19. HenceForth
Product Name: Kangaeroo
1. Executive Summary
As the demand for sustainable practices has increased by 50% from 2021, 71% of more than 11,500
global consumers are making changes to their lifestyles and the products they buy to live moresustainably. [1] ‘Greenwashing' has increased as consumers increasingly seek to buy environmentallysound products. In the current state, 21% of consumers question the credibility of the sustainability
claims made by companies and are concerned about greenwashing. This is supported by numericalevidence, as the European Commission reported that out of 344 seemingly dubious claims investigated,
37% of the claim included vague and general statements such as “conscious”, “eco-friendly”, and“sustainable”. [2] To tackle this issue, a proposed greenwashing detection application by incorporating AI
technology to identify the ecological aspects of groceries, so consumers can make informed choices of
their chosen items.
2. Our mission
Kangaeroo aims to empower consumers with accurate information on product sustainability while adding
a touch of humor and interactivity to the shopping experience. Through the integration of advanced AI
technology, our innovative robot, strategically placed on the handle of shopping carts, objectively
analyzes product ingredients, packaging, and marketing claims in real time.
We provide consumers with a spectrum of green (no greenwashing or truly eco-friendly) to red(greenwashing) indicators while engaging in witty banter along the way. When unrealistic orinappropriate claims or marketing tactics are detected, the robot boldly reveals products on the red sideof the spectrum. Our goal is to foster transparency and objectivity, preventing the prevalence ofgreenwashing and SDGswashing in the marketplace.
3. Our productKangaeroo, our interactive robot, follows six sequential steps to assist the consumer indetermining whether or not a product is capitalizing on "Greenwashing". The steps are
as follows below;
1) Barcode Scanning: Once the barcode of the chosen product is placed in front of thescanner, the in-built laser beam is directed onto the barcode, and the reflected light isdetected by the sensor, which interprets the dark and light bars, decoding the code, andidentifying the product information. On the KangaePouch system, the identified productis searched within the system, allowing the system to list the ingredients, materials, andcompositions inside the selected product on the display screen.
2) Product Showcase: The consumer then showcases the product to the eyes of the robot for 15seconds. During the 15 seconds, the high-resolution camera will capture detailed images of the productsurface. [3] With Kangaeroo's motorized ability of zoomed lens, Kangaeroo will be able to adjust its focal
length to zoom in and out according to the magnification of the captured images. The true magic lies inDigital Zoom, however, which would allow Kangaeroo to magnify specific areas of interest, which havebeen trained to it. Such as Forests, Trees, Leaves, Water, the Sun, or anything resembling a natural orsustainable resource.
3) Analysis: Image Interpretation: Based on the images captured, Kangaeroo includes an Image
Processing Software, which identifies and analyzes the specific patterns, colors, designs, and images
based on an algorithm which Kangaeroo is trained in using [4] Convolutional Neural Networks (CNNs).
Thanks to its prior training, Kangaeroo can identify and understand the object on the packaging. Text
Interpretation: Not only that, text plays a major role in the Greenwashing market, hence using thecaptured images, Kangaeroo runs an [5] Optical Character Recognition system to extract texts andkeywords. It would also translate these texts into machine-readable text characters. It conducts
tokenization, to ensure that punctuation, special characteristics, and stopwords are removed for its
understanding. To ensure accuracy, Kangaeroo pre-processes the image to do noise reduction, contrast
enhancement, and image binarization to separate text from the background. Kangaeroo, once
understood the text, runs a Keyword Extraction and [6] Sentiment Analysis to determine important terms
and tone behind the words.
