Development of an AI-Powered Consumer Product Packaging Decoding Application

Consumers face difficulties understanding the safety risks associated with ingredient labels and verifying the trustworthiness of ecological logos on personal care and household products. The lack of regulatory oversight leads to greenwashing and misinformation, making it hard for consumers to make informed purchase decisions and trust the ecological claims made by brands.

A nonprofit organization dedicated to consumer safety and transparency, focusing on educating consumers about product ingredients and ecological branding across various product categories.

• Develop a mobile application enabling consumers to photograph product ingredient labels and ecological logos, providing immediate, comprehensive summaries of safety and ecological trustworthiness.
• Achieve high accuracy (aiming for at least 88%) in text and logo recognition to ensure reliable information delivery.
• Allow user submissions to improve the recognition algorithms and expand the database of ingredients and ecological logos.
• Expand the application's database to cover multiple product categories, including cosmetics, household products, food, electronics, and appliances.
• Increase consumer engagement and awareness through app availability on major mobile platforms and targeted marketing campaigns.

• In-app camera functionality to capture images of ingredient labels and ecological logos.
• AI-powered text recognition to extract ingredient information from product packaging images.
• Logo detection and recognition to identify and validate ecological certification symbols.
• Matching algorithms to compare extracted data against an internal database.
• Dynamic display of product safety risk summaries based on toxicity levels, exposure scenarios, and demographic groups.
• Ecological logo trustworthiness scores with detailed explanations of logos’ scope and reliability.
• User submission interface to upload new ingredient images or ecological logos for database enhancement.
• Seamless integration with the existing database for real-time data retrieval and updates.
• Cross-platform mobile app compatibility for iOS and Android devices.

• Recognition API integrations for text and logo extraction.
• Database systems for ingredient and logo data storage and retrieval.
• User feedback and submission modules to facilitate algorithm trainings and database updates.

• Recognition accuracy target of at least 88% after configuration and training improvements.
• Application responsiveness with minimal latency to ensure real-time user feedback.
• Secure user data handling and privacy compliance.
• Scalable infrastructure to support increasing user base and expanding database content.
• High availability and robust error handling for reliable consumer experience.

The application aims to empower consumers with transparent, trustworthy information about product safety and ecological claims, leading to more informed purchasing decisions. Achieving an 88% or higher recognition accuracy enhances user trust and engagement. Growth in database coverage across multiple product categories and active user submissions will foster greater transparency and reduce greenwashing practices, ultimately contributing to improved public health and ecological awareness.