As climate change becomes more apparent, our environment is facing a huge challenge.
There is now a sense of urgency among researchers and businesses to have sustainable solutions in order to address the climate crisis.
One of the most proactive ways of the now-present effects of climate change is through the power of technology.
With the increasing number of weather events provided by scientific research such as hurricanes to extreme drought, rapid increase of sea level due to global warming, wildfire, and intense flooding, the effects of these changes will affect different forms of life including individuals and companies.
Billions of dollars, livelihoods, and communities are at risk due to climate change.
The climate realities that the Earth is facing now came from decades of machineries, financial crisis, and collapse of oil prices.
What is Climate Change Intelligence?
We had a boom of clean technology in the early to mid 2010’s wherein stakeholders plunged millions of dollars into startups. However, these startups are still in the research and development stage of their business and in return, they lost more than they received as it required to shell out more money and time.
Due to the complexity of the crisis, the sheer amount of data in relation to the climate is difficult to track and manage. With that, interested players ranging from startup entrepreneurs to mainstream companies are now looking at sustainable-driven technology to assess the granular data and forecast climate predictions. Machine learning and artificial intelligence are ways to move forward.
Simply defined, Climate Intelligence (CI) is used for data and analysis to predict climate information, determine how climate is changing, understand how those changes affect our society and economy, and how to adapt accordingly.
Hence, a need for a more robust source of Business Intelligence emerged.
In order to address immediate and future business decisions that concern climate risks, Climate Intelligence (CI) came into the picture.
Climate Change, Machine Learning, and Artificial Intelligence
According to a recent study, Machine Learning (ML) is an ideal tool to address climate change and reduce greenhouse emissions with the collaboration of individuals from different fields. The use of machine learning and artificial intelligence (AI) has assisted the problem of societal and global good, but this movement is now towards identifying on how to approach and the issue of climate change.
Client Intelligence (CI) is generated through the gathering and analysis of an immense volume of data through machine learning and artificial intelligence.
Data is gathered through drones, nano and micro-satellites, and ground sensors to pick-up large amounts of information faster in our environment daily ranging from land, air, and wate.
However, raw data is not enough. With the data and information gathered through the advancement of technology, researchers and businesses can produce analyses and insights faster.
Adding to the new large sets of information collected through artificial intelligence and machine learning, and historical data, information on climate change and its solutions can be targeted instead of generalization.
Different algorithms and data used by artificial intelligence may also allow researchers to provide data with high-resolution images provided by the national government and companies. This may not only monitor the natural environment but man-made environment as well like vegetation, infrastructure, and land cover changes.
For instance, the use of artificial intelligence (AI) can gather images of power plants that release carbons which contribute to air pollution. It can generate analysis of emissions being released and this can measure its impact on nearby infrastructures.
Researchers, entrepreneurs, and corporations have responded to the urgency by integrating their expertise, data and analysis gathered through different data sources, machine learning and artificial intelligence (AI) to further understand climate change and innovate in various sectors such as agriculture and infrastructure.
Contact us here and find out more on how CLIMATIG can help you.
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References for further reading:
Wen, J. (2019, September 12). Climate intelligence: a clean way forward – Digital Initiative.
Eastling, J. (2021, February 5). Climate Intelligence: The Digital Fabric for Climate Action – Medium
Snow, J. (2019, July 18). How artificial intelligence can tackle climate change – National Geographic.