented using a computing device disposed within the environment, such as a terminal located near the person's location.

At block 535, acquired image information is analyzed to determine one or more item interactions performed by the person. At block 540, the item interactions are evaluated to determine whether any match the task. If at least one match is determined (“YES”) the method proceeds to block 545, where performance of the task is evaluated according to one or more criteria. However, if no matches are determined (“NO”), the method returns to block 535 to continue analysis of image information.

At block 555, the rewards for the person are updated based on the evaluation of task performance. The rewards may be maintained as part of the personal profile and/or a virtual transaction record for the current transaction. The grouping of blocks 535, 540, 545, and 555 may be generally referred to as a subroutine 565.

At block 560, the method determines whether all generated tasks have been completed. If complete (“YES”), the method ends. However, if not complete (“NO”), the method returns to one of block 525 and 535, depending generally on whether multiple tasks were presented to the person. If multiple tasks were presented at once to the person (e.g., as a checklist), the method may return to block 535 to continue analysis of image information. However, if only a single task was presented to the person at the first instance, a next task is presented to the user when the method returns to block 525.

FIG. 6 illustrates a method 600 of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment. The method 600 represents one possible implementation of the method 400, and may generally be used in conjunction with the arrangement 300 described above. In one embodiment, the method 600 represents an expired items game available within the environment.

Method 600 begins at block 605, where the system determines that one or more expiring items have either reached their expiration date or are nearing their expiration date. The determination may be based on information available through inventory management module 358, such as the item expiration information 359. A retailer or other provider (e.g., an item manufacturer) may generally wish to remove expiring items from display as customers or shoppers may perceive

At block 615, a task involving at least one of the expiring items of block 605 is presented to the person during a transaction. The task (i.e., the selected item and/or associated behavior) may be selected for the person based on personal profile 322 information, such as preferences 328 and/or prospective item information 336. For example, given two different types of expiring items, one type of which the person does not prefer (i.e., a negative preference), the system may tend to select the other type to present as part of the task. The task may further be based on location information 510 to reduce any inconvenience for the person who is to perform the task.

Generally, the task may include locating an expiring item and/or sorting the expiring item from other non-expiring items. In some cases, the task may be associated with a discount on purchasing the expiring item. By incentivizing customers or shoppers to locate the expiring items, the retailer or environment administrator may not need to send an employee to perform the same task.

At block 625, subroutine 565 is performed. As discussed above, the subroutine 565 generally includes analyzing image information, determining a match with the presented task, evaluating performance of the task, and updating rewards based on the evaluation. At an optional block 630, the system determines whether the presented task item had been sorted from other items, but not selected by the person. For example, the person may have located the expiring item consistent with the presented task, but did not remove the item as he or she did not intend to purchase the item. In this case, the retailer or environment administrator may not wish to leave the expiring item in place, but may remove the item to avoid selection by other shoppers. Accordingly, if the item was sorted but not selected (“YES”), at block 635 the system may notify an employee to collect the sorted item.

In an alternative embodiment, the presented task may prescribe a placement of the expiring (but not yet expired) item, to improve the likelihood that the expiring item is selected prior to its expiration date. For example, an expiring item located near the bottom of a stack of items may be located by the person and placed near the top of the stack, so that the item is more visible and may be more likely to be selected by other shoppers.

FIG. 7 illustrates a method 700 of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment. The method 700 represents one possible implementation of the method 400, and may generally be used in conjunction with the arrangement 300 described above. In one embodiment, the method 700 represents an online services game available within the environment.

Method begins at block 705, where a task is presented involving one or more initiatives and one or more items. The initiatives 364 may specify one or more physical or virtual features associated with the environment, such as website features, mobile app features, etc.

The associated item for the task may be selected based on personal profile 322 information, such as prospective item information 336 and other information 340. In some cases, the associated item for the task may be selected from prospective items included in the prospective item information 336. For example, say the initiative relates to using a mobile computing app to research an item or view a comparison of items. One associated task may be acquiring image information of an item using a mobile computing device; the app then loads the information related to the item for viewing by the person (i.e., the feature highlighted in the initiative). Here, the system may select an item for the task based on items that the person has included in a shopping list but has not yet selected for purchase (e.g., by removing from display and placing in a shopping receptacle). This information may be reflected in the virtual transaction record 349. Another example of a task is accessing a web page associated with an item that is already selected or expected to be selected by the person (say, based on prospective item information 336, purchase history, etc.). The task may require that the person transmit a link to the page (or other content from the page) to a computing device associated with the environment (such as server 265).

