Three ways AI can help fight climate change

Undoubtedly climate change is intensifying and the world continues to be devastated by storms, wildfires many digital tools, including artificial intelligence (AI), are being utilised to both predict and limit the impact of climate change.

There is a growing interest in machine-based learning systems that use algorithms to identify patterns in data sets and make predictions, recommendations or decisions in real or virtual settings. To share more into how AI can help fight against climate change, we highlight three example showing where it can have an impact.

Using AI to measure and minimise emissions in business

To support governments’ efforts to reach climate targets, organisations need to control their climate influence and reduce their carbon emissions. To do this, businesses need to accurately measure their baseline emissions, set targets and then act accordingly.

Typically hindered by the first step, if not all of them, AI-powered solutions can allow companies to tackle these steps through the same tool, which can inadvertently result in better decision making on climate-conscious strategies.

AI-powered solutions allow swift, dependable and rigorous baselining of the entire emission footprint, with improved accuracy, AI-based forecasts and simulations. One example of this is Google’s collaboration with electricityMap. By collaborating with this platform Google has coordinated computing tasks with times of low-carbon electricity supply in the grid and as a result, has cut down on the CO2 emissions caused by the consumption of electricity.  

AI and waste management

Poor waste management contributes significantly to climate change and air pollution and directly affects many ecosystems and species - particularly as landfills release a notable amount of methane. 

AI plays an integral role when it comes to waste management. By pairing this technology with the internet of things (IoT) sensors for intelligent garbage bins, AI can keep track of the availability of trash receptacles across a city, enabling municipalities to adjust and improve the routes, time and frequency of waste gathering. 

 But, until all bins are intelligent, waste needs to be sorted in a waste management facility, where AI can come into play again. Automated sorting is a lot more efficient, human workers sort between 30 and 40 recyclables per minute while AI-powered machines can handle up to 160 - and can work around the clock.

Advancing renewable energy with AI

Already, there are a number of programmes looking to optimise renewable energy. The global transition to renewable energy will need AI technology to manage decentralised grids. AI can also balance electricity supply and demand needs in real-time, and optimise energy use and storage to reduce rates.

With the help of AI software, decentralised energy sources can send any excess electricity they produce to the grid, while utilities direct that power to where it’s needed. Furthermore, the powerful prediction capabilities of AI will lead to improved demand forecasting and asset management.

The technology’s automation capability can also drive operational excellence in many crucial areas.