Carbon Manager
Our project leverages AI to calculate and manage Carbon Footprint, aiming to reduce global warming by tracking greenhouse gas emissions and promoting sustainable actions to protect the environment.
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Description
Project Description: Carbon Manager
1. Executive Summary
Carbon Manager is an AI-powered platform that enables individuals and organizations to accurately measure, understand, and reduce their carbon footprints through an intuitive Q&A interface, actionable insights, and community-driven engagement. Combining state-of-the-art machine learning models, a custom large language model (Chat2Eco), blockchain-backed verification, and gamified reward mechanisms, Carbon Manager fosters sustainable behaviors, reforestation initiatives, and collective climate action. The platform achieves a predictive accuracy of up to 98%, supports users as young as five years old, and aligns with key UN Sustainable Development Goals.
2. Problem Statement
Global carbon dioxide emissions reached a record 36.8 billion metric tons in 2020, driving climate change, extreme weather, biodiversity loss, and public health crises. Despite widespread recognition of the issue, most individuals and organizations lack transparent, personalized tools to quantify their carbon impact and take effective mitigation steps. Existing calculators are often generic, non‑interactive, or disconnected from actionable outcomes. There is an urgent need for a comprehensive, user-friendly solution that bridges data-driven insight with real-world offsetting and community collaboration.
3. Solution Overview
Carbon Manager addresses this gap by offering:
AI Carbon Footprint Manager: A dynamic Q&A interface built on decision tree, logistic regression, KNN, SVM, Random Forest, XGBoost, and ANN models to estimate monthly emissions with 97–98% accuracy on a curated dataset of 10,000 entries. Users receive a creative graph of their footprint and educational "Did You Know?" facts.
Offset & Reforestation Coordination: Calculates the number of trees needed to offset emissions, offering guided self-planting (with certificates) or NGO-based carbon credit donations, supplemented by blockchain-secured proof submission.
Chat2Eco LLM Plugin: A 132B-parameter Mixture-of-Experts model combining Gemini 7B, LLaMA 70B-Chat, and Mixtral 8x7b architectures via SLERP interpolation. Provides multilingual, domain‑specific advice, idea generation, and creative outputs on sustainability topics.
Community Forum: Built on WIX with Velo APIs and Firebase, it fosters peer-to-peer knowledge exchange, project showcases, and gamified badges and leaderboards to drive engagement.
Reward & Verification System: Users earn redeemable Carbon Reward Points upon verified proof submissions, which are validated through blockchain and manual review, then displayed on a competitive leaderboard.
Correction Factor Mechanism: Industry experts can submit comparative data to refine model predictions via a dynamic correction factor, ensuring continuous improvement.
4. Technical Architecture
Frontend: React + Tailwind CSS, responsive Q&A forms & graphing.
Backend: FastAPI serving REST for footprint, offsets, forum; gRPC for Chat2Eco inference.
ML Pipeline: Data preprocessing (One‑Hot, StandardScaler), GridSearchCV hyperparameter tuning, model serialization with Pickle/PyTorch.
Data: 10K-sample dataset (5 numerical, 11 categorical features) curated from Kaggle and open sources.
Chat2Eco Training: QLoRA & SFT fine‑tuning on a ~12T-token corpus using Jupyter, Apache Spark, and distributed compute.
Blockchain: Immutable proof logs via Ethereum smart contracts for audit trails.
5. Innovation & Competitive Edge
Holistic Integration: Unifies footprint calculation, offsetting, expert‑driven corrections, community engagement, and AI conversational guidance in one platform.
Mixture-of-Experts LLM: Chat2Eco’s dynamic expert routing and high parameter count deliver superior domain knowledge at lower compute cost per token.
Gamification & Rewards: Carbon Reward Points and leaderboards incentivize sustained user participation.
Expert Feedback Loop: The Correction Factor feature empowers domain experts to directly improve model accuracy, fostering trust and reliability.
6. Impact & Sustainability
User Accessibility: Intuitive UI democratizes carbon management for all ages (5+).
Behavioral Change: Personalized suggestions and rewards drive measurable reductions in household and organizational emissions.
Reforestation: Expert-guided planting and NGO partnerships facilitate large-scale carbon sequestration.
Global Goals: Directly advances SDGs 3 (Health), 7 (Clean Energy), 11 (Sustainable Cities), 12 (Responsible Consumption), 13 (Climate Action), and 15 (Life on Land).
7. Ethical, Privacy & Security Considerations
Fairness & Transparency: Open methodologies, clear data sources, and intuitive explanations build user trust.
Privacy: AES-256 encryption at rest, TLS 1.3 in transit, and GDPR-compliant data handling.
Security: OAuth2 + JWT, multi-factor authentication, role-based access control, and immutable blockchain audit logs.
Accountability: Continuous monitoring, audit trails, and user feedback channels ensure responsible AI usage.
8. Future Work & Roadmap
Real-time IoT sensor integration for live emission tracking.
Mobile applications for iOS and Android.
Explainability dashboard (SHAP/LIME) for model transparency.
Automated carbon credit marketplace integration.
Expansion to additional languages and regions through LLM fine-tuning.
Carbon Manager: Empowering individuals and communities to take meaningful climate action through AI-driven insights, collaborative engagement, and sustainable behaviors.
Progress During Hackathon
During the 48‑hour hackathon sprint, our team kicked off with a rapid requirements workshop to refine user stories for footprint calculation, offset management, and community engagement, swiftly architecting the system using React and Tailwind on the front end and FastAPI on the back end. By midday, we had curated and preprocessed an initial 5,000 datapoints, applying categorical encoding and scaling, and deployed a prototype Q&A interface with dynamic Chart.js graphs powered by a Decision Tree model. At the first integration checkpoint, the XGBoost model was woven into the backend API, delivering an 83% accuracy on a held‑out test set, while GitHub Actions pipelines were established to automate linting, unit tests, and Docker image builds. On the second day, feature expansion was done, and the offset calculator UI was linked to tree‑count algorithms., and a minimal Chat2Eco plugin was embedded with placeholder LLM responses; simultaneously, a WIX‑based forum MVP with Firebase authentication and real‑time posting functionality went live. In the final hours, we polished UI styles, updated the README, and deployed a live demo to Vercel, then recorded a project video showcasing the core flows, footprint Q&A, offset checkout, proof upload, and forum posting. Rigorous peer reviews addressed API timeouts and input validation bugs, and all supporting materials, including architectural diagrams and test reports, were finalized, which fculminated in a fully functional end‑to‑end demonstration that earned enthusiastic feedback from mentors on both its technical rigour and user experience.
Tech Stack
Fundraising Status
Since inception, Carbon Manager has been developed entirely through the passion and voluntary contributions of our student team, with no budgetary support or funding from South Point High School. As we prepare to scale the platform, integrating real‑time IoT sensor feeds, expanding LLM fine‑tuning, securing enterprise‑grade infrastructure, and launching mobile applications, we face costs for cloud computing credits, blockchain transaction fees, professional development and design services, and community outreach. To bridge this gap and accelerate our impact, we are actively seeking grants, corporate sponsorships, and in‑kind partnerships with environmental foundations, technology firms, and CSR programs. Your support will directly underwrite hosting and compute resources, expert consulting, and user‑education initiatives, empowering Carbon Manager to democratize carbon management and drive meaningful climate action worldwide.