By selecting items for a task in which the person may already be interested, and by integrating the task into an action that the person is expected to perform (e.g., selecting an item on a shopping list), the level of participation in initiatives and other rewards tasks may generally be increased.

The other information 340 may include initiatives participation 710 information, which reflects the person's participation in various initiatives. For example, the system may determine not to present a task relating to an initiative which the person has previously participated in. In one embodiment, the initiatives participation 710 may be as simple as single data bits indicating whether the person has participated or not. Of course, the initiatives participation may include more in-depth information about the nature of the participation, items involved, etc.

At block 715, subroutine 565 is performed. As discussed above, the subroutine 565 generally includes analyzing image information, determining a match with the presented task, evaluating performance of the task, and updating rewards based on the evaluation. Of note, the acquired image information may be acquired as part of the person's performance of the task—such as capturing an image of the item included in the presented task—or perhaps reflected in image information that includes the person manipulating the computing device to perform the task.

FIG. 8 illustrates a method 800 of providing rewards to a person based on item interactions during a transaction in an environment, according to one embodiment. The method 800 represents one possible implementation of the method 400, and may generally be used in conjunction with the arrangement 300 described above. In one embodiment, the method 800 represents a profile matching game available within the environment.

Method 800 begins at block 805, where an entry is determined from a shopping list 337 of a person's personal profile 322. In an alternative embodiment, other prospective item information associated with the personal profile 322 may be substituted for the shopping list. In some embodiments, the shopping list entry may correspond directly to an item in the environment—for example, exactly matching an item brand, name, size, etc. In other embodiments, the shopping list may describe one or more items generically without including the unique identification information—for example, an entry including “soda” instead of a more specific intended item, such as a six-pack of 12-ounce cans of Coca-Cola®. Alternatively, an item may be specifically included in the shopping list entry, but is out of stock in the environment.

At block 815, the system determines a categorical grouping corresponding to the entry. For example, for an entry of “lettuce,” some possible categorical groupings include ^“green vegetables,” “leafy greens,” “vegetables,” etc. The most pertinent categorical grouping may be determined using profile information and/or the virtual transaction record—for example, the selection of other vegetables (e.g., carrots, celery, cucumbers, tomatoes) during the transaction may indicate that the person is purchasing items to assemble a salad. As a number of different vegetables have been selected in this example, an appropriate grouping for the lettuce entry may be narrower than merely “vegetables” or “green vegetables” categories. Assume for the purposes of this example that the system determines “leafy greens” to be the best categorical grouping. The example leafy greens category may encompass a plurality of different items—different varieties of lettuce, spinach, kale, collards, Swiss chard, cabbage, Brussels sprouts, etc. Each of the plurality of items may have different qualities or characteristics, such as nutrition information, which may be comparatively ranked relative to one or more criteria.

At block 825, a task involving the grouping is presented to the person. The task may be presented relative to the one or more criteria, which may be explicitly included or deduced from the personal profile 322. The criteria may be based on health information 332, such as nutrition goals 334 and/or fitness goals 335. The task may further be based on inventory and/or incentive information, such as a need to sell certain items.

Continuing the earlier example, say one of the person's nutrition goals 334 is increasing daily potassium intake. Each of the plurality of items in the “leafy greens” category may have a differing amount of potassium content. Thus, the items may be given a relative ranking according to their potassium content—e.g., spinach as having the most potassium, Swiss chard second-most, kale third-most, and so forth. Of course, a combination of multiple criteria may be used to rank the categorical items; the criteria may be weighted as part of determining scoring for each of the items.

Presenting the task to the person may include directing the person to find the item within the categorical grouping that best matches one or more criteria. In the example, the task may prompt the person to locate the leafy green vegetable having the highest potassium content.

