Clean tech defines a set of technologies that reduce, eliminate, or optimize the use of natural resources. However, energy and climate change that are not bound by borders are a globally shared issue. So, how do we track the current state of the environment and the impacts of our decisions?
Ongoing efforts towards greater cohesion between the modern world and environment around us are much greater than. From harnessing renewable energy to using it efficiently in the home, data science is used in many ways.
With the expanding IoT, we have more opportunities to collect and share data relevant to green energy. So much so that human minds cannot effectively analyze the amount of data on our own. Using data analytics, energy companies and engineers can optimize their current processes operations, create more efficient tools, and have deeper insights for making decisions.
In the past, clean energy was desirable but costly. By harnessing the power of data science and optimization, clean energy costs have declined to a fraction of what they once were. From 2009 to 2019, costs of solar power and onshore wind electricity declined 90% and 70% respectively (Our World In Data).
In particular areas such as B.C, hydropower has also become the leading source for electricity generation. Of course these all came by the advancement of new technology, but more so how we maximize efficiency of existing technologies through predicting trends using data analysis.
This way, the impact of data science is an exponential multiplier of the technology we have at hand.
