How neural networks help in the fight against climate change


Artificial intelligence systems have been criticized for their high energy consumption. However, this technology also has the potential to provide solutions to combat the effects of climate change

What’s the trend?

Under the influence of anthropogenic factors, the concentration of greenhouse gases in the atmosphere is increasing. As a result, we are experiencing global warming – an increase in the average temperature on Earth, the main cause of which is human activity. It has been observed since the end of the 19th century, and its speed is constantly increasing.

If warming is not stopped, the planet will face negative consequences: some coastal cities will disappear, there will be many more starving people, and wars will break out over vital resources. Therefore, the fight against it is a stable trend of our century. AI will help humanity cope with global warming.

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AI to combat global warming

To prevent the effects of climate change, a number of measures should be taken. These include identifying sources of harmful emissions, using renewable energy sources, forecasting floods, forest fires and others.

Researcher Lakshmi Babu Sahir from Anglia Ruskin University is studying exactly how AI can be used to combat global warming. It identifies four main areas: energy, transport, agriculture, and disaster forecasting.


AI can reduce the negative consequences of this area by more accurately forecasting supply and demand. Neural networks can identify patterns in how and when people use electricity. It is also possible to predict the amount of energy generated using clean sources such as solar panels and wind generators. This data can help you use electricity more efficiently.

By estimating the amount of energy obtained from green sources, AI is able to plan  the most “profitable” time for washing clothes or charging an electric car. On an industrial scale, AI will help power grid operators prevent and reduce power system failures.

Iranian scientists  used AI to predict a research center’s energy consumption. The occupancy of the building, its structure and local weather conditions were taken into account. Based on the data obtained, specialists developed algorithms that reduced energy consumption by 35%.


Transport accounts for about 20% of global CO 2 emissions . AI models can create eco-friendly travel options by advising drivers on routes with the least amount of congestion and continuous traffic. This will reduce exhaust emissions.

In addition, AI can also be useful for traveling in electric vehicles. In 2021, Swedish researchers proposed an AI-based system that plots routes for electric vehicles with minimal energy consumption. To do this, the system took into account characteristics such as vehicle speed and the location of charging points.


Several scientific papers have demonstrated that more efficient agricultural practices can reduce negative environmental impacts. Ai can develop a plan for the economical use of space and fertilizers.

A study by Stanford University scientists back in 2017 showed that advanced AI models can predict soybean yields at the county level. This result was made possible by using satellite imagery to analyze and track crop growth. Predicting crop failure will help plan alternative ways of purchasing food.

Disaster Management

AI is contributing to disaster forecasting and mitigation. For example, an AI model proposed by a group of international scientists in 2021  studied drone images to predict flood damage in the Indus River basin in Pakistan.

Forest fires release smoke particles into the atmosphere. This air pollution contributes to the greenhouse effect. Fires can be prevented using artificial intelligence technologies. Technology company Overstory AI uses AI to process satellite imagery and climate data. As a result, the project helps detect fires to quickly eliminate them.



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