At block 835, subroutine 565 is performed. As discussed above, the subroutine 565 generally includes analyzing image information, determining a match with the presented task, evaluating performance of the task, and updating rewards based on the evaluation. In this case, evaluating the person's performance is based on which item the person selects from the categorical grouping. For example, the person might receive a largest score for selecting the spinach, and lesser scores for selecting one of the other types of leafy greens. In some embodiments, the system may present the “best” choice to the person after the person's item selection has been made, in order to improve their understanding and item selection abilities.

At block 840, the system determines whether additional entries remain on the shopping list. If so (“YES”), the method returns to block 805. Accordingly, the profile matching game may be implemented as an incremental game, adapting the task and/or scoring based on the person's selection of the previous item. Based on the item selected from a first grouping, the system assess how the selected item affects nutrition goals, fitness goals, etc. included in the personal profile, and may adapt the next task accordingly. For example, if the person selects the leafy greens item corresponding to the highest potassium content, evaluation of subsequent shopping list entries may lessen the relative importance of the items' potassium content (e.g., adjusting relative weighting) in favor of other criteria. The system may further suggest one or more items (not included on the shopping list) based on the person's selections, whether to complement the selected items or to compensate for deficiencies of the selected items.

The descriptions of the various embodiments of the present disclosure have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

In the preceding, reference is made to embodiments presented in this disclosure. However, the scope of the present disclosure is not limited to specific described embodiments. Instead, any combination of the following features and elements, whether related to different embodiments or not, is contemplated to implement and practice contemplated embodiments. Furthermore, although embodiments disclosed herein may achieve advantages over other possible solutions or over the prior art, whether or not a particular advantage is achieved by a given embodiment is not limiting of the scope of the present disclosure. Thus, the following aspects, features, embodiments and advantages are merely illustrative and are not considered elements or limitations of the appended claims except where explicitly recited in a claim(s). Likewise, reference to “the invention” shall not be construed as a generalization of any inventive subject matter disclosed herein and shall not be considered to be an element or limitation of the appended claims except where explicitly recited in a claim(s).

Aspects of the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module,” or “system.”

The present disclosure may be a system, a method, and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure.

The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.

Computer readable program instructions for carrying out operations of the present disclosure may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

Aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.

These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.

Embodiments of the disclosure may be provided to end users through a cloud computing infrastructure. Cloud computing generally refers to the provision of scalable computing resources as a service over a network. More formally, cloud computing may be defined as a computing capability that provides an abstraction between the computing resource and its underlying technical architecture (e.g., servers, storage, networks), enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. Thus, cloud computing allows a user to access virtual computing resources (e.g., storage, data, applications, and even complete virtualized computing systems) in “the cloud,” without regard for the underlying physical systems (or locations of those systems) used to provide the computing resources.

Typically, cloud computing resources are provided to a user on a pay-per-use basis, where users are charged only for the computing resources actually used (e.g., an amount of storage space consumed by a user or a number of virtualized systems instantiated by the user). A user can access any of the resources that reside in the cloud at any time, and from anywhere across the Internet. In context of the present disclosure, a user may access applications (e.g., a retail store app for a mobile computing device) or related data (e.g., compiled shopping data) available in the cloud. Doing so allows a user to access this information from any computing system attached to a network connected to the cloud (e.g., the Internet).

While the foregoing is directed to embodiments of the present disclosure, other and further embodiments of the disclosure may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.

Claims

1. A computer-implemented method of providing rewards to a person based on item interactions during a transaction in an environment, the person associated with a personal profile, the method comprising:

generating, based on information in the personal profile, one or more tasks for the person to complete during the transaction, each task including at least one item interaction;

presenting, using an output device within the environment, the one or more tasks to the person;

analyzing image information acquired by one or more visual sensors within the environment to evaluate the person's performance of the one or more tasks; and

awarding, based on the evaluation, an amount of rewards to the person.

2. The method of claim 1, wherein the amount of rewards are applied to one of the personal profile and a virtual transaction record reflecting the person's item interactions during the transaction.

3. The method of claim 1, wherein the information in the personal profile includes one or more of an item interaction history, item preferences, health information, prospective item information for the transaction, and participation information for one or more initiatives.

