Three different patterns emerge when we analyze present-day artificial intelligence in climate change applications. The first pattern states that monitoring technologies perform way better compared to human abilities-whether in terms of speed or accuracy- from thousands of percentage points.
Second, implementation costs are the major challenge in every sector, ranging from the sensors on forests to the grid infrastructures. Third, all instances of successful deployments shared certain common characteristics, such as very good government support, collaboration with the private sector, and clear regulatory frameworks.
An increased number of solutions to fight climate change depend on scaling up these proven AI solutions. Most promising developments tend to be a mixture of , satellite monitoring, and ground sensors. This convergence indicates that the next big leap would integrate various AI approaches rather than singular solutions.
Also Read:
