12 ways how AI can help to solve the problem of global warming

With the rapid development of technologies of artificial intelligence (AI) in recent years, many began to wonder about how these same technologies can help in addressing one of the most serious threats that has hung over humanity – global climate change? A new article prepared by one of the leading experts in the field of development of artificial intelligence and published in online repositories arXiv.org trying to answer this question, offering several examples of how machine learning will be able to prevent the sunset of our civilization.

The proposed methods range from the use of AI and satellite technologies for more effective monitoring of deforestation, to develop new materials that can replace steel and cement (for their production accounts for up to 9 percent of the greenhouse gases in the atmosphere). Despite this diversity, in his article, the experts return time and time again to broader possibilities of using such technologies. Especially against this backdrop stand the possibilities of using the technology of machine vision for monitoring the environment; conducting big data analyses to determine the inefficiency of the industries with high emissions of harmful substances into the atmosphere; and the use of AI to develop new more effective models of systems, like our climate models, through which we can better predict and prepare for future changes.

The authors of the article, including including a British artificial intelligence researcher, founder and CEO of DeepMind Demis of Hassabi, winner of the Turing award and one of the “fathers of deep learning” by Joshua Bengio and co-founder of Google Brain — Google research project for the study of artificial intelligence based deep learning — Andrew ng say that AI can provide “invaluable assistance” to minimize the worst effects of global climate change, but add that this technology is not a “silver bullet” — the only means from all problems. In their opinion, this issue needs to take a direct active participation of political forces.

“Only technology is not enough. Technology that can reduce the effects of climate change have been available for many years, but to a large extent and scale, they unfortunately were not adapted by the society. And although we hope that machine intelligence can be useful in reducing costs associated with the use of methods aimed at reducing the effects of climate change, mankind must also take an active part,” write the authors of a new study.

In total the article discusses several areas in which machine learning could be applied, kategorizovanih in the time frame of their potential use explained by the fact that there is enough developed this technology. Below you can review this list.

Artificial intelligence will improve the efficiency of power supply systems

If in the future humanity plans to rely on more renewable energy sources, utility companies will need ways to more effectively predict and calculate the amount of energy that we really will need to use. Moreover, these calculations will need to occur in real time and throughout the period of operation of these enterprises.

Already developed algorithms that can predict energy demand, however, the effectiveness of these algorithms can be further improved by making the calculations on such factors as the climate of certain regions and peculiarities of conducting economic activity. Attempts to make the specifics of these algorithms more understandable also will enable operators of utility companies to more accurately interpret the results of their analysis and use in planning, choosing the optimal time to start these sources of renewable energy.

Artificial intelligence will help in the discovery of new materials

Scientists need to develop new materials for more efficient production, storage and use of energy, however, as a rule, the process of discovery and development of new materials is very slow and not always successful. Machine learning technology will allow to accelerate process of search, development and improvement of new formulas with the desired properties.

Perhaps this will lead to the development of, for example, a new type of fuel, let’s call him “Sunny”, which will be able to retain the energy of sunlight; will create new and very effective absorbent of carbon dioxide or construction materials, the production of which will stand out less carbon. These materials will one day be able to replace steel and concrete, whose production in the atmosphere produces almost 10 percent of total world greenhouse gas emissions.

Artificial intelligence will help to reorganize the transport system

Delivery of goods around the world is very complicated and often inefficient logistics process in which the interaction of products of different volumes, weights and sizes and using different modes of transport. At the same time, transport accounts for a quarter of all CO2 emissions. Machine learning technology used in this area, will more effectively combine goods require delivery to the same destination, which will reduce the number of required transport. In addition, such a system would be more resilient to unexpected disruptions in the systems of transport and will be able to manage huge fleets of unmanned trucks. However, the authors note that at the moment the technology is still not ready.

Artificial will lead to fast adoption of electric vehicles

Electric cars, a key element of decarbonisation vehicles face a number of challenges, not allowing them to become truly mainstream. This question can help machine learning, according to the report. For example, using algorithms you can improve the management of energy consumption in batteries to increase mileage per charge, and reduce the potential buyers of such vehicles the level of concern about limiting the distance of travel. In addition, these technologies allow to optimize the charging time.

