AI-Powered PCF Verification System
Our prototype employs AI-driven Comparative Analysis Algorithms to improve accuracy and credibility in product carbon footprint calculations for sustainability initiatives.
Challenge
Verifying Product Carbon Footprints
The SINE Foundation's challenge centers on using AI to verify product carbon footprints and improve data quality for sustainability initiatives, while managing complexities in carbon footprint calculations.
About the prototype
The solution leverages AI-driven Comparative Analysis Algorithms for the verification of Product Carbon Footprint (PCF) calculations. Faced with the challenge of diverse and proprietary data models used by companies, our solution benchmarks data against industry standards and similar products. A ranking algorithm assigns weighted scores based on factors such as raw material sourcing, manufacturing processes transportation, and end-of-life considerations Integrated with various certifications, the system ensures a comprehensive evaluation enhancing the accuracy of sustainability assessments. A user-friendly interface enables product and manufacturer searches, providing detailed reports on potential inconsistencies or data manipulations. This solution empowers stakeholders, including regulatory bodies and sustainability analysts, with actionable insights, promoting transparency, higher data quality, and environmentally responsible business practices for the promise of a decarbonized economy.
Outputs
Further information about the progress, milestones, and roadblocks.
Interface mock-ups on Figma
Presentation of the prototype