AI and Sustainability: 8 Ways AI Can Help The Environment

Thoughts on AI and Sustainability: 8 Main Ways AI Can Help Achieve Environmental Sustainability

By Melanie Johnson

This article provides an informative introduction to Artificial Intelligence (AI), its environmental effects, and, most importantly, its promise to revolutionize today’s world. We may expect a more sustainable and wealthy future if several AI technologies come together.

Artificial Intelligence, or AI, is a rapidly evolving field that transforms how humans live, learn, make decisions, and work. In fact, AI systems work by iterating and learning based on massive amounts of labeled training data, which makes it feasible for them to have perceptions similar to those of humans.

The technique for creating training data for both Artificial Intelligence (AI) and Machine Learning (ML) is guaranteed by image annotation. Video annotation, like image annotation, helps modern machines recognize objects. However, in addition to identifying and recognizing objects, video annotation is used to build the training data set for visual perception-based AI models.

AI and sustainability bond

Reading about AI intelligent devices and technological advances seems mind-blowing and thrilling; however, training AI models could cast doubt on its benefits at first glance. AI-based models need to process a lot of data, which inevitably raises the requirement for computing power and electricity and the necessity to keep data centers cool. Due to their high energy requirements, AI systems can have high financial and environmental costs, leaving a considerable carbon footprint.

Fortunately, in addition to producing a carbon footprint, AI also has the potential to reduce it and become more sustainable. Google’s DeepMind division, for instance, has developed artificial intelligence that teaches itself how to conserve energy while cooling the company’s data centers, reducing energy consumption by 35%.

Selecting only the most pertinent data for training or effectively modifying existing models for a new task, which dramatically lowers the cost of training a model, is one way to make AI more sustainable.

Another area relates to edge computing which decreases the reliance on cloud services for data processing. Neuromorphic computing is an alternative field that draws inspiration from how the brain functions. The energy-intensive nature of current computer models is intended to be solved by neuromorphic architecture in order to sustain AI.

AI and Sustainability: Light reflected on a shop window containing Mad Max-like characters in Rome, Italy
Light reflected on a shop window containing Mad Max-like characters in Rome, Italy
Photo by Gabriella Clare Marino on Unsplash

How can AI make the environment more sustainable?

Can AI aid in the creation of a more sustainable world? The simple answer is yes! Addressing and resolving environmental sustainability challenges is difficult, but the introduction and evolution of artificial intelligence have made the impossible possible. Here’s how:

  • AI-optimized models can offer other strategies for biodiversity protection.
  • It can decrease energy consumption and avoid electricity waste by monitoring energy usage.
  • AI provides effective approaches to water pollution and scarcity.
  • AI has the potential to create more environmentally sustainable transportation networks.
  • AI can uncover undiscovered patterns in manufacturing processes or operations.
  • It can minimize air pollution and improve its quality.
  • AI can enhance overall harvest quality and accuracy.
  • AI-based models can forecast extreme weather events and natural disasters, allowing for proactive measures to be taken.

Biodiversity

Numerous reports describe how artificial intelligence (AI) is being used to improve biodiversity monitoring and conservation.

When paired with satellite imagery, AI can identify changes in land use, vegetation, forest cover, and the effects of natural disasters. Furthermore, invasive species can be supervised, recognized, and documented. Identifying and tracking their presence, as well as eliminating them, is accomplished through the use of machine learning and computer vision.

For example, Blue River Technology, a company that uses artificial intelligence, has an easier way of detecting the presence of invasive species and other changes in biodiversity. Lastly, Anti-poaching squads can now easily arrange their patrol routes with the aid of predictive software.

Energy

Artificial intelligence (AI) is arguably used to reduce the consumption of natural resources and energy demands associated with human activities.

When it comes to energy research, the main focus areas include neural networks, expert systems, pattern recognition, and fuzzy logic models, as well as energy production and distribution, operations, and maintenance.

Smart grids, in contrast to traditional power grids, can use artificial intelligence techniques to regulate and control various neighborhood power grid components in order to deliver precisely the amount of electricity required or requested by its dependents. What is more, smart sensors and meters can be installed within buildings to gather information, monitor, analyze, and optimize energy usage.

