Quantifying carbon compensation by encouraging reuse of functional articles as decorative articles

Abstract

Systems and techniques are described herein for quantifying carbon compensation by encouraging reuse of a functional article as a decorative article. A unique visual art form created by a user that incorporates at least one consumer product package is received. A digital record is created for the unique visual art form in a computer database. The digital records include at least one first record of art loop events performed based on receiving the unique visual art form. A value is assigned to the art loop event based on an evaluation of visual elements present in the unique visual art form. And adding an amount equal to the value to the account balance of the user.

Description

Cross Reference to Related Applications

[0001] This application claims the benefit of priority from U.S. Provisional Patent Application Serial No. 63 / 500,410, filed May 5, 2023, entitled “QUANTIFYING CARBON OFFSET THROUGH INCENTIVIZING REUSE OF FUNCTIONAL ITEMS AS A DECORATIVE ITEM,” the disclosure of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] Embodiments described herein relate generally to carbon emissions management, and in some embodiments, more specifically to a portal for users to submit images of artcycle works made from discarded packaging, and to provide rewards as a reward for committing not to dispose of the artcycle works. BACKGROUND

[0003] Product packaging protects the enclosed product during storage, shipping, and handling, and also provides a backing for providing product information. When the end user opens the product packaging, the packaging is typically discarded. This means that in the best-case scenario, the packaging is taken to a sanitary landfill or recycling facility. Both landfilling and recycling operations emit byproducts, such as gases, residual, etc. Artcycle is a technique of reusing waste in an art installation as an artistic expression by an artist. BRIEF DESCRIPTION OF DRAWINGS

[0004] In the drawings, which are not necessarily drawn to scale, like numerals describe similar components throughout the several views. Like numerals having different letter suffixes can represent different instances of the like components. The drawings illustrate various embodiments discussed in the document, by way of example, not by way of limitation.

[0005] Figure 1 Examples of a process for data collection for improving and quantifying carbon offset through incentivizing reuse of functional items as decorative items, according to embodiments, are illustrated.

[0006] Figure 2A 、 2B Examples of bottles for achievable artcycle for improving and quantifying carbon offset through incentivizing reuse of functional items as decorative items, according to embodiments, are illustrated in 2C and 2D.

[0007] Figure 3An example of a process for a portal to improve and quantify carbon offset by incentivizing the reuse of functional items as decorative items according to embodiments is shown.

[0008] Figure 4 An example of a process for a portal to improve and quantify carbon offset by incentivizing the reuse of functional items as decorative items according to embodiments is shown.

[0009] Figure 5 An example of a method for improving and quantifying carbon offset by incentivizing the reuse of functional items as decorative items according to embodiments is shown.

[0010] Figure 6 is a block diagram that shows an example of a machine upon which one or more embodiments can be implemented. DETAILED DESCRIPTION

[0011] Reference will now be made in detail to some aspects of the disclosed subject matter, examples of which are illustrated in the accompanying drawings. While the disclosed subject matter will be described in conjunction with the enumerated claims, it will be understood that the enumerated claims are not intended to limit the claims to the disclosed subject matter.

[0012] Throughout this document, values expressed in a range format should be interpreted in a flexible manner to include not only the numerical values explicitly recited as the limits of the range, but also to include all the individual numerical values or sub-ranges encompassed within that range as if each numerical value and sub-range is explicitly recited. For example, a range of "about 0.1 % to about 5%" or "about 0.1 % to 5%" should be interpreted to include not only about 0.1 % to about 5%, but also the individual values (e.g., 1 %, 2%, 3%, and 4%) and the sub-ranges (e.g., 0.1 % to 0.5%, 1.1 % to 2.2%, 3.3% to 4.4%) within the indicated range. The statement "about X to Y" has the same meaning as "about X to about Y," unless otherwise indicated. Likewise, the statement "about X, Y, or about Z" has the same meaning as "about X, about Y, or about Z," unless otherwise indicated.

[0013] In the present document, the terms “a” or “an”, or the term “the” are used to include one or more than one, unless the context clearly dictates otherwise. The term “or” is used in the inclusive sense, unless the context clearly dictates otherwise. The statement “at least one of A and B” or “at least one of A or B” has the same meaning as “A, B, or A and B.” Additionally, it is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Any use of section headings is intended to aid reading the present document and is not to be interpreted as limiting; information that is relevant to a section heading can occur within or outside of that particular section. A comma can be used as a delimiter to the left or right of a decimal point or as a number separator; for example, “0.000,1” is equivalent to “0.0001.” All publications, patents, and patent documents cited in the present document are incorporated by reference in their entirety for all purposes to the same extent as if each individual publication, patent, or patent document were individually so incorporated; in the event of inconsistent usages between this document and those documents so incorporated, the usages in the incorporated references should be considered supplementary to that of this document; for irreconcilable inconsistencies, the language in this document prevails.

[0014] In the methods described herein, the acts can be carried out in any order unless explicitly claimed otherwise or the context clearly indicates otherwise. Additionally, specified acts can be carried out concurrently unless explicitly claimed otherwise or the context clearly indicates otherwise. For example, the act of doing X claimed in claim 1 and the act of doing Y claimed in claim 1 can be carried out concurrently in a single operation, and thus the process as it occurs would fall within the literal scope of the claimed process.

[0015] As used herein, the term“about” can allow for a degree of variability in a value or range, for example, within 10%, within 5%, or within 1% of a stated value or of a stated limit of a range, and includes the exact stated value or range. As used herein, the term“substantially” means a majority or a substantial part, such as at least about 50%, 60%, 70%, 80%, 90%, 95%, 96%, 97%, 98%, 99%, 99.5%, 99.9%, 99.99%, or at least about 99.999% or more, or 100%. As used herein, the term“substantially free of’ can mean free of or having trace amounts of such that the amount of material present does not affect the material properties of a composition including the material, such that about 0 wt% to about 5 wt% of the composition is the material, or about 0 wt% to about 1 wt%, or about 5 wt% or less, or less than or equal to about 4.5 wt%, 4 wt%, 3.5 wt%, 3 wt%, 2.5 wt%, 2 wt%, 1.5 wt%, 1 wt%, 0.9 wt%, 0.8 wt%, 0.7 wt%, 0.6 wt%, 0.5 wt%, 0.4 wt%, 0.3 wt%, 0.2 wt%, 0.1 wt%, 0.01 wt%, or about 0.001 wt% or less, or about 0 wt%.

[0016] The methods and systems discussed herein increase the rate of art cycling and / or carbon offsetting by providing incentives to transform objects that would normally be disposed of or recycled into art cycling works. The incentives encourage individuals to participate in reducing carbon footprints. The methods and systems discussed herein provide a number of benefits, including reducing costs associated with waste collection and art cycling and increasing collection efficiency. The methods and techniques discussed herein enable marketing channels for participating retailers to establish value by being good corporate citizens. U.S. Patent No. 10,318,960 generally describes methods and systems for improving recycling by using financial incentives. Conventional techniques for consumer-generated art using brand assets can use non-fungible tokens (NFTs). However, NFT generation and management incur environmental costs associated with computing resources used to generate the NFTs. See, e.g., https: / / www.packaginginsights.com / news / non-fungible-tokens-crypto-art-cycling-propels-packaging-design-into-digital-ownership-age.html.

[0017] The systems and techniques discussed herein provide a stackable bottle system that creates a unique substrate for art cycle artistic expression and minimizes waste and energy consumption associated with art cycles or discarding used packaging while promoting new support for creating art and facilitating art cycles. In examples, a series of interlocking bottles can be used as individual artistic elements or combined to make a substantially continuous surface that becomes a durable and unique art cycle work for a consumer while minimizing waste associated with empty containers. A digital representation of the art cycle work can be used to create NFTs, carbon offsets, etc.

[0018] In examples, the bottles can be blank or decorated with individual artistic expressions. The bottles can be stacked based on a combination of images and image orientations determined by the order and orientation of the stack to create various visual effects. Artists transform the unique visual effects created by the individuals and / or bottles into art cycle outputs that can be used as standalone themes or paired with other visual elements to create art cycle composite works that are unique to the creator.

[0019] In examples, the geometry and glass distribution of the bottles can be specifically designed to provide a glass wall or glass canvas when assembled to allow for art cycle expression on a vertical flat surface.

[0020] In some example embodiments, individual art cycle physical works can be created and assigned a value. In some example embodiments, derivative works of the art cycle physical works (e.g., digital impressions, etc.) can be created, e.g., using a digital camera. Digital impressions of the individual art cycle physical works can be uploaded to a portal. The portal enables the digital version of the work to be incorporated into the metaverse (e.g., as an avatar, etc.). The digital version can be used to create an NFT associated with the digital version of the work. The portal enables creators to create carbon offsets based on including packaging into an art cycle work and committing to keep the packaging as part of the art cycle work rather than disposing of the work as a recyclable or waste. The portal enables creators to participate in contests that are limited to people who have created an art cycle composite work.

[0021] Art valuation involves unique challenges and opportunities in identifying the digital landscape in internet-based information exchange. The internet has fundamentally changed the way information is disseminated and consumed, and this shift extends to the art market. Enabling internet-centric art valuation systems presents several technical challenges. The internet provides a vast amount of data ranging from auction results and gallery exhibitions to social media trends and online art critiques, resulting in data overload. Sifting through the large volume of data to find relevant and reliable information for art valuation can be challenging for humans. Determining the provenance and authenticity of art pieces is more complex when transactions and exhibitions take place online. The risk of fraud and misrepresentation increases, and without a system that digitally verifies art pieces using features that are imperceptible to humans but perceptible to specialized computing systems, the credibility of online art valuation will be compromised. While the internet provides access to global art markets, it also leads to market fragmentation due to differences in platforms and standards. This can result in inconsistent valuations and make it difficult to compare art pieces across different platforms without the objectivity and consistency provided by specially programmed computing devices. Influenced by viral content and social media, online trends can quickly shift. Art valuation can become unstable, responding quickly to online hype rather than intrinsic artistic value.

[0022] To address these challenges, several internet-centric solutions can be implemented. Big data analysis and AI can be used to process and analyze large data sets from various online sources to derive meaningful insights for art valuation. This helps filter out noise from valuable data, providing a more accurate and comprehensive basis for valuation. Blockchain technology can be implemented to create tamper-proof ledgers of art pieces’ provenance and transaction history (e.g., records, etc.) to enhance transparency and trust in online art transactions, supporting more reliable valuations. A centralized platform can be developed that aggregates data from various sources and standardizes the art valuation process across different markets to reduce market fragmentation and provide a consistent framework for comparing and valuing art globally. Real-time data from social media and other online platforms can be analyzed using machine learning models to gauge public sentiment and trends, allowing valuations to dynamically adapt to changing trends while maintaining a balance between market demand and intrinsic artistic value. An interactive platform can be created that enables art enthusiasts, collectors, and experts to contribute to and participate in the valuation process, democratizing art valuation to incorporate a broader range of perspectives and reduce bias.

[0023] Both challenges and solutions are closely intertwined with digital technology. Leveraging these technologies as described herein enables art valuation to be more transparent, accurate, and democratic, consistent with the global and interconnected nature of the modern art market.

[0024] Rather than using brand assets to create NFTs that are unique to the creator, the methods and systems discussed herein implement the unique ability to leverage quantified carbon offsets created by keeping the packaging, thereby avoiding the carbon cost of discarding or recycling the packaging (e.g., glass containers, etc.), to offset the cost of generating the NFT, and to offset the carbon cost of manufacturing the product (e.g., fragrance, etc.) contained in the packaging.

[0025] In examples, art cycle data is evaluated using collection and statistical analysis techniques. Evaluating art cycle data enables various benefits, including: monitoring compliance with applicable laws, extracting trends from the consumer population, long-term planning, performance analysis, and standardization of city subsidy applications.

[0026] In examples, tracking and analysis of carbon footprints is used to create the bottle, the fragrance contained in the bottle, and / or marketing and sales activities associated with marketing and selling the bottle, in order to design and implement effective strategies to increase art cycling. Data collection and analysis enables officials in all sectors of the economy to identify and respond to trends at the micro and macro levels by:

[0027] Effectiveness of art cycling projects is accurately measured on a geographic basis (e.g., by collected tons, art cycling rate, participation rate, etc.).

[0028] Detailed data is provided that describes the effectiveness of art cycling projects. For example, by matching carbon offsets attributed to a project or art cycling creation, the route collection system can be optimized to help.

[0029] Effectiveness of art cycling projects at the household collection level is managed so that marketing activities can be designed to maximize the adoption and use of art cycling.

[0030] The amount of material saved by the original product purchaser rather than thrown away or recycled can be analyzed in conjunction with existing art cycling data, waste management, production of packaging or fragrance, generation of NFTs, etc., thereby providing accounting of energy use and economic activity. Information about the environmental impact of various named activities can be quantified, tangible proof of the benefits of art cycling certain materials can be generated to encourage the reduction of the overall carbon footprint.

[0031] Data related to art cycling is managed using a database system that includes inputs for receiving information from generated art cycling items. For example, data can be collected and stored in a database related to NFTs generated from physical art cycling items. The information can include a collection of source identifications and associated amounts of recycling. The database system can produce such information as: a geographic analysis module for analyzing geographic art cycling patterns of respective households; a historical analysis module for analyzing temporal trends of art cycling for one or more respective households; a value analysis module for analyzing valuations of certain art cycling items and related NFTs made by various art cycling artists; and an incentive response module for determining responsiveness of respective households to art cycling incentives.

[0032] In an example, a unique reward program is provided that enables economic incentives to be provided to households to increase their art cycling rates. Art cycling containers are matched to individuals by providing an identifier such as a machine-readable code (e.g., a barcode, a radio frequency identification (RFID) tag, etc.) on the container to associate the container with an individual (e.g., based on purchase, acquisition, etc.). The value of art cycling objects and related artistic expressions are valued by an index or algorithm (by way of example and not limitation, “Jerry Gogsian’s Recommended Focus”), and a monetary value is assigned to the art cycling objects. The owner or creator of the art cycling objects has an opportunity to create a digital version of the art cycling objects (e.g., an NFT, etc.). The record of art cycling objects and the quantity of particular objects (e.g., one or more stackable fragrance bottles, etc.) are converted into a credit amount (e.g., “ArtCycle Dollars,” etc.), and the credit amount is deposited into an account associated with the household. The household can redeem the credits in their account for goods, services, coupons for goods or services, other benefits or discounts, for example, at participating retailers, as carbon offsets for manufacturing, selling, and / or distributing fragrances, fragrance packaging, art cycling NFT generation, etc. The household can view their account and view information such as dates of their art cycling activities, amounts recycled over a given time period, the number of credits they have earned for art cycling, particular art cycling activities, the total amount of credits in their account, their shopping history and credits, etc. The household can also order credits for use in shopping at participating retailers.

[0033] A database and algorithm are used to assign a value to the art cycle and recycling amount for a household. The assigned value can be a financial (e.g., monetary, economic, etc.) value. The database and algorithm enable different reward rates to be applied to the art cycle flexibly by household, street, town, city, state, etc. to ensure the best impact on households to be incentivized. For example, a household can view their art cycle data on an internet website that converts the amount of recycled material into a value and allows them to redeem the value for goods, services, coupons for goods or services, and / or other benefits or discounts.

