AI applications are transforming business operations and processes in the power sector as well as the broader economy, leading to greater cost savings, increased efficiency and new services for consumers. But further developments rely on the ability to foster and support innovation, addressing outstanding matters related to investments, data access and governance, as well as ethics. By 2025, 81% of the energy companies will have adopted artificial intelligence, reaping the numerous benefits of accelerated developments in this field and fast tracking the clean energy transition. This is according to an assessment released by Eurelectric, AI Insights: The Power Sector in a Post-Digital Age. First, AI can enable a faster decarbonisation of the power sector.
You can now run computations on your phone that would have been unthinkable a few years ago. But as small devices get smarter, we discover new uses for them that overwhelm their resources. If you want your phone to recognize a picture of your face (image classification) or to find faces in pictures (object detection), you want it to run a convolutional neural net (CNN). Modern computer vision applications are mostly built using CNNs. This is because vision applications tend to have a classifier at their heart--so, for example, one builds an object detector by building one classifier that tells whether locations in an image could contain an object, then another that determines what the object is.
The Dubai Electricity and Water Authority (Dewa) has adopted the use of Smart Dubai's Ethical AI Toolkit. It reports using it for 13 artificial intelligence (AI) use cases across various departments, registering an average performance rate of almost 90 per cent on complying with the principles and guidelines set out. Smart Dubai developed the toolkit to set clear guidelines on the ethical use of AI to prevent having a fragmented, incoherent approach to ethics, where every entity sets its own rules. Dewa's use of the toolkit was spread across several different departments. The Innovation & the Future (I&TF) division's use cases included outage planning and load forecasting, solar power generation forecasting, network design and area planning, visual inspection on solar photovoltaics and the virtual assistant Rammas.
A solar-powered autonomous drone scans for forest fires. A surgeon first operates on a digital heart before she picks up a scalpel. A global community bands together to print personal protection equipment to fight a pandemic. "The future is now," says Frédéric Vacher, head of innovation at Dassault Systèmes. And all of this is possible with cloud computing, artificial intelligence (AI), and a virtual 3D design shop, or as Dassault calls it, the 3DEXPERIENCE innovation lab. This open innovation laboratory embraces the concept of the social enterprise and merges collective intelligence with a cross-collaborative approach by building what Vacher calls "communities of people--passionate and willing to work together to accomplish a common objective." This podcast episode was produced by Insights, the custom content arm of MIT Technology Review. It was not produced by MIT Technology Review's editorial staff. "It's not only software, it's not only cloud, but it's also a community of people's skills and services available for the marketplace," Vacher says. "Now, because technologies are more accessible, newcomers can also disrupt, and this is where we want to focus with the lab." And for Dassault Systèmes, there's unlimited real-world opportunities with the power of collective intelligence, especially when you are bringing together industry experts, health-care professionals, makers, and scientists to tackle covid-19. Vacher explains, "We created an open community, 'Open Covid-19,' to welcome any volunteer makers, engineers, and designers to help, because we saw at that time that many people were trying to do things but on their own, in their lab, in their country."
Attention is increasingly turning to organic photovoltaic (OPV) solar cells after decades of relying on silicon, which is relatively expensive and lacks flexibility. OPV solar cells will be cheaper to make by using printing technologies, as well as being more versatile and easier to dispose of. But a major challenge is sorting through the huge volume of potentially suitable chemical compounds that can be synthesised (tailor-made by scientists) for use in OPVs. Researchers have tried using machine learning before to address this issue but many of those models were time consuming, required significant computer processing power and were difficult to replicate. Crucially, they did not provide enough guidance for the experimental scientists seeking to build new solar devices.
Plans to beam 5G signals to the public via drones that stay airborne for nine days at a time have been announced by two UK firms. They want to use antenna-equipped aircraft powered by hydrogen to deliver high-speed connectivity to wide areas. Stratospheric Platforms and Cambridge Consultants say they could cover the whole of the UK with about 60 drones. But telecoms analysts question whether the economic case for this scheme is quite as simple as it sounds. The Cambridge-based companies say they would run the service in partnership with existing mobile operators. They are already backed by Deutsche Telekom, which hopes to trial the technology in rural southern Germany in 2024.
Edge AI offers lots of improvement over conventional ML architectures. First of all the latency involved with any network transfer is removed, which can be critical in some use cases. The battery drain involved with streaming data is no longer an issue, allowing for better battery life, and associated costs for data communication are significantly reduced. This is highly beneficial for a number of use cases. Sensors in remote locations like offshore wind farms can come pre-loaded with the algorithms that enable them to make decisions without the complex infrastructure of getting them internet-connected.
While countries around the world ponder how to build up secure, reliable, and cost-efficient infrastructure for their future 5G networks, two companies in the UK have come up with a rather unorthodox solution to deliver faster connectivity. Engineering firm Cambridge Consultants and telecommunications company Stratospheric Platforms Limited (SPL) have unveiled a new proof-of-concept, which could see 5G beams broadcast from the skies thanks to antennas fitted onto drones flying some 20,000 meters above the ground. The prototype that has been tested so far is only one eighth of the intended full size, but the companies hope that the final product will come in the form of a three square-meter antenna capable of beaming 5G directly onto areas up to 140 kilometers in diameter. The antennas will be integrated into zero-emission aircraft powered by hydrogen, and capable of carrying the equipment for up to nine days in a row. According to Cambridge Consultants, a fleet of 60 aircrafts equipped with antennas would be enough to blanket the whole of the UK with 5G connectivity, delivering mobile speeds evenly across the country in excess of 100 Gbps.
Ten years ago, I was engaged in the writing of an energy power grid report that was part of a national initiative to assess the health of our electrical energy grid and its resilience. Assets like wind farms and contemporary fossil and nuclear fuel systems were in place for energy distribution, but to my surprise there was also equipment in the grid that dated back to the 1890s and was still in production. I began to understand the challenges of using renewable energy such as wind and solar when it came to assessing energy supply and demand and ensuring there is enough on-hand energy to power the homes and businesses that are relying on it. When utilities were using gas, coal, or nuclear energy to power the grid, the in-flow of that fuel from its source was consistent, so it was easy to assess supply and demand on any given day and to deliver the energy needed to power homes and businesses. What if the wind gusted to 40 mph one day, and was perfectly still on the next day?
At the intersection of machine learning and energy consumption stands an incredibly powerful force with the potential to transform the way we globally produce and consume energy. So powerful in fact, that the concept of merging machine learning and renewable resources has been named the "energy internet" by economic theorist and author Jeremy Rifkin or "digital efficiency" by Intel and GE. Digital twin tech, or a virtual representation of a product, is a critical concept in IoT that's still being sorted out. You forgot to provide an Email Address. This email address doesn't appear to be valid.