Emissions
Emissions

Emissions

Algorithms Artificial Intelligence Cities Civil and environmental engineering Climate change Computer modeling Computer science and technology Electrical engineering and computer science (EECS) Emissions IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Energy Initiative MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering Sustainability Transportation

Parking-aware navigation system could prevent frustration and emissions

By minimizing the need to drive around looking for a parking spot, this technique can save drivers up to 35 minutes — and give them a realistic estimate of total travel time.

Artificial Intelligence Climate change Computer modeling Electric grid Emissions Energy Energy efficiency Infrastructure Invention MIT Energy Initiative MIT Sloan School of Management open source Policy Research Technology and policy

Helping power-system planners prepare for an unknown future

Macro, a modeling tool developed by the MIT Energy Initiative, enables energy-system planners to explore options for developing infrastructure to support decarbonized, reliable, and low-cost power grids.

Artificial Intelligence Cleaner industry Climate change Electric grid Emissions Energy Energy efficiency MIT Energy Initiative Research Sustainability Technology and policy

MIT Energy Initiative launches Data Center Power Forum

MIT faculty and MITEI member company experts address power demand from data centers.

Algorithms Artificial Intelligence Climate change Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Emissions Energy Energy storage Infrastructure Lincoln Laboratory machine learning MIT Energy Initiative MIT Schwarzman College of Computing MIT Sloan School of Management Research School of Engineering Supercomputing Sustainable computing

Responding to the climate impact of generative AI

Explosive growth of AI data centers is expected to increase greenhouse gas emissions. Researchers are now seeking solutions to reduce these environmental harms.

Algorithms Artificial Intelligence Climate change Computer modeling Data EAPS Earth and atmospheric sciences Emissions IDSS machine learning MIT Schwarzman College of Computing Pollution Public health Research School of Science Sustainability

Simpler models can outperform deep learning at climate prediction

New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.

Algorithms Artificial Intelligence Autonomous vehicles Cities Civil and environmental engineering Climate change Computer modeling Computer science and technology Electrical engineering and computer science (EECS) Emissions IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering Sustainability Transportation

Eco-driving measures could significantly reduce vehicle emissions

New research shows automatically controlling vehicle speeds to mitigate traffic at intersections can cut carbon emissions between 11 and 22 percent.

Alternative energy Artificial Intelligence Chemical engineering DMSE Electrical engineering and computer science (EECS) Emissions Energy Energy efficiency Faculty Laboratory for Information and Decision Systems (LIDS) Lincoln Laboratory MIT Energy Initiative Renewable energy School of Engineering Special events and guest speakers Staff Sustainability

Confronting the AI/energy conundrum

The MIT Energy Initiative’s annual research symposium explores artificial intelligence as both a problem and a solution for the clean energy transition.

Artificial Intelligence Civil and environmental engineering Cleaner industry Concrete Concrete Sustainability Hub DMSE Emissions Environment Infrastructure Materials science and engineering Research School of Engineering Sustainability Technology and society

AI stirs up the recipe for concrete in MIT study

With demand for cement alternatives rising, an MIT team uses machine learning to hunt for new ingredients across the scientific literature.

Algorithms Artificial Intelligence Autonomous vehicles Civil and environmental engineering Computer science and technology Data Emissions IDSS Laboratory for Information and Decision Systems (LIDS) Logistics machine learning MIT Schwarzman College of Computing Research School of Engineering Sustainability Traffic management Transportation

New tool evaluates progress in reinforcement learning

“IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.

Artificial Intelligence Civil and environmental engineering Climate change Collaboration Emissions IDSS International initiatives Mechanical engineering MIT Schwarzman College of Computing MIT Sea Grant Nuclear science and engineering Oceanography and ocean engineering Research School of Engineering Supply chains Technology and policy Transportation

MIT Maritime Consortium sets sail

A new international collaboration unites MIT and maritime industry leaders to develop nuclear propulsion technologies, alternative fuels, data-powered strategies for operation, and more.