[0034] In an example, a unique visual art form incorporating at least one consumer product package created by a user can be formed. A representation of the unique visual art form can be transmitted to a server. The server can access a package database containing data about the carbon footprint of the package. A first value (F) can be generated that is a representation of the carbon footprint of the at least one consumer product package used to form the unique visual art form. In an example, to establish the carbon footprint value (F), the server accesses a database containing detailed information about the carbon footprint of various consumer product packages. This data can include emissions associated with the production, transportation, and disposal of the package. The particular consumer product package used in the artwork is identified. This can be done manually by the artist or automatically through image recognition technology in the server. For each identified package, the corresponding carbon footprint data is retrieved from the database. The total carbon footprint value (F) of the artwork is calculated by summing the carbon footprints of all the packages used in the artwork. This value represents the environmental impact in terms of carbon emissions.

[0035] A digital record of the representation can be created. The digital record can include at least one first record of an art cycle event made based on receiving the unique visual art form. The at least one first record can include: a first indication of the art cycle event indicating a time of creation of the unique visual art form; a second indication of the art cycle event indicating a commitment not to recycle or dispose of the at least one consumer product package incorporated into the unique visual art form; a visual depiction of the art cycle event; and the first value.

[0036] A second value (S) can be assigned to the record based on an evaluation of elements present in the unique visual art form (S). In an example, the second value (S) is determined based on an evaluation of various elements present in the artwork. These elements can include artistic quality, creativity, use of materials, thematic expression, integration of sustainable practices, etc. A scoring system can be established to assess these elements. This can involve ratings by art critics, public voting, or assessment of the artwork sustainability aspects by environmental experts. Based on the evaluation, a score or value is assigned to the artwork, reflecting its artistic and environmental significance. The score can be influenced by how effectively the artwork uses recycled materials, promotes sustainability messages, or innovates in material reuse.

[0037] A third value (T) can be generated from the first and second values. The third value is represented by the equation: (T) = WF * (F) + WS * (S). WF and WS represent weights associated with the first value (F) and the second value (S), and 0 ≤ WF, WS ≤ 1. The third value (T) is assigned to the digital record to generate a unique representation of the visual art form.

[0038] The formula (T = WF x F + WS x S) is used to integrate the calculated values F (carbon footprint) and S (art and environmental evaluation). WF and WS are predefined weights that determine the relative importance of the carbon footprint versus the art / environment score in the final valuation of the artwork. The resulting value T provides a comprehensive measure that reflects both the environmental impact and the artistic value of the artwork. This quantification process not only helps to assess the environmental impact of the materials used, but also encourages more environmentally conscious artistic practices by integrating artistic value to promote a holistic view.

[0039] Machine learning (ML) can be used to enhance the scoring system and the assignment of scores in the context of evaluating art, particularly when complex criteria such as artistic quality and environmental impact are involved, which can be subjective if strictly judged by humans. Machine learning algorithms can be less susceptible to emotional or environmental factors that can cause human raters to deviate. Machine learning algorithms can analyze images or descriptions of art to extract relevant features. These features can include: visual elements (e.g., color, texture, shape, composition, etc.), material identification (e.g., identifying the type of consumer product packaging used, etc. by image recognition techniques), thematic elements (e.g., presence of themes related to sustainability or environmentalism in the art, etc.). A dataset is prepared for efficient use of ML, which includes instances of art and their manually scored evaluations (e.g., assessments of carbon footprint and art / environmental value, etc.). This dataset is used as training data. A machine learning model is trained against the dataset. The model learns to associate the extracted features with scores assigned by human experts. Different types of ML models can be used, including, by way of example and not limitation, regression models (for continuous score prediction), classification models (in cases where scores are classified into discrete categories (e.g., high, medium, low), etc.

[0040] Once trained, the ML model can predict scores for new art based on the features. This automated scoring can contribute to measurability (e.g., fast scoring of large quantities of art, etc.) and consistency (e.g., reduction of human bias or variability in scoring, etc.). The system can be designed to incorporate a feedback mechanism, where the predicted scores are periodically reviewed and corrected by human experts. This feedback can be used to retrain and improve the ML model, enhancing its accuracy and reliability over time.

[0041] For carbon footprint (F), ML can help predict environmental impact based on historical data of similar materials used in other art. The prediction model can estimate emissions based on factors such as material type, quantity, and processing methods used. Machine learning can also be used to perform more complex analyses, such as identifying trends in material usage, predicting future sustainability trends for art, or analyzing the impact of certain materials or practices over time. To calculate the carbon footprint of an artwork, especially one that incorporates consumer product packaging or other materials, ML can be used to perform a more detailed analysis of various factors. Because different materials have different environmental impacts, additional features can be extracted and considered to enhance the accuracy of the carbon footprint calculation, including material composition, which can include material type. For example, plastics generally have a higher carbon footprint than biodegradable materials. The material composition feature can include the quantity of each material, which represents the amount of each material used that can impact the total carbon footprint.

[0042] Material source characteristics representing the content of recycling can be extracted, as recycled materials generally have a lower carbon footprint compared to new materials. Material source characteristics can also include geographic origin, as the distance a material travels from its point of origin to the artist’s studio can impact the carbon footprint due to transportation emissions.

[0043] Manufacturing process characteristics can be extracted, including energy consumption to represent the amount of energy used in the production of the material, and the type of energy used indicating whether it is from renewable sources or fossil fuels that can impact the carbon footprint.

[0044] Transportation characteristics can be extracted, including transportation modes to reflect that different modes (e.g., air, sea, road) have different emission profiles, and transportation efficiency to reflect that bulk shipping, for example, can reduce the carbon footprint per unit compared to individual shipping.

[0045] Use phase characteristics representing the durability of the material can be extracted, as more durable materials can result in a lower footprint over time if the artwork lasts longer and reduce the need for replacement materials and required maintenance, as some artworks can require energy or additional materials for maintenance, thereby impacting their overall environmental impact.

[0046] End-of-life characteristics can be extracted, including disposal methods indicating whether the material is disposed in a landfill, recycled, or composted, which can impact the total carbon footprint and biodegradability to reflect that biodegradable materials can have a lower environmental impact at the disposal phase.

[0047] Life cycle assessment (LCA) characteristics can be extracted, including a comprehensive LCA based on a complete life cycle assessment of the material to provide a detailed view of the environmental impact from production to disposal.

[0048] Environmental certification can be extracted as a characteristic, including material certifications and labels certified by environmental standards (e.g., Forest Stewardship Council (FSC) for wood, Energy Star for electronic components, etc.), which can indicate a lower carbon footprint. Technical and process innovation characteristics can be extracted to indicate the use of new technologies or innovative practices in producing or processing materials that reduce environmental impact.

[0049] By extracting and analyzing these characteristics, a more comprehensive and accurate calculation of the carbon footprint of the artwork can be achieved. This not only helps to assess the environmental impact, but also promotes transparency and accountability in the art community, encouraging more sustainable practices.

[0050] By integrating machine learning into the scoring system, the process becomes more efficient and scalable, and also gains the potential to obtain deeper insights through data-driven analysis. This approach can enhance the way art is evaluated, especially in the context where environmental impact and artistic innovation are key considerations.

[0051] The economic and environmental impact of art cycle work can be calculated in a participating community. One or more marketing channels can be generated that involve participating retailers that can benefit from an increase in brand value that is realized due to their commitment to the environment and the art cycle and the local community that the art cycle project serves. By enabling users to obtain rewards for art cycling, the tax burden associated with waste disposal is reduced for governments and businesses.

[0052] Figure 1 An example of a process 100 for data collection to improve and quantify carbon offsetting by incentivizing the reuse of functional items as decorative items in accordance with an embodiment is shown.

