Mitigating Issues of High Ozone Layer with Artificial Intelligence
Scientists can now Predict the Mitigating issues of the High Ozone Layer by leveraging AI
It is a well-known fact that, by leveraging Artificial Intelligence, multiple industries are boosting productivity and ensuring employee safety worldwide. Industries include automobile, manufacturing, retail, agriculture, healthcare as well as aeronautics. The world knows about the functionalities of Artificial Intelligence and the issues of the high ozone layer of the earth due to global warming and pollution. What if scientists can protect the ozone layer by leveraging Artificial Intelligence? Yes, scientists can forecast the warnings from the high ozone layers up to two weeks in advance with the implementation of Artificial Intelligence. The University of Houston’s Air Quality Forecasting and Modelling Lab developed a new Artificial Intelligence system to control the ongoing issues of high ozone layer generate solutions effectively and efficiently to protect the earth. Scientists have taken initiatives to remove the substantial exposure of the ozone layer near the earth’s surface. This can reduce the possibilities of throat infection, breathing issues, asthma as well as respiratory troubles.
Weather forecast can be done two weeks in advance while the change in the high ozone layer can only be predicted two to three days in advance. The usual numerical model was creating a problem for researchers and scientists to predict the changes accurately. This breakthrough of developing a new AI system can enhance the accurate prediction for mitigating issues of the high ozone layer.
The team has achieved to build this first-ever cutting-edge technology, to forecast the ozone layer efficiently and accurately. They utilised a unique loss function in developing this machine learning algorithm that helped in the optimisation of the AI model through mapping decisions to their respective costs. There was an Index of Agreement or IOA to cover as the smarter loss function over the traditional loss function. The team used IOA to mathematically compare the gaps between what is expected and the outcome. It allowed the machine learning algorithm to forecast multiple accurate outcomes with the help of four to five years of historical ozone data.
Ozone is the secondary pollutant unstable and colourless gas formed by a chemical reaction after sunlight mixes with Nitrogen Oxides and highly volatile organic compounds. These chemicals can be found in multiple industrial emissions as well as the automobile industry. Scientists are working on predicting other types of pollutants with the expansion of this AI model.
Artificial Intelligence, is considered to be the best cutting-edge technology to forecast weather conditions, pollutions as well as natural disasters. There is no doubt, that industrialisation has enhanced the standard of living across the world. Meanwhile, the harmful emissions are destroying the lives of people through various respiratory diseases. AI models can predict accurate and promising outcomes due to their ability to analyse the environment with real-time data and historical data.