Artificial intelligence optimizes the infrastructure of the buildings

Smart control system operating on the basis of machine learning can greatly reduce the energy consumption of buildings, taking into account weather conditions, current employment, buildings and other environmental factors, then appropriately adjusts the heating, cooling, ventilation, lighting in the room. Smart buildings can transmit information about the current state of the environment directly in the grid in order to reduce the level of energy consumption in the case that there is a shortage of low-carbon electricity.

AI will be able to more accurately calculate the number of used energy resources

In many regions of the world practically there are no data on the level of local consumption and the emissions of greenhouse gases in the atmosphere, which can be a big problem for the development and implementation of effective compensation measures. Methods of computer vision allow the use of satellite technology to estimate area (square) units, to machine learning algorithms based on these data, calculate the levels of energy consumption and emissions. Similar methods can be used to identify buildings requiring modernization to improve their efficiency.

Artificial intelligence can optimize supply chains

Using similar capabilities, machine learning technology to optimize the channels and supply chain to minimize emissions of hydrocarbons in the transport of various goods. The possibility of more effective prediction of the law of supply and demand will reduce production and transport waste.

Artificial intelligence makes the scalable precision agriculture

Most modern agricultural farms use the principle of cultivation of monocultures. In other words, over a large area grown only one culture. This approach facilitates to farmers the task of the processing field of agricultural machinery and other basic standalone tools, but at the same time depletes the soil, depriving it of nutrients and thereby making it less productive. The result is to increase yields is often used a variety of fertilizers, particularly nitrogen-based, which can turn into nitrogen oxides – greenhouse gases 300 times more dangerous than carbon dioxide. Robots using machine learning can help agriculture to assess the current condition of the soil and suggest what you need to plant crops to restore soil health, reducing the need to use fertilizers.

AI will help to more effectively monitor deforestation

Deforestation contributes to the emissions of about 10 percent of the total greenhouse gases. Tracking and prevention of this often illegal activities – usually very time-consuming and routine process that requires personal observation on the spot. In turn, satellite imagery coupled with computer vision technologies allow automatic analysis of forest cover loss in large scale and the special sensors installed on the stations in combination with algorithms, for example, can identify the sounds of chainsaws, can help law enforcement more effectively combat illegal activities.

AI will help to change our consumer attitude

According to the authors of the report, “the world’s a widespread misconception that ordinary people can have a serious effect on climate change.” Therefore, in this question it is necessary to clarify exactly how people can help. Machine learning technology will allow us to calculate the carbon footprint of man (the totality of all greenhouse gas emissions that it creates in the course of daily activities) and to make small changes that will allow it to reduce. For example, the system can suggest more use of public rather than private transport; less likely to buy in the store meat; or reduce electricity consumption at home. Each of us individually creates a small carbon footprint, but if you take all at once, the numbers will be much greater. Changing our relationship to consumption and the sum of all individual actions can have a big cumulative effect.

AI will increase the efficiency of meteorology and climatology

Many of the most significant impacts of climate change in coming decades will be associated with very complex natural systems, such as the changing dynamics of cloud or ice cover. These are the questions whose solution depends on the AI hopes. Accurate modeling of these processes will help scientists more effectively predict extreme weather conditions (e.g. hurricanes and droughts), which in turn will help States to develop methods of protection from the worst effects of these phenomena.

Artificial intelligence will help with geoengineering

At this stage, this use of AI among all the above is highly speculative, but it also hopes at least some scientists. If we can develop ways to make the cloud cover of our planet more reflective or even create artificial clouds to aerosols, we can reflect from the Ground is more sunlight. But this issue requires serious investigation. AI can help, but the authors of the report note that this method is the use of artificial intelligence – the question is very long term, which will require cooperation of all governments of the world. Agree with this position, for example, specialists of the canadian Waterloo University, who believe that this is an unreasonable approach to the issue of geoengineering to start a third world war.

Discuss this article in our Telegram chat.

Leave a Reply

Your email address will not be published. Required fields are marked *