[0053] At operation 105, participating retailer data is recorded in a database. The participating retailer data includes data associated with the participating retailer reward program. At operation 110, a credit amount is associated with the participating retailer reward program. In an example, the data can be provided from the art cycle registration website in a text file (e.g., a file with a.txt extension, etc.), an extensible markup file (XML) file, or another electronic data format. The data file can include various fields / columns including, by way of example and not limitation:

[0054] (1) a customer ID, account ID, or container ID that can include: an RFID tag number as the first 23 characters or numbers; an 8-digit fixed length barcode or keyboard input; another ID number; and a zero sequence code in the form of “99999999999999999999999”; (2) a year 2000 (Y2K) compliant transaction date (e.g., in the format MM / DD / YYYY, etc.); (3) a time (e.g., in the 24-hour clock format HH:MM:00, etc.); (4) an assessed art cycle value (e.g., valued by an individual, an algorithm, etc.); (5) a total weight (e.g., in the 6-digit number format, etc.).

[0055] In an example, as a user art cycles more materials, the user obtains more credits. For example, for each stackable individual bottle that a user (1) commits not to dispose of as trash or recycle and (2) incorporates into an art cycle object, the user is given “X” account credits in the form of art cycle dollars, for example. The number of credits that a residence can obtain per month can be limited. For example, the upper limit of credits that each household can obtain per month can be set to $20.

[0056] When the data file is submitted, fields and tables are updated for each user. By way of example and not limitation, the fields and columns that are updated can include: (1) the total value of art cycle objects to date. For example, the weight of each art cycle pickup is added to the cumulative weight and the total weight of all items art cycled by the user since the user opened the account is obtained; (2) the account credit amount. For example, the weight of each art cycle pickup at the residence (e.g., as reflected in the data file) is converted to account credits. This credit amount is added to the existing account balance for the given user.

[0057] At operation 115, each pickup record is inserted into a pickup data table. The pickup data table is stored in a database (e.g., MICROSOFT® SQL server database or the like) and connected through an open data base connectivity (ODBC) connection. Upon insertion, the database gives each pickup record a unique identifier for later reference.

[0058] When a user enters the portal (e.g., a website or the like), they log in using a username and password. Because each user or residence has a unique username, each user can only log in once.

[0059] When a user logs into their account, they can view their account overview, by way of example and not limitation, including: art cycle activity and the credits the user has earned for art cycling; net recyclables to date; the amount recycled in a given week; the amount and / or date of the last pickup; and shopping history. The user can view account information and / or art cycle information, shop using their account balance, and learn about community environmental initiatives.

[0060] The user can view participating retailers and rewards. To shop, the user selects a desired vendor. For each selected vendor, the user specifies an account credit amount to spend. This value is then deducted from the user's account. For example, if the user selects to spend $10 at three different vendors, a total of $30 is deducted from the user's account.

[0061] At operation 120, the user can select a reward to redeem the credits in their account. At operation 125, the value of the reward is deducted from their account. When the user specifies a vendor and dollar amount, a coupon or other item of redeemable merchandise can be shipped to the address associated with the user's account. The user cannot spend more account credits than exist in their account, unless a mechanism to borrow future credits is defined, which can result in a different psychological incentive to encourage art cycling.

[0062] A report is generated showing the date / time that the user ordered the reward. The reward and fulfillment process is initiated to deliver the reward to the user's address.

[0063] The collected data is analyzed for art cycle rates, participation rates, route efficiency, and performance analysis. The data present in the database can be used to generate various reports. By way of example and not limitation, example reports include individual user reports, full user reports, individual vendor reports, vendor reports, vendor report charts, monthly overview reports, art cycle and participation rate analysis, daily reports of art cycle rewards ordered.

[0064] Administrators can export user reports for each user, which include user activity including art cycle history, history of points earned, and use of points at participating retailers. Administrators can also export system reports containing a system overview. By way of example and not limitation, system reports include individual vendor reports, overview reports, shipping reports, and user reports.

[0065] Reports can be run on various data in the system. Reports can be generated on demand or generated on a regular basis, such as weekly, monthly, or yearly.

[0066] Individual user reports can include a display of a user's art cycle history, earnings, and order activity. Individual user reports display current and past art cycle data for a single user. By way of example and not limitation, the data includes current balance, points earned this month, and report data range. Individual user reports include a user's art cycle history and earnings record with respect to recycling dates. The report also includes a user's order history and the date and contents of each order.

[0067] Full user reports include a display of the art cycle history of a group of users. In an example, a full user report can be generated by collecting routes, zip codes, streets, and routes. By way of example and not limitation, data included in a full user report includes account number, RFID#, user address, and current balance.

[0068] Individual vendor reports display a list of users who have used their points to shop at a particular vendor. In an example, an individual vendor report can be generated for each individual vendor. Individual vendor reports display activity between individual users and a selected vendor. By way of example and not limitation, data in an individual vendor report includes user address, city, state, zip code; rewards ordered from the selected vendor, date of first order, date of last order, and percentage of points used at the selected vendor.

[0069] A vendor report shows how a group of collective users use their points. In an example, a vendor report can be generated by collecting routes, zip codes, or streets. The report shows the most popular vendors for a selected group of users (e.g., by percentage of points spent, total points spent, etc.). By way of example and not limitation, data in the vendor report includes coupon percentage, vendor name, coupon count, and total points.

[0070] A vendor report chart shows how a group of users use their points. In an example, a vendor report chart can be generated for all vendors in the system by zip code or street. The vendor report chart shows the most popular vendors for a selected group of users or across the system. As a bar chart, the report shows vendors on the Y-axis and coupon percentage on the X-axis.

[0071] A monthly overview report shows a group of users’ engagement rate over a given time period. In an example, a monthly overview report can be generated showing engagement rate over the past 4 weeks. In an example, a second series shows weekly engagement rate, which shows the percentage of engaged users for all weeks in the system. In an example, a third series shows monthly overview showing engaged users per month. In an example, a fourth series shows the average and median art cycle value recycled by users per week.

[0072] The terminology and expressions employed herein are used as terms of description and not of limitation, and there is no intention, in the use of such terms and expressions, of excluding any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of aspects of the present disclosure. Thus, it should be understood that although the present disclosure has been specifically disclosed by specific aspects and optional features, modification and variation of the concepts herein disclosed can be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of aspects of the present disclosure.

[0073] Figure 2A , 2B Figs. 2A, 2C, and 2D show an example implementable art cycle bottle for improving and quantifying carbon offset by incentivizing the reuse of functional items as decorative items, according to an embodiment. Figure 2A Fig. 2A shows a side view of an example implementable art cycle bottle, according to an embodiment. Figure 2B Fig. 2B shows a front view of an example implementable art cycle bottle, according to an embodiment. Fig. 2C shows a top view of an example implementable art cycle bottle, according to an embodiment. Figure 2D Fig. 2D shows a bottom view of an example implementable art cycle bottle, according to an embodiment. As shown in Figs. 2A-2D, the example bottle includes a recess into which a top portion of another example bottle can be inserted to couple the bottles when creating an art cycle piece. Figure 2A , 2B As shown in Figs. 2A-2D, the example bottle includes a recess into which a top portion of another example bottle can be inserted to couple the bottles when creating an art cycle piece.

[0074] Figure 3 An example of a process 400 of a portal for improving and quantifying carbon offset by incentivizing the reuse of functional items as decorative items according to embodiments is shown. As shown, a user can create a physical art cycle piece using an example bottle or multiple example bottles as shown in Figure 3 Figure 2A 2B , 2C, and 2D, etc. The user can use the bottle to create a base for an art cycle work, or the arrangement and other decorative elements can include the art cycle work.

[0075] Figure 4 An example of a process 400 of a portal for improving and quantifying carbon offset by incentivizing the reuse of functional items as decorative items according to embodiments is shown. As shown, a user can create a physical art cycle piece using an example bottle or multiple example bottles as shown in

[0076] At operation 405, the user authenticates with the art cycle portal. If the user is a first-time visitor to the portal, the user will be prompted to create a user account, and will be prompted to accept a user agreement and provide user data to generate and populate a user profile.

[0077] At operation 410, the user uploads or otherwise provides an image of a physical art cycle work that they have created and wish to add to their user profile. For example, the user can create an art cycle work using an example bottle or multiple example bottles as shown in Figure 2A 2B , 2C, and 2D. The user captures an image of the art cycle work using a digital camera. In an example, an image capture component of the portal can be used to control an imaging device included with the user computing device to capture the image to prevent tampering, forgery, or other fraudulent activity.