4. The method of claim 1, wherein generating the one or more tasks is further based on one or more of item incentive information, initiative information, and item inventory information.

5. The method of claim 4, wherein the item inventory information indicates a first item nearing a corresponding expiration date, and wherein at least one task includes the person locating the first item.

6. The method of claim 1, wherein the one or more tasks includes locating a selected item, wherein presenting the one or more tasks includes providing descriptive information about the item without explicitly identifying the item.

7. The method of claim 1, wherein generating the one or more tasks includes:

determining an entry of a shopping list included in the personal profile; and

determining a categorical grouping that corresponds to the entry and that includes a plurality of items,

wherein the one or more tasks are presented with respect to the determined grouping, and wherein evaluating the performance of the one or more tasks is based on which of the plurality of items is involved in the corresponding item interaction.

8. A computer program product of providing rewards to a person based on item interactions during a transaction in an environment, the person associated with a personal profile, the computer program product comprising:

a computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by one or more computer processors to perform an operation that includes: generating, based on information in the personal profile, one or more tasks for the person to complete during the transaction, each task including at least one item interaction; presenting, using an output device within the environment, the one or more tasks to the person; analyzing image information acquired by one or more visual sensors within the environment to evaluate the person's performance of the one or more tasks; and awarding, based on the evaluation, an amount of rewards to the person.

9. The computer program product of claim 8, wherein the amount of rewards are applied to one of the personal profile and a virtual transaction record reflecting the person's item interactions during the transaction.

10. The computer program product of claim 8, wherein the information in the personal profile includes one or more of an item interaction history, item preferences, health information, prospective item information for the transaction, and participation information for one or more initiatives.

11. The computer program product of claim 8, wherein generating the one or more tasks is further based on one or more of item incentive information, initiative information, and item inventory information.

12. The computer program product of claim 11, wherein the item inventory information indicates a first item nearing a corresponding expiration date, and wherein at least one task includes the person locating the first item.

13. The computer program product of claim 8, wherein the one or more tasks includes locating a selected item, wherein presenting the one or more tasks includes providing descriptive information about the item without explicitly identifying the item.

14. The computer program product of claim 8, wherein generating the one or more tasks includes:

determining an entry of a shopping list included in the personal profile; and

determining a categorical grouping that corresponds to the entry and that includes a plurality of items,

wherein the one or more tasks are presented with respect to the determined grouping, and wherein evaluating the performance of the one or more tasks is based on which of the plurality of items is involved in the corresponding item interaction.

15. A system of providing rewards to a person based on item interactions during a transaction in an environment, the person associated with a personal profile, the method comprising:

one or more computer processors;

at least a first visual sensor disposed within the environment and communicatively coupled with the one or more computer processors; and

a memory containing program code which, when executed by the one or more computer processors, performs an operation that includes: generating, based on information in the personal profile, one or more tasks for the person to complete during the transaction, each task including at least one item interaction; presenting, using an output device within the environment, the one or more tasks to the person; analyzing image information acquired by one or more visual sensors within the environment to evaluate the person's performance of the one or more tasks; and awarding, based on the evaluation, an amount of rewards to the person.

16. The system of claim 15, wherein the amount of rewards are applied to one of the personal profile and a virtual transaction record reflecting the person's item interactions during the transaction.

17. The system of claim 15, wherein the information in the personal profile includes one or more of an item interaction history, item preferences, health information, prospective item information for the transaction, and participation information for one or more initiatives.

18. The system of claim 15, wherein generating the one or more tasks is further based on one or more of item incentive information, initiative information, and item inventory information.

19. The system of claim 18, wherein the item inventory information indicates a first item nearing a corresponding expiration date, and wherein at least one task includes the person locating the first item.

20. The system of claim 15, wherein generating the one or more tasks includes:

determining an entry of a shopping list included in the personal profile; and

determining a categorical grouping that corresponds to the entry and that includes a plurality of items,

wherein the one or more tasks are presented with respect to the determined grouping, and wherein evaluating the performance of the one or more tasks is based on which of the plurality of items is involved in the corresponding item interaction.