Tracking CO2 Emissions with Machine Learning with Laurence Watson - TWIML Talk #277

This article discusses the use of machine learning, specifically computer vision, to track CO2 emissions. It focuses on a conversation with Laurence Watson, CTO of Plentiful Energy and former data scientist at Carbon Tracker. The core of the discussion revolves around Carbon Tracker's goals and their report on using satellite imagery to estimate fossil fuel power plant utilization. The article highlights the application of computer vision to process satellite images of coal plants, including the labeling process, and addresses the challenges associated with the project's scope and scale. This suggests a practical application of AI in environmental monitoring.

• •Carbon Tracker uses satellite imagery and computer vision to monitor coal plant activity.
• •The project involves labeling satellite images for machine learning.
• •The project faces challenges related to scope and scale.