[0078] At decision 415, it is determined whether the user has completed a commitment to maintain a physical version of the theme art cycle work. For example, the user can commit not to recycle or dispose of the art cycle work in the trash. In an example, the user can be allowed to sell the art cycle piece to a collector or otherwise dispose of the art cycle work to prevent the art cycle work from entering a landfill or recycling facility.

[0079] If it is determined at decision 415 that the user has not completed the commitment, the commitment is generated and transmitted to a display of the user at operation 420. If it is determined at decision 415 that the user has completed the commitment, a non-fungible token (NFT) is generated using the image of the art cycle work at operation 425.

[0080] ​​​At operation 430, a value is assigned to the NFT. The value can be based on the number of packages identified as being used in the image (e.g., example bottles, etc.), based on the complexity of the art cycle, etc. Various image analysis and machine learning techniques can be used to gather features from the image that can be used to assign a value to the NFT to evaluate complexity, number of component items, etc.

[0081] In examples, an appraisal can be requested at operation 435. The appraisal request can be transferred to an art or art cycle appraiser, a community of art cycle reviewers, an automated appraisal service, etc. An appraisal can be returned at operation 440, and the value assigned to the NFT can be based on the received appraisal.

[0082] At operation 445, the assigned value is credited to the user’s account. For example, if the value of the NFT is appraised to be $30, the user’s account balance is increased by $30. At operation 450, the user is presented with purchase options. The purchase options can include game entries, various carbon offsets, coupons, products, digital content, etc.

[0083] At decision 455, it is determined whether the user makes a purchase. If so, the user’s account is decreased by the amount of the purchase at operation 460. The purchase is moved to a fulfillment process for delivery to the user. When the user has completed a purchase or it is determined that the user has not made a purchase, the process 400 ends at operation 465.

[0084] Figure 5 An example of a method 500 for improving and quantifying carbon offsets by incentivizing the reuse of functional items as decorative items is shown in accordance with an embodiment. The method 500 can provide features as described in Figure 1 and 3 and can use example bottles as shown in Figure 2A , 2B , 2C, and 2D.

[0085] At operation 505, an image of a unique visual art form created by a user incorporating at least one consumer product package is received.

[0086] At operation 510, a digital record is created in a computer database for the unique visual art form incorporating the at least one consumer product package. The digital record includes at least one first record of an art cycle event based on receiving the image, and the at least one first record includes: a first indication of the art cycle event, a second indication of the art cycle event, and a visual depiction of the art cycle event. The first indication indicates a time of creation of the unique visual art form, and the second indication indicates a commitment not to recycle or dispose of the at least one consumer product package incorporated into the unique visual art form.

[0087] At operation 515, a value is assigned to the art cycle event based on the evaluation of the elements present in the image. In an example, the value can be calculated using an external valuation or valuation algorithm. At operation 520, the user’s account balance is increased by an amount equal to the value. In an example, the valuation can be integrated with the gallery by collecting data from various prestigious galleries that exhibit art. This can include exhibition history, sales data, gallery reputation, etc. Gallery influence is used to incorporate a weighting system where the reputation and historical significance of the gallery contributes to the valuation of the art. Community engagement can be sought through a reputation portal that implements a function where individuals who have visited a particular gallery can provide feedback or rate the art. This can be implemented as a mobile app, website, etc., or can use existing services such as, by way of example and not limitation, LiveArt in New York Rockland. The reputation website develops a network or “reputation web” that connects users based on the galleries they visit and the art they interact with. This network can help identify influential users whose opinions can have more weight in the valuation process. An algorithmic valuation adjustment can be used that uses machine learning algorithms to incorporate feedback to analyze user feedback and adjust the technical valuation accordingly. Feedback can be integrated quantitatively into existing valuation models. Reputation metrics can be developed to evaluate the reputation or influence of galleries and users within the reputation web, thereby affecting the valuation of art based on these metrics. Transparency and dynamic updates using real-time data ensure that the valuation system updates in real-time or near real-time as new feedback and exhibition data is input. Open analytics provide users with tools to understand how valuations are affected by different factors, thereby enhancing transparency.

[0088] In an example, a non-fungible token can be generated for a unique visual art form incorporating at least one consumer product package using an image. In an example, the non-fungible token can be submitted to a non-fungible token exchange. The non-fungible token exchange can include a trade or exchange interface that facilitates trade and exchange of non-fungible tokens among users. Upon receiving a settlement of an exchange or trade transaction, a user’s account balance can be increased by an amount specified in the exchange or trade settlement. In an example, the trade or exchange interface can include an exchange interface having controls that enable a user to exchange a non-fungible token for carbon offsets, a promotional store exchange coupon, or currency. In an example, a promotional store exchange coupon converts at least a portion of a single type of credit in a user’s account into a reward redeemable from one or more third-party providers. The reward comprises one of a good, a service, a good coupon, a service coupon, or other pecuniary benefit from the one or more third-party providers. Each of the one or more third-party providers can be a different vendor, service provider, or retailer. The reward can be generated by a computer database and can be deposited into a user’s account.

[0089] Figure 6 A block diagram of an example machine 600 upon which any one or more of the techniques (e.g., methodologies) discussed herein can perform is shown. In alternative embodiments, the machine 600 can operate as a standalone device or can be connected (e.g., networked) to other machines. In a networked deployment, the machine 600 can operate in the capacity of a server machine, a client machine, or both in server-client network environments. In an example, the machine 600 can act as a peer machine in peer-to-peer (P2P) (or other distributed) network environment. The machine 600 can be a personal computer (PC), a tablet PC, a set-top box (STB), a personal digital assistant (PDA), a mobile telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term "machine" shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein, such as cloud computing, software as a service (SaaS), other computer cluster configurations.

[0090] As described herein, examples can include or can operate by logic or a number of components or mechanisms. A circuit set is a collection of circuits embodied in a tangible entity containing hardware (e.g., simple circuits, gates, logic, etc.). A circuit set membership can change over time as circuits are added and removed from the collection. A circuit set includes a member that can perform a specified operation when operating. In an example, hardware of the circuit set can be immutably designed to carry out a specific operation (e.g., hardwired). In an example, the hardware of the circuit set can include variably connected physical components (e.g., execution units, transistors, simple circuits, etc.) including a computer readable medium physically modified (e.g., magnetically, electrically, moveable placement of irretrievably grounded particles, etc.) to encode instructions of the specific operation. In connecting the physical components, the underlying electrical properties of a hardware constituent are changed, for example from an insulator to a conductor or vice versa, as indicated by the direction of an arrow. The instruction permits the

[0091] The machine (e.g., computer system) 600 can include a hardware processor 602 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a hardware processor core, or any combination thereof), a main memory 604 and a static memory 606, some or all of which can communicate with one another via an interlink (e.g., bus) 608. The machine 600 can further include a display unit 610, an alphanumeric input device 612 (e.g., a keyboard), and a user interface (UI) navigation device 614 (e.g., a mouse). In an example, the display unit 610, input device 612 and UI navigation device 614 can be a touch screen display. The machine 600 can additionally include a storage device (e.g., drive unit) 616, a signal generation device 618 (e.g., a speaker), a network interface device 620, and one or more sensors 621, such as a global positioning system (GPS) sensor, compass, accelerometer, or other sensor. The machine 600 can include an output controller 628, such as a serial (e.g., universal serial bus (USB), parallel, or other wired or wireless (e.g., infrared (IR), near field communication (NFC), etc.) connection to communicate or control one or more peripheral devices (e.g., a printer, card reader, etc.).