Water

Here are the main ways AI can foster water conservation:

  • We can forecast stream flow and examine water quality metrics by using machine learning (ML) models.
  • In order to make informed management decisions, professionals can use AI to anticipate the weather and project water use in a particular area.
  • Droughts, as well as weather, soil, and subsurface water conditions, may be predicted using AI and satellite data.
  • AI can help water resource managers decrease costs and minimize environmental impact by reducing or eliminating waste.

Transportation

Artificial intelligence (AI) applications can also be used to obtain environmentally-friendly transportation. Computer vision techniques can be used to aid decision-making in traffic management and safety, as well as public transportation, urban mobility, and road marking. As soon as AI-powered autonomous vehicles enter the market, techniques such as route optimization, eco-driving algorithms, and shared transportation services will help to reduce the carbon footprint and the actual number of cars on the road.

Manufacturing

Artificial intelligence (AI) in manufacturing can help manufacturers reduce waste and energy use. Another issue that sophisticated learning machines and intelligent networks can help with is controlling industrial pollutants and waste management. This equipment and network can detect leaks, potential hazards, and departures from industry standards and government requirements. For example, the Internet of Things (IoT) technology has been employed in a range of industrial efforts, including refrigerators, thermostats, and even retail establishments.

Air

A practical strategy to manage and reduce air pollution is artificial intelligence. AI may gather data from sensors and satellites and assist scientists in mixing climate models. Here are AI applications for better and cleaner air:

  • Urban people may be warned about the pollution levels in their neighborhoods using simulations driven by AI. There are tools available that can quickly and accurately pinpoint the sources of pollution.
  • Using information from cameras, radar sensors, and moving objects, AI can minimize air pollution.
  • AI-enhanced air purifiers may continually record environmental and air quality data and modify their filtering performance.

Agriculture

Artificial intelligence (AI) has the potential to transform agriculture by better monitoring and managing environmental conditions and agricultural yields.

Farmers may utilize drones and satellite pictures to assess soil quality and crop productivity. John Deere, for example, annotates camera images to discriminate between weeds and crops at the pixel level, then uses the information to administer pesticides only to weed-infested areas. The corporation saves a lot of money on pesticides while improving agricultural production.

Weather forecast and disaster resilience

  • Some devices such as drones and cutting-edge sensor platforms can be used to monitor earthquakes, floods, windstorms, sea-level fluctuations, and other natural disasters. By predicting the impending threats beforehand, early evacuations can be possible.
  • Another application is the combination of AI with classical physics-based modeling tools, which will assist many meteorological businesses in simulating the effects of catastrophic weather events on infrastructure and other systems, allowing them to advise on disaster risk management techniques.
  • AI can enhance earthquake prediction, tsunami warning, and early recognition of wildfires by using geological data from research centers worldwide.

Can AI, after all, ensure a sustainable future?

If the answer to this question has not been clear to you yet, here are a few stats:

  • According to PwC UK research, deploying AI for environmental applications may contribute up to $5.2 trillion to the global economy in 2030.
  • Simultaneously, the employment of AI levers might cut global greenhouse gas (GHG) emissions by 4% by 2030.
  • As part of this shift, AI may produce 38.2 million net new employment throughout the global economy, delivering higher-skilled vocations.

To summarize, Artificial Intelligence (AI) is the ability of trained machines and computers to simulate human intelligence, such as recognizing objects, understanding and responding to language, making decisions, solving problems, etc.

This article aimed to emphasize AI’s potential within a variety of disciplines to manage our environment more effectively and sustainably. Apart from having a somewhat detrimental influence on the environment, AI has the ability to positively impact the environment in areas like agriculture, energy, water, transportation, and others. By more effectively regulating crop yields and environmental circumstances, AI can revolutionize agricultural output.

AI can aid in reducing carbon emissions and guarantee that everyone has access to inexpensive, dependable, and clean energy by providing intelligent grid systems. By minimizing or eliminating waste, decreasing costs, and lessening environmental consequences, using AI to water resource forecast, management, and monitoring can assist in relieving the worldwide water issue.

Overall, we are very close to creating a better world where the most pressing environmental concerns would be addressed and resolved through AI. By leveraging its power, we will soon accelerate the global efforts to achieve sustainable development goals.


About the Author

Melanie Johnson is an AI and computer vision enthusiast with a wealth of experience in technical writing. Passionate about innovation and AI-powered solutions, she loves sharing expert insights and educating individuals on tech.

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