4) Red vs. Green Zone Determination: Kangaeroo is trained to make its judgment based on a "Red" vs"Green" zone. Its advanced analysis skills allow it to scale a product into either of the zones. Claim
Identification: Kangaeroo is trained to consider terms such as "all", "completely" etc. in the Red Zone. Ifusing OCR, it detects such vocabulary, which is Henceforth named "Big Claims", Kangaeroo will count it
as 1 Red Flag found. Frequency Analysis: If a product uses what we named, "Fluff Words", more thanits threshold setting, Kangaeroo will count it as 1 Red Flag found. Kangaeroo counts the frequency ofeach word in the text and identifies if the word goes beyond its threshold setting (which is set up by us).
Pattern Recognition: Kangaeroo recognizes what we named, "Gobbledygook words", defined byHenceforth. If Kangaeroo matches a "Gobbledygook Word" such as "Synergistic", but does not matchany other words related to this, such as "substances", "agents" or "interaction", it will conclude that this ismerely a word used for marketing, with no explanation. Hence, it will count as 1 Red Flag found.
5) Alert Zone When Kangaeroo recognizes any images/colors that are frequently used forGreenwashing marketing, such as Forests, Leaves using the CNN model, it will count it in the "AlertZone". Natural Language Processing: Based on the product identification using the barcode in thebeginning, the access to the ingredients, and the Keyword analysis conducted, it will find any
contradictions between the ingredients (in the database) and claims made in the product packaging. Our
comparison algorithm has a set of criteria for determining a match (exact, partial, synonym, and fuzzymatch). With information reports supporting our algorithm, a word such as "natural" in a claimed diaper
packaging for example, would have a "fuzzy" match if it collides with one of the materials of the diaper
being polypropylene (which is a plastic polymer). Hence, Kangaeroo will count it in the "Alert Zone".
6) Interaction with Consumers: After conducting such analysis, which would all occur in a short time,
Kangaeroo will interact with the customer, stating all the "Red Flags" and "Alert Zones" it detected.
Expect, to increase user engagement and encourage user participation, Kangaeroo is trained tocommunicate playfully and humorously! Anytime, Kangaeroo counts a Red Flag or Alert Zone,
Kangaeroo's vocabulary and sentence formation have been structured through Machine Learning [7] (orGenerative Pre-trained Transformer) on a previously collected dataset. Kangaeroo would vocallycommunicate the main summarized red and alert zones it detects, while on the KangaePouch, the user
will be able to read. To help personalize the experience for the user, Kangaeroo can store transcripts,
metadata, and analysis for each session. This is due to data logging, and algorithms developed whichallow Kangaeroo to interpret the logged data in the right context.
Target market/strategy
Our target customers are consumers who are willing to purchase sustainable products. Our target
industry is a supermarket grocery store that sells products and uses carts. Our products act as anextension on usual carts. This allows the product to be low-cost and lowers the hurdle to be introduced.
We use penetration pricing methods to allow fast dissemination of the production and acquire moremarket share. The usage of robotics, and AI allows us to attract consumers and gives the consumer achance to critically see the products and the company in terms of eco and SDGs.
4. Finance
We used penetrative pricing for our finance strategy,prioritizing our market share. Hence the product priceincreases over time. Due to mass production, theaverage cost of the product decreases over time. Staff
salaries and marketing costs increase as we expand ourbusiness for system maintenance and further expansionof the business.
5. Conclusion
With Kangaeroo, we guide consumers towards
eco-friendly choices and contribute to a more environmentally conscious world. The innovation of AI
detection robots has the potential to enhance valuable shopping experiences that are not only
informative but also entertaining and meaningful.
6. References[1]https://www.simon-kucher.com/en/insights/2022-global-sustainability-study-growth-potential-environm
ental-change[2]https://ec.europa.eu/commission/presscorner/detail/en/ip_21_269[3]https://link.springer.com/referenceworkentry/10.1007/0-387-30038-4_56[4]https://www.ibm.com/topics/convolutional-neural-networks[5]https://www.ibm.com/blog/optical-character-recognition/[6]https://aws.amazon.com/what-is/sentiment-analysis/[7]https://www.nri.com/jp/knowledge/glossary/lst/alphabet/gpt_3