[0092] The storage device 616 can include a machine readable medium 622 on which is stored one or more sets of data structures or instructions 624 (e.g., software) embodying or utilized by any one or more of the techniques or functions described herein. The instructions 624 can also reside completely, or at least partially, within the main memory 604, within static memory 606, or both, within the hardware processor 602 during execution thereof by the machine 600. In an example, one or any combination of the hardware processor 602, the main memory 604, the static memory 606, or the storage device 616 can constitute machine readable media.

[0093] While the machine readable medium 622 is illustrated as a single medium, the term “machine readable medium” can include a single medium or multiple media (e.g., a centralized or distributed database, and / or associated caches and servers) configured to store the one or more instructions 624.

[0094] The term "machine-readable medium" can include any medium that is capable of storing, encoding, or carrying instructions for execution by the machine 600 and that cause the machine 600 to perform any one or more of the techniques of the present disclosure, or that is capable of storing, encoding or carrying data structures used by or associated with such instructions. Non-limiting machine-readable medium examples can include solid-state memories, and optical and magnetic media. In examples, a machine-readable medium can exclude non-transitory, transitory, propagation signals (e.g., a non-transitory machine-readable medium). Specific examples of non-transitory machine-readable storage media can include nonvolatile memory, such as semiconductor memory devices (e.g., Electrically Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM)) and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

[0095] The instructions 624 can be transmitted or received by the machine 600 via the network interface device 620 utilizing any one of a number of transfer protocols (e.g., frame relay, internet protocol (IP), transmission control protocol (TCP), user datagram protocol (UDP), hypertext transfer protocol (HTTP), etc.). Example communication networks can include a local area network (LAN), a wide area network (WAN), a packet data network (e.g., the Internet), mobile telephone networks (e.g., cellular networks), Plain Old Telephone (POTS) networks, and wireless data networks (e.g., Institute of Electrical and Electronics Engineers (IEEE) 802.11 family of standards known as Wi-Fi®, LoRa® / LoRaWAN® LPWAN standards, etc.), IEEE 802.15.4 family of standards, peer-to-peer (P2P) networks, 3rd Generation Partnership Project (3GPP) standards for 4G and 5G wireless communication, including: 3GPP Long-Term Evolution (LTE) family of standards, 3GPP LTE-Advanced family of standards, 3GPP LTE-Advanced Pro family of standards, 3GPP New Radio (NR) family of standards, etc. In examples, the network interface device 620 can include one or more physical jacks (e.g., Ethernet, coaxial, or phone jacks) or one or more antennas to connect to the communications network 626. In examples, the network interface device 620 can include a plurality of antennas to engage in wireless communication using at least one of single-input multiple-output (SIMO), multiple-input multiple-output (MIMO), or multiple-input single-output (MISO) techniques. The term "transmission medium" shall be taken to include any intangible medium that is capable of storing, encoding or carrying the instructions for execution by the machine 600, and includes digital or analog communications signals or other intangible medium to facilitate communication of such software.

[0096] Example

[0097] Example 1 is a system comprising: at least one processor; and a memory comprising instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to: receive a unique visual art form created by a user incorporating at least one consumer package; create a digital record for the unique visual art form in a computer database, wherein the digital record comprises at least one first record of an art cycle event made based on receiving the unique visual art form, and wherein the at least one first record comprises: a first indication of the art cycle event, wherein the first indication indicates a time of creation of the unique visual art form; a second indication of the art cycle event, wherein the second indication indicates a commitment to not recycle or dispose of the at least one consumer package incorporated into the unique visual art form; and a visual depiction of the art cycle event; assign a value to the art cycle event based on an evaluation of visual elements present in the unique visual art form; and increase an account balance of the user by an amount equal to the value.

[0098] In Example 2, the subject matter of Example 1, wherein the visual art takes the form of an image.

[0099] In Example 3, the subject matter of Example 2 includes the memory further comprising instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to generate a non-fungible token of the unique visual art form using the image.

[0100] In Example 4, the subject matter of Examples 1-3, wherein the value is calculated using an external valuation or valuation algorithm.

[0101] In Example 5, the subject matter of Examples 3-4 includes the memory further comprising instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to: submit the non-fungible token to a non-fungible token exchange, wherein the non-fungible token exchange comprises a trade or exchange interface that facilitates trading and exchanging of the non-fungible token among users; and upon receiving an exchange or trade transaction settlement, increase the account balance of the user by an amount specified in the exchange or trade transaction settlement.

[0102] In Example 6, the subject matter of Example 5, wherein the trade or exchange interface comprises an exchange interface having controls that enable the user to exchange the non-fungible token for carbon offsets, a promotional store gift card, a charitable donation, or currency.

[0103] In Example 7, the subject matter of Example 6 includes a memory further including instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to: calculate a value of the non-fungible token; and assign the value to the non-fungible token.

[0104] In Example 8, the subject matter of Example 7, wherein the value is calculated in the form of a take.

[0105] In Example 9, the subject matter of Examples 7-8, wherein the value is a value calculated in the form of a royalty stream.

[0106] In Example 10, the subject matter of Examples 6-9, wherein the value is distributed among a plurality of non-fungible token exchanges.

[0107] In Example 11, the subject matter of Examples 1-10 includes a memory further including instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to: train a machine learning processor using features extracted from training data to generate a carbon footprint valuation model, the training data including images of artwork and corresponding carbon footprint data, artwork valuation data, and carbon footprint adjusted valuation data; receive the unique visual art form as input to the machine learning processor; and evaluate features extracted from the input using the carbon footprint valuation model to calculate the value of the art cycle event.

[0108] In Example 12, the subject matter of Examples 1-11 includes a memory further including instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to: access a database of an internet art valuation portal, the database comprising a plurality of pieces of art from a plurality of prestigious exhibition venues, corresponding valuation data, and historical exhibition data; extract, by the at least one processor, a set of features from the unique visual art form, wherein the features comprise at least one of visual characteristics, artist information, and historical sales data; apply a comparative machine learning model trained on the plurality of pieces of art and the corresponding valuation data, wherein the model compares the extracted features of the unique visual art form to similar features of art in the database; adjust, by the at least one processor, an initial valuation derived from the comparative machine learning model based on historical exhibition data of the art in the database in prestigious exhibition venues and a venue influence score of exhibited art, wherein the venue influence score is derived from frequency and recency of exhibitions related to market trends; generate, by the processor, a valuation output for the unique visual art form based on the adjusted valuation, wherein the valuation output is displayed to a user through an internet-based portal; and dynamically update, by the processor, the comparative machine learning model based on new pieces of art and valuation data input into the database and new exhibition data from the prestigious exhibition venues to improve future valuations.

[0109] Example 13 is a computer-implemented method comprising: receiving a unique visual art form created by a user incorporating at least one consumer package; creating a digital record for the unique visual art form in a computer database, wherein the digital record includes at least one first record of an art cycle event made based on receiving the unique visual art form, and wherein the at least one first record includes: a first indication of the art cycle event, wherein the first indication indicates a time of creation of the unique visual art form; a second indication of the art cycle event, wherein the second indication indicates a commitment to not recycle or dispose of the at least one consumer package incorporated into the unique visual art form; and a visual depiction of the art cycle event; assigning a value to the art cycle event based on an evaluation of visual elements present in the unique visual art form; and increasing an account balance of the user by an amount equal to the value.

[0110] In Example 14, the subject matter of Example 13, wherein the visual art takes the form of an image.

[0111] In Example 15, the subject matter of Example 14 includes generating a non-fungible token of the unique visual art form using the image.

[0112] In Example 16, the subject matter of Examples 13-15, wherein the value is calculated using an external valuation or valuation algorithm.

[0113] In Example 17, the subject matter of Examples 15-16, includes submitting the non- fungible token to a non-fungible token exchange, wherein the non-fungible token exchange includes a trade or exchange interface that facilitates trading and exchanging of the non-fungible token between users; and upon receiving an exchange or trade transaction settlement, increasing the account balance of the user by an amount specified in the exchange or trade transaction settlement.

