10. Data Analysis and Control

“When it comes to climate change, machine learning can help on both mitigation and adaptation sides.”

This story has been taken from the multimedia report Top 10 Frontier Technologies for Climate Action. Find it here.

We associate computer technology with the places where most innovation happens — Silicon Valley, Berlin, London, New York.

But the cost of computational power is decreasing, and as electronics become smaller, cheaper and more widespread, they are more accessible to the developing world. Invisible computational systems can revolutionise all manner of industries, even in countries where electricity connections are unreliable. And the rapid growth of mobile technology has connected off-grid communities across Africa and Asia, opening up new opportunities.

Innovators are still figuring out how machine learning and quantum computing can be targeted to help solve climate problems. But in today’s world, technology means we have access to more data than ever before — sometimes more than companies or governments know what to do with. The use of data might be more dominant in more developed, high tech economies, but computer systems and data collection are increasingly available in the less-developed world too. And that means the opportunity to do something with that data.

To effectively tackle climate change and its impacts through tech, people in the places that need these technological solutions must have access to them. Knowledge sharing is essential. People working in tech don’t know what they don’t know — someone sitting in Silicon Valley might not be best placed to come up with a tech solution for rural Tanzania. This can be solved by supporting accelerators, incubators, and competitions locally to encourage home-grown ideas about how best to apply tech to each environment.

Machine Learning

Machine learning refers to systems that can automatically learn and improve from experience without being explicitly programmed — accessing data and learning to use it themselves. When it comes to climate change, machine learning can help on both mitigation and adaptation sides. It could help to distribute and manage energy more effectively across different areas through modelling and forecasting. For agriculture in a controlled environment, machine learning could help to create the best possible growing conditions — adjusting light exposure or water delivery. It could improve the way cities are planned and run, for instance working out when and where public transport is most needed, or when certain roads are busiest. Hyperlocal weather forecasting could also help individual villages or farmers plan for extreme weather events.

Machine learning can also help first responders and government identify heavily damaged sites after a natural disaster. Hypergiant have recently released an an open-sourced AI model that uses satellite imaging for this purpose. They have made it and several other AI projects available on a platform called Modzy , built by consulting firm Booz Allen Hamilton.

Automation

From factories to phone networks, steering vehicles to controlling temperatures, automation is already revolutionising the way we live. Part of the point of gathering and processing data is to get insights that can then inform action. In automation, those actions are not carried out by people, but are passed along to control units that can execute predefined instructions. Automation is, in theory, more efficient, and it also reduces overall costs. It could have numerous applications that might help to reduce emissions and waste. In agriculture, in-ground sensors could detect water levels and relay the information to water delivery systems, thus automating irrigation management. Driverless cars could revolutionise transport and logistics. Robots could allow the 3D printing of bricks for buildings. The possibilities are endless.

Want to explore the other nine Frontier Technologies for Climate Action? Click here.

Is there a technology here that captures your attention? Put your thoughts in the comments section below or get in touch at ftlenquiries@imcworldwide.com