Artificial intelligence and machine learning can help analyze large amounts of environmental data to better understand climate change and predict future impacts. AI is used to identify patterns in data from sensors monitoring conditions around the world. This data provides insights into vulnerabilities and helps predict extreme weather events. AI technologies can also optimize renewable energy production and design more energy efficient systems, buildings and consumer products to mitigate climate change. However, training AI models also contributes to carbon emissions which must be addressed.
2. The Effects of Machine Learning and Artificial
Intelligence on the Analysis of Environmental
Big Data and the Prediction of the Future of the
Environment
« ِِﯾمﺣاﻟرﱠ ِنَﻣْﺣاﻟرﱠ ِ ﱠ
ﷲ ِمِْﺳﺑ »
Iran University of Science & Technology
School of Management, Economics and Progress Engineering
Milad Jahandideh (99229184)
Dr. Majid Hosseinzadeh
5. Artificial Intelligence
A non-human program or model that can solve sophisticated tasks.
For example, a program or model
that translates text or a program
or model that identifies diseases
from radiologic images both
exhibit artificial intelligence.
6.
7. Data and Dataset
A collection of examples.
Data is an essential part of machine learning.
If you would like to build any machine learning system you need to either get the data (e.g. from
some public resource) or collect it on your own.
All the data that is used for either building or testing the ML model is called a dataset.
9. Machine Learning
A program or system that builds (trains) a predictive model from input data.
The system uses the learned model to make useful predictions from new (never-before-seen) data.
10.
11.
12.
13. We utilise AI and machine learning technology to help us:
● Understand our current reality
● Predict future weather events
● Create new products and services to minimise our human impact
● Making businesses more efficient
How can AI help combat climate change?
14. Climate Study: Big-Data
Machines can analyse the flood of data that is generated every day from sensors, gauges and monitors
to spot patterns quickly and automatically.
By looking at data about the changing conditions of the world’s land surfaces that is gathered by NASA
and aggregated at Landsat(https://landsat.usgs.gov/), it provides a very accurate picture of how the
world is changing.
15. This information can be used to identify our biggest vulnerabilities and risk zones.
This knowledge from climate scientists can be shared with decision-makers so they know how to
respond to the impact of climate change—severe weather such as hurricanes, rising sea levels and
higher temperatures.
16. Better Weather Event Predictions
The damage to human lives and property can be reduced if there are earlier warning signs of a
catastrophic weather event. There has been significant progress in using machine-learning algorithms that
were trained on data from other extreme weather events to identify tropical cyclones and atmospheric
rivers.
https://www.technologyreview.com/2017/08/23/105467/climate-change-research-is-getting-a-big-dose-of-ai/
● The technology is already being used to send natural disaster alerts in Japan
● Monitor deforestation in the Amazon
17. Developing Better Solutions
Artificial intelligence and deep learning can help climate researchers and innovators test out their
theories and solutions about how to reduce air pollution and other climate-friendly innovations.
18. By using the information provided by machine learning algorithms, Google was able to cut the amount of
energy it used at its data centres by 15%. Similar insights can help other companies reduce their carbon
footprint.
https://www.theguardian.com/environment/2016/jul/20/google-ai-cut-data-centre-energy-use-15-per-cent
20. There are several consumer-facing AI devices such as:
https://venturebeat.com/2017/10/25/ai-powered-devices-are-helping-consumers-battle-climate-change/
https://store.google.com/us/product/nest_learning_thermostat_3rd_gen?hl=en-US&GoogleNest
● Smart thermostats regulate energy consumption
● Automatically switching off lights not in use
● AI applications could also help design more energy-efficient buildings
● ....
21. Optimizing Renewable Energy
Engineers often face issues with predicting weather changes, calculating demand-supply ratio, surplus
planning, and more. Machine learning algorithms process humongous amounts of data to gain insights
on energy requirements and ways of meeting those energy demands.
Whether it is real-time weather conditions, data from the solar panels, pollution metrics and more, ML
algorithms can turn these data into useful information.
AI can also monitor and operate power plants according to optimal weather conditions.
22. Some homeowners have already experienced the
effects of a changing environment. For others, it
might seem less tangible. To make it more
realistic for more people, researchers from
Montreal Institute for Learning Algorithms (MILA),
Microsoft, and ConscientAI Labs used GANs, a
type of AI, to simulate what homes are likely to
look like after being damaged by rising sea
levels and more intense storms.
https://www.nationalgeographic.com/environment/article/artificial-intelligence-climate-change
Showing the effects of extreme weather