Ways in which Artificial Intelligence helps protect the environment

A review of the data of the GRACE satellite (Gravity Recovery and Climate Experiment), installed in 2002 to visualise the terrestrial changes, have determined terrifying data for our planet: it confirms the depletion of groundwater, the loss of 260 billion of tons of ice per year in Greenland and 140 billion tons in Antarctica, between 2002 and 2017.

The increase in global temperature, the rise in sea level, polluted air in cities and the loss of a large number of habitats, form our reality. And with that, the destruction of the planet is a reality.

In this context and taking into account the technological boom, how can we take advantage of technological innovations to promote and establish a sustainable world?

Here is where Artificial Intelligence (AI) raises its hand…AI, a technology that is allowing the implementation of solutions to face the problems of the Earth, according to the AI ​​for Good World Summit and the study carried out by the ITU News Magazine, based on in the conclusions of the PwC report “The fourth industrial revolution and the planet”.

1. Smart agriculture

AI ​​allows correcting actions in agriculture due to automation through robotics, so that it enables the detection of diseases and problems of crops in their initial phase, programming the feeding of livestock and profitable agricultural activities based on the offer and the demand. According to the mentioned report, this will allow to “increase the efficiency in the utilization of agricultural resources, reduce the consumption of water, fertilizers and pesticides that cause damages to important ecosystems, and increase the resistance to the extreme climate changes”.

2. Smart Cities

Sustainability within the cities is one of the most important parts in the plan of protecting the environment. Through automation, virtual reality and augmented reality, AI can generate real-time data on the activities of water and energy consumption, allowing to have a full knowledge to optimise the sustainability of cities.

3. Renewable energy

One of the main sustainable challenges that the world faces is the establishment of renewable energies in the main cities. In this case, AI can improve the storage and efficiency of energy, as well as facilitate the integration and reliability of these renewable energies.

4. AI and disasters

Predicting and preparing for disasters are two key points when it comes to saving lives and reducing the number of injuries and material damage as an aftermath. AI ​​allows to analyse simulations and real-time data on a set of catastrophes in a specific region, improving their preparation and providing coordinated alerts with the corresponding emergency services.

5. Weather predictions

According to the aforementioned study by PwC, AI technologies are being developed with the aim of improving our understanding of the effects of climate change, so that “in a little over ten years” advances in AI will make personal computers as powerful as the current supercomputers, accelerating scientific findings, due to a reduction of economic expenses in research.

6. Vehicles and AI

Autonomous and connected electric vehicles will reduce the production of greenhouse gases. According to the report “fleets of autonomous electric vehicles will be essential to achieve real benefits.”

7. Transparent management of the planet

The idea is to establish a “geospatial control panel for the planet” equipped with AI, in real time and with an open architecture that allows to control and manage environmental systems with a scale and speed still unknown to us. Thanks to this, we would be able to eradicate illegal water extraction, deforestation and the loss of biological diversity and air pollution, among other nature threats. According to the report, it is necessary to “collaborate with each other to have API and open source data and, ultimately, achieve a digital platform of public interest.”

8. The study of the earth and AI

It is essential that developers and AI experts collaborate with engineers and specialists in earth sciences in order to identify the systems that can be coded “to apply the reinforcement learning in favor of scientific advancement and discovery”. Among these systems we find climatic physics, material science and biology, among others.

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