Predicting Carbon Intensity from Grid Frequency Data Using FFT Analysis and Gradient Boosted Regression

An advanced machine learning system that leverages ensemble methods and deep learning for comprehensive climate risk assessment and prediction. The tool combines multiple ML models with real-time weather data analysis to provide actionable insights for climate-related threats.

Hackathon winner at AI Engineer World Fair Hackathon: Transforming code, one function at a time, to reduce digital carbon footprints and create a more sustainable digital world.

🌿 AI-powered environmental news aggregation & analysis platform with smart query expansion, sentiment balancing, and real-time insights.

CATIA is a catastrophe AI system that integrates advanced artificial intelligence, actuarial science, risk analysis, and machine learning to provide robust assessments of natural hazards such as hurricanes, floods, and wildfires, with a focus on financial impacts and mitigation strategies.

A curated list of high-quality resources, startups, tools, and frameworks driving innovation in climate technology.

PHREEQC geochemical modeling of Enhanced Rock Weathering in Darjeeling tea plantations for carbon removal quantification and agricultural soil enhancement

AI-powered carbon footprint tracker — log eco-friendly habits (walking, cycling, public transport, no AC) and get real-time CO₂ savings with personalised sustainability insights.

An AI-powered geospatial intelligence dashboard for predicting atmospheric ozone levels using 27 years of NASA data. Features 3D climate mapping and live satellite tracking.

ML-based estimation of datacenter power demand and grid impact analysis for US electrical infrastructure.

GreenLang: Enterprise Climate Intelligence Platform - 100+ AI agents for carbon accounting, ESG compliance (CSRD, EUDR, CBAM, GHG Protocol, ISO 14064, CDP, TCFD, SBTi, EU Taxonomy), MRV automation, and regulatory reporting. Built with Python, PostgreSQL, Redis, Kubernetes.

Decentralized environmental monitoring network on Cardano – VerdantWatch Catalyst Fund15 proposal

Google Open-Source Project: Stochastic building simulator and real-world dataset for training and benchmarking reinforcement learning agents in energy-efficient smart control environments. Built with Gym, TensorFlow Agents, and 6+ years of real building data.

Lanzarini Model (Geodetic-Entropic Optimization). Official Protocol: 18 March 2026. Reducing AI energy consumption by 58.42% (5.01 TWh/year) via Geodesic L-Operator and 2.99 Hz Resonance.

klimaTwin is an ai powered campus climate twin that turns real time energy water air quality and e waste data into actionable behavioral nudges and verified sustainability impact.

🌍 AI-Powered Personal Carbon Footprint Tracker — Scan receipts, track food/transport/energy emissions, get AI coaching. Built with Claude AI + Streamlit.

Smart agriculture backend API that predicts optimal crops using Machine Learning. Features: Real-time weather integration, multi-language support, PDF reports, and historical yield analysis. Built with FastAPI, scikit-learn, and deployed on Render.

EnerCast is a data-driven machine learning project that estimates national CO₂ emissions from energy consumption patterns. It combines a reproducible data pipeline, leakage-safe feature selection, and rule-based baselines to compare traditional estimation approaches with ML models and evaluate emission-reduction scenarios for carbon credit scoring.

Dockerized FastAPI service for forecasting Germany’s hourly electricity load using real Open Power System Data (OPSD). Includes time-series feature engineering, machine-learning baseline model, and production-ready API endpoints.

Open-source 16.7 kWh phase-change thermal energy storage system for building electrification