Satellites are our eyes over space and Google has come up with a new method to utilize this giant monster in a more better way. Google has teamed up with a nonprofit AI firm called WattTime to monitor emissions from all the world’s power plants using satellites.
In a nutshell: by the use of satellites, WattTime is going to precisely track the air pollution (including carbon emissions) coming out of every single power plant in the world, in real-time with an AI-powered algorithm.
This project aims to keep tabs on every single power plant in the world. However, the program will prioritize those power plants that currently fly beneath the radar.
WattTime AI is a Carbon Tracker and it will help to decrease dirty energy use.
In recent experiments, the Carbon Tracker has already proven how effective this sort of satellite spying can be, using it to estimate the use of coal plants in China year.
WattTime also says that the system is capable of identifying heat from smokestack plumes or cooling-water discharge by the use of infrared imaging and the sensors that can directly track NO2 emissions are in development.
With the use of this AI-system, WattTime will be able to derive exact, real-time emissions information, including information on carbon emissions, visible smoke, heat, and NO2 for every power plant in the world.
The resent results of this technology where satisfying and soon WattTime and WRI approached the team at Carbon Tracker about expanding this methodology to every single power plant in the world.
Researchers said the WattTime’s program will be very useful in the upcoming future to analysis and to better identify those areas where renewable energy is already cheaper than fossil power.
WattTime hopes this project will help to bring an end on pollution in many ways.
The AI system will further also contribute as a think tank that will focus on the financial part of transitioning away from fossil fuels and the World Resources Institute (WRI).
The satellites will publish this information in real-time online where anyone can access it: individuals, nonprofits, government entities.
If we talk about the overall stage of development of WattTime AI, then it is still in its early stage and many things are still needed to fix like, It relies on images that clouds can mess with, so the quality of the data gathered varies.
Also, the satellites can’t measure what kind of pollutants are being emitted, or how much exactly. They can provide estimates, though, and that’s better than nothing in places where the data just doesn’t exist.
But these flaws will eventually get fixed as the project will start to gain more maturity and it is also a great initiative towards harmful events like Global Warming and Pollution.
Over the period of history, poor monitoring and gaming of emissions data have made it difficult to enforce pollution restrictions on power plants. This system promises to effectively eliminate poor monitoring and gaming of emissions data.
As per the latest report by the State of Global Air report, air pollution is the fifth greatest global mortality risk.
It causes 5 million early deaths and 147 million years of healthy life lost, every year, and the countries building the most power plants are experiencing the most air pollution.
Who is WattTime?
AER is a program that uses real-time grid data and machine learning to determine exactly when the grid is producing the cleanest electricity.
It can then automatically adjust power consumption to match up with those times, ensuring that users take advantage of the lowest-carbon power available.
(Many kinds of power consumption can be safely shifted in time, like water heaters, battery charging, and some industrial processes; they are “dispatchable.”) AER is, as the name indicates, entirely automated; it works behind the scenes, without any user intervention.
WattTime is a mission-based nonprofit with a track record, legitimate partners, and serious financial backing. Despite its diminutive size, it has a chance of becoming the global clearinghouse for transparent, reliable pollution data.
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