Climate change has a direct impact on the agrarian societies, the frequency of natural disasters and the overall ecology of the planet. Using artificial intelligence, countries like Norway and India have made significant development in increasing their crop yields (30% increase in groundnut yields) and production of flexible and autonomous renewable energy grids and circuits. AI has also helped scientists map cyclones, atmospheric rivers, and weather fronts with 89 to 99 percent accuracy. These things were often hard to identify and predict beforehand, until now.
Today, issues like water conservation, agriculture, biodiversity, and climate change are increasingly getting addressed by AI-powered terrestrial machines and geospatial satellites. Scientists and innovators in technology-driven conglomerates are educating themselves through artificial intelligence courses online.
It is a game changer
According to Global Goals Coast, Artificial Intelligence reveals that 61% of all the world’s population is concerned and anxious about climate change. Artificial Intelligence can learn from data with intricacies and precision to give more specific and in-depth predictions. Currently used softwares have an average resolution of 62 miles ( i.e. 100 kilometres) making it good enough for generic atmospheric predictions, but not good enough to give detailed information on aspects like features of clouds.
Using Machine Learning, scientists can make more accurate predictions. This information from climate scientists can be imparted to administrative leaders by influencing their decisions on how to react to the effect of environmental change.
Cube Satellites are compact, cheap and will provide real-time monitoring of climate change as well as its countermeasures. Cube satellites generate big data at an enormous speed which translated into actionable insights. Generation of huge amounts of data helps scientists better understand climate change over a relatively small region with more accuracy, leading to more specific solutions.
For instance, the satellite can be trained to use machine learning to calculate the actual cost of carbon emissions. Carbon emitting industries can, then, justify the use of renewable energy alternatives, keeping intact their profits and efficiency of operations.
GeoAI Data Science Virtual Machine (GDSV)
Technology giants Microsoft and Esri have collaborated to build an AI-powered machine that will, by using cloud technology and infrastructure, analyse the geospatial data to visualise and give solutions to pressing environmental concerns. The device will additionally be intuitive and interactive and will use Geographic Information System (GIS) that generates 2D and 3D maps of its focus areas.
According to Microsoft representatives, GeoAI Data Science Machine is an experimental project that uses tools like artificial intelligence, machine learning and data science tools to provide intelligent predictions. Microsoft’s flagship initiative AI for Earth provides grants to organisations for adequate environmental protection, research and innovation.
AI predicting natural disasters
Natural disasters like earthquakes and tornadoes are hard to predict as they strike unexpectedly, doing immense damage to property and life. However, a team of geophysicists from Pennsylvania State University and Los Alamos National Laboratory have been harvesting data on stimulated quakes and using machine learning tools, to find common earthquake causing variables.
What they’ve noticed is that a “squeaking and crushing commotion” in the acoustical information has turned out to be a valuable indicator that enables them to pinpoint the onset of an earthquake. While these discoveries may not be completely applicable in the present-day reality, a few researchers are hopeful that AI could, at last, furnish the capacity to figure seismic tremors.
Machine learning assumes a vital role in the climate predictions across the globe each passing day. Innovations are being utilised to predict when a typhoon will hit.
An organisation called One Concern has made a vigilant AI program called Seismic Concern that is dealing with events like forest fires, floods and hurricanes. Seismic Concern takes information about seismic activity, the structural sturdiness of surrounding building and the socio-economics of the individuals that may get affected. It goes on to provide customised facilities according to the needs of people spread in different areas.
The more we use AI and machine learning innovation, the more enabled we will be to comprehend our present reality, foresee future climate changes and make innovations that limit how much humans are affected by it. Business organisations can be made proficient by adopting greener and more environmentally friendly alternatives that are linked with artificially intelligent machinery.
Developing better solutions
Scientists and innovators at Green Horizon Product of IBM test El Nino scenarios that may occur in the future. The scientists are trying to theorise a pollution-free methodology in business models and lifestyle trends. Google has reportedly cut down 15% of its carbon footprint by adopting artificial technology in its operations.
Not only does AI find greener solutions in the climate change aspect, but it also directly benefits citizens save their own money and resources. Using AI-powered thermostats that can intelligently control indoor temperatures can help in saving as high as 30% energy
Because artificial intelligence cannot yet determine why and how a natural disaster occurs, scientists are not fully confident in relying on predictions made by AI-powered machines alone. Climate enthusiasts are, however, using the suggestions given by bots and combining it with their professional and experiential knowledge to device a more informed and accurate forecast.
Salman is a prolific environmental writer, and has authored more than 300 articles in reputed journals, magazines and websites. He is proactively engaged in creating mass awareness on renewable energy, waste management, sustainability and conservation all over the world.
Salman can be reached on firstname.lastname@example.org.
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