It claims this machine learning and IoT-based approach will dramatically reduce errors in manufacturing
It will support researchers using computation-based models to tackle basic science challenges, advance clean energy technologies, improve energy efficiency and predict extreme weather and climate patterns
Equinor says digital solutions helped increase subsurface understanding, ensure more efficient start-up of wells, higher stable production and more efficient maintenance
Funding will support projects which will harness algorithms to take advantage of artificial intelligence and machine learning technologies
The research plans to expand use of technology to find solutions to challenges including Covid-19
Mixergy claims the technology can help households save up to 20% on their hot water bills and has been certified to deliver grid balancing services to National Grid
The software will be used in the real-time management of the network and forward planning when assessing the impact of new connections across the system
In this case, a question of great interest will be: how will these AI systems interact with their end users in the energy management field?
One of the proposals is the development of machine learning solutions to improve and extend diagnostic and prognostic capabilities for predictive maintenance of plants
Artificial Intelligence (AI) is currently perceived in many ways. Some believe the Hollywood view of the self-aware, fully thinking autonomous entity, that will take over the world. Others that is no more than a complex, rules-based search engine that clever programmers have disguised as your new friend. They’re both wrong.