[0114] In Example 18, the subject matter of Example 17, wherein the trade or exchange interface includes an exchange interface having controls that enable the user to exchange the non-fungible token for carbon offsets, a promotional store gift card, a charitable donation, or currency.

[0115] In Example 19, the subject matter of Example 18, includes calculating a value of the non-fungible token; and assigning the value to the non-fungible token.

[0116] In Example 20, the subject matter of Example 19, wherein the value is calculated in the form of a take-it-or-leave-it offer.

[0117] In Example 21, the subject matter of Examples 19-20, wherein the value is a value calculated in the form of a royalty stream.

[0118] In Example 22, the subject matter of Examples 18-21, wherein the value is distributed among a plurality of non-fungible token exchanges.

[0119] In Example 23, the subject matter of Examples 13-22, includes training a machine learning processor using features extracted from training data to generate a carbon footprint valuation model, the training data containing images of artwork and corresponding carbon footprint data, artwork valuation data, and carbon footprint adjusted valuation data; receiving the unique visual art form as input to the machine learning processor; and using the carbon footprint valuation model to evaluate features extracted from the input to calculate the value of the art cycle event.

[0120] In Example 24, the subject matter of Examples 13-23 includes accessing a database of an internet art valuation portal, the database including a plurality of pieces of art from a plurality of prestigious galleries, corresponding valuation data, and historical exhibition data; extracting, by the at least one processor, a set of features from the unique visual art form, wherein the features include at least one of visual characteristics, artist information, and historical sales data; applying a comparative machine learning model that has been trained on the plurality of pieces of art and the corresponding valuation data, wherein the model compares the extracted features of the unique visual art form to similar features of art in the database; adjusting, by the at least one processor, an initial valuation derived from the comparative machine learning model based on historical exhibition data of the art in the database in prestigious galleries and an influence score of galleries that have exhibited art, wherein the influence score is derived from frequency and recency of exhibitions that correlate to market trends; generating, by the processor, a valuation output for the unique visual art form based on the adjusted valuation, wherein the valuation output is displayed to a user through an internet-based portal; and dynamically updating, by the processor, the comparative machine learning model based on new pieces of art and valuation data input into the database and new exhibition data from the prestigious galleries to improve future valuations.

[0121] Example 25 is at least one machine readable medium comprising instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations to perform any of the computer-implemented methods of Examples 13-22.

[0122] Example 26 is at least one machine readable medium comprising instructions that, when executed by at least one processor, cause the at least one processor to perform operations to: receive a unique visual art form created by a user incorporating at least one consumer package; create a digital record for the unique visual art form in a computer database, wherein the digital record includes at least one first record of an art cycle event made based on receiving the unique visual art form, and wherein the at least one first record includes: a first indication of the art cycle event, wherein the first indication indicates a time of creation of the unique visual art form; a second indication of the art cycle event, wherein the second indication indicates a commitment to not recycle or dispose of the at least one consumer package incorporated into the unique visual art form; and a visual depiction of the art cycle event; assign a value to the art cycle event based on an evaluation of visual elements present in the unique visual art form; and increase an account balance of the user by an amount equal to the value.

[0123] In Example 27, the subject matter of Example 26, wherein the visual art takes the form of an image.

[0124] In Example 28, the subject matter of Example 27 includes instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to generate a non-fungible token of the unique form of visual art using the image.

[0125] In Example 29, the subject matter of Examples 26-28, wherein the value is calculated using an external valuation or valuation algorithm.

[0126] In Example 30, the subject matter of Examples 28-29 includes instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to: submit the non-fungible token to a non-fungible token exchange, wherein the non-fungible token exchange includes a trading or exchange interface that facilitates trading and exchanging of the non-fungible tokens among users; and upon receiving an exchange or trading transaction settlement, increase the account balance of the user by an amount specified in the exchange or trading transaction settlement.

[0127] In Example 31, the subject matter of Example 30, wherein the trading or exchange interface includes an exchange interface having controls that enable the user to exchange the non-fungible token for carbon offsets, a promotional store gift card, a charitable donation, or currency.

[0128] In Example 32, the subject matter of Example 31 includes instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to: calculate a value of the non-fungible token; and assign the value to the non-fungible token.

[0129] In Example 33, the subject matter of Example 32, wherein the value is calculated in the form of a take-home benefit.

[0130] In Example 34, the subject matter of Examples 32-33, wherein the value is a value calculated in the form of a royalty stream.

[0131] In Example 35, the subject matter of Examples 26-34, wherein the value is distributed among a plurality of non-fungible token exchanges.

[0132] In Example 36, the subject matter of Examples 26-35 includes instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to train a machine learning processor using features extracted from training data to generate a carbon footprint valuation model, the training data including images of artwork and corresponding carbon footprint data, artwork valuation data, and carbon footprint adjusted valuation data; receive the unique visual art form as input to the machine learning processor; and evaluate features extracted from the input using the carbon footprint valuation model to compute the value of the art cycle event.

[0133] In Example 37, the subject matter of Examples 26-36 includes instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to access a database of an internet art valuation portal, the database including a plurality of pieces of artwork from a plurality of prestigious exhibition venues, corresponding valuation data, and historical exhibition data; extract, by the at least one processor, a set of features from the unique visual art form, wherein the features include at least one of visual characteristics, artist information, and historical sales data; apply a comparative machine learning model trained on the plurality of pieces of artwork and the corresponding valuation data, wherein the model compares the extracted features of the unique visual art form to similar features of artwork in the database; adjust, by the at least one processor, an initial valuation derived from the comparative machine learning model based on historical exhibition data of the artwork in the database in prestigious exhibition venues and influence scores of exhibition venues of exhibited artwork, wherein the influence scores are derived from frequency and recency of exhibitions related to market trends; generate, by the processor, a valuation output of the unique visual art form based on the adjusted valuation, wherein the valuation output is displayed to a user through an internet-based portal; and dynamically update, by the processor, the comparative machine learning model based on new artwork and valuation data input into the database and new exhibition data from the prestigious exhibition venues to improve future valuations.

[0134] Example 38 is a computer-implemented method comprising: forming a unique visual art form created by a user incorporating at least one consumer package; transmitting, to a server, a representation of the unique visual art form; accessing, by the server, a package database comprising data regarding carbon footprints of packages; generating a first value (F), wherein the first value is a representation of the carbon footprint of the at least one consumer package used to form the visual art form; creating a digital record of the representation, wherein the digital record comprises at least one first record of an art cycle event made based on receiving the unique visual art form, and wherein the at least one first record comprises: a first indication of the art cycle event, wherein the first indication indicates a time of creation of the unique visual art form; a second indication of the art cycle event, wherein the second indication indicates a commitment to not recycle or dispose of the at least one consumer package incorporated into the unique visual art form; a visual depiction of the art cycle event; and the first value; assigning a second value (S) to the record based on an evaluation of elements present in the unique visual art form; and generating a third value (T) from the first value and the second value, wherein the third value is represented by the equation: (T) = WF*(F) + WS*(S), where WF and WS represent weights associated with the first value (F) and the second value (S), and 0 < WF, WS < 1; and assigning the third value (T) to the digital record to generate a unique representation of the visual art form.

[0135] Example 39 is at least one machine readable medium comprising instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations to implement any of Examples 1-38.

[0136] Example 40 is an apparatus comprising means for implementing any of Examples 1-38.

[0137] Example 41 is a system for implementing any of Examples 1-38.

[0138] Example 42 is a method for implementing any of Examples 1-38.

Claims

1. A system comprising: at least one processor; and memory including instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to: receive a unique visual art form created by a user incorporating at least one consumer package; create a digital record for the unique visual art form in a computer database, wherein the digital record includes at least one first record of an art cycle event made based on receiving the unique visual art form, and wherein the at least one first record includes: a first indication of the art cycle event, wherein the first indication indicates a time of creation of the unique visual art form; a second indication of the art cycle event, wherein the second indication indicates a commitment to not recycle or dispose of the at least one consumer package incorporated into the unique visual art form; and a visual depiction of the art cycle event; assign a value to the art cycle event based on an evaluation of visual elements present in the unique visual art form; and increase an account balance of the user by an amount equal to the value.

2. The system of claim 1, wherein the visual art takes the form of an image.

3. The system of claim 2, the memory further including instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to generate a non-fungible token of the unique visual art form using the image.

4. The system of claim 1, wherein the value is calculated using an external valuation or valuation algorithm.

5. The system of claim 3, the memory further including instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to: submit the non-fungible token to a non-fungible token exchange, wherein the non-fungible token exchange comprises a trade or exchange interface that facilitates trade and exchange of the non-fungible token among users; and upon receiving an exchange or trade transaction settlement, increase the account balance of the user by an amount specified in the exchange or trade transaction settlement.

6. The system of claim 5, wherein the trade or exchange interface comprises an exchange interface having controls that enable the user to exchange the non-fungible token for carbon offsets, a promotional store exchange coupon, a charitable donation, or currency.

7. The system of claim 6, the memory further including instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to: calculate a value of the non-fungible token; and assign the value to the non-fungible token.

8. The system of claim 7, wherein the value is calculated in the form of a take- away benefit.

9. The system of claim 7, wherein the value is a value calculated in the form of a royalty stream.

10. The system of any one of claims 6 to 9, wherein the value is distributed among a plurality of non-fungible token exchanges.

11. The system of claim 1, the memory further comprising instructions which, when executed by the at least one processor, cause the at least one processor to perform operations to: train a machine learning processor using features extracted from training data to generate a carbon footprint valuation model, the training data comprising images of artwork and corresponding carbon footprint data, artwork valuation data, and carbon footprint adjusted valuation data; receive the unique visual art form as input to the machine learning processor; and use the carbon footprint valuation model to evaluate features extracted from the input to calculate the value of the art cycle event.

12. The system of claim 1, the memory further comprising instructions which, when executed by the at least one processor, cause the at least one processor to perform operations to: access a database of an internet art valuation portal, the database comprising a plurality of pieces of artwork from a plurality of prestigious exhibition venues, corresponding valuation data, and historical exhibition data; extract, by the at least one processor, a set of features from the unique visual art form, wherein the features comprise at least one of visual characteristics, artist information, and historical sales data; apply a comparative machine learning model trained on the plurality of pieces of artwork and the corresponding valuation data, wherein the model compares the extracted features of the unique visual art form to similar features of artwork in the database; adjust, by the at least one processor, an initial valuation derived from the comparative machine learning model based on historical exhibition data of the artwork in the database in prestigious exhibition venues and an influence score of the venue where the exhibited artwork, wherein the influence score is derived from frequency and recency of exhibitions related to market trends; generate, by the processor, a valuation output of the unique visual art form based on the adjusted valuation, wherein the valuation output is displayed to a user through an internet-based portal; and dynamically update, by the processor, the comparative machine learning model based on new artwork and valuation data input into the database and new exhibition data from the prestigious exhibition venues to improve future valuations.

13. A computer-implemented method comprising: receiving a unique visual art form created by a user incorporating at least one consumer product package; creating a digital record for the unique visual art form in a computer database, wherein the digital record comprises at least one first record of an art cycle event made based on receiving the unique visual art form, and wherein the at least one first record comprises: a first indication of the art cycle event, wherein the first indication indicates a time of creation of the unique visual art form; a second indication of the art cycle event, wherein the second indication indicates a commitment not to recycle or dispose of the at least one consumer package incorporated into the unique visual art form; and a visual depiction of the art cycle event; assigning a value to the art cycle event based on an evaluation of visual elements present in the unique visual art form; and increasing an account balance of the user by an amount equal to the value.

14. The computer-implemented method of claim 13, wherein the visual art takes the form of an image.

15. The computer-implemented method of claim 14, further comprising generating a non-fungible token of the unique visual art form using the image.

16. The computer-implemented method of claim 13, wherein the value is calculated using an external valuation or valuation algorithm.

17. The computer-implemented method of claim 15, further comprising: submitting the non-fungible token to a non-fungible token exchange, wherein the non-fungible token exchange comprises a trade or exchange interface that facilitates trading and exchanging of the non-fungible token among users; and upon receiving an exchange or trade transaction settlement, increasing the account balance of the user by an amount specified in the exchange or trade transaction settlement.

18. The computer-implemented method of claim 17, wherein the trade or exchange interface comprises an exchange interface having controls that enable the user to exchange the non-fungible token for carbon offsets, a promotional store gift card, a charitable donation, or currency.

19. The computer-implemented method of claim 18, further comprising: calculating a value of the non-fungible token; and assigning the value to the non-fungible token.

20. The computer-implemented method of claim 19, wherein the value is calculated in the form of a take-a-benefit.

21. The computer-implemented method of claim 19, wherein the value is a value calculated in the form of a royalty stream.

22. The computer-implemented method of any one of claims 18 to 21, wherein the value is distributed among a plurality of non-fungible token exchanges.

23. The computer-implemented method of claim 13, further comprising: training a machine learning processor using features extracted from training data to generate a carbon footprint valuation model, the training data comprising images of artwork and corresponding carbon footprint data, artwork valuation data, and carbon footprint adjusted valuation data; receiving the unique visual art form as input to the machine learning processor; and using the carbon footprint valuation model to evaluate the features extracted from the input to calculate the value of the art cycle event.

24. The computer-implemented method of claim 13, further comprising: accessing a database of an internet art valuation portal, the database comprising a plurality of pieces of artwork from a plurality of prestigious galleries, corresponding valuation data, and historical exhibition data; extracting, by the at least one processor, a set of features from the unique visual art form, wherein the features comprise at least one of visual characteristics, artist information, and historical sales data; applying a comparative machine learning model trained on the plurality of pieces of artwork and the corresponding valuation data, wherein the model compares the extracted features of the unique visual art form to similar features of artwork in the database; ​ adjusting, by the at least one processor, an initial valuation derived from the comparative machine learning model based on historical exhibition data of the artwork in the reputable galleries in the database and an influence score of the galleries of exhibited artwork, wherein the influence score is derived from frequency and recency of exhibitions related to market trends; generating, by the processor, a valuation output of the unique visual art form based on the adjusted valuation, wherein the valuation output is displayed to a user through an internet-based portal; and updating, by the processor, the comparative machine learning model dynamically based on new artwork and valuation data input into the database and new exhibition data from the reputable galleries to improve future valuations.

25. At least one machine readable medium comprising instructions that, when executed by processing circuitry, cause the processing circuitry to perform operations to perform any of the computer-implemented methods of claims 13-22.

26. A computer-implemented method comprising: forming a unique visual art form incorporating at least one consumer package created by a user; transmitting a representation of the unique visual art form to a server; accessing, by the server, a packaging database comprising data regarding carbon footprints of packages; generating a first value (F), wherein the first value is a representation of the carbon footprint of the at least one consumer package used to form the visual art form; creating a digital record of the representation, wherein the digital record comprises at least one first record of an art cycle event based on receipt of the unique visual art form, and wherein the at least one first record comprises: a first indication of the art cycle event, wherein the first indication indicates a time of creation of the unique visual art form; a second indication of the art cycle event, wherein the second indication indicates a commitment to not recycle or dispose of the at least one consumer package incorporated into the unique visual art form; a visual depiction of the art cycle event; and the first value; assigning a second value (S) to the record based on an evaluation of elements present in the unique visual art form; and generating a third value (T) from the first value and the second value, wherein the third value is represented by the following equation: assigning the third value (T) to the digital record to generate a unique representation of the visual art form. (T) = W F *(F) + W S *(S) where W F and W S represent weights associated with the first value (F) and the second value (S), respectively, and 0 ≤ WF， W S ≤1; and ​

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