Hydroscope actively tries to minimise it’s environmental footprint whenever it can through different actions.
low computing power #
To this day, most of the Hydroscope code was developed, tested and built to run on a 2014 MacBook Pro. Some machine learning tools Hydroscope uses do require a bit more power, which is sourced through cloud computing solutions, that through economies of scale can keep the environmental cost of these computations to a bare minimum.
parsimonious data usage #
Although an important part of what Hydroscope does is to generate more contextual data from the data you provide, the overall size of data in our system is kept to a minimum, using all available strategies from reducing the stored data to efficient data compression. Each sailing session generates roughly 100Mb of data in the worst case scenario. This keeps the volume of data on our servers to a low level, reducing their environmental impact to a minimum.
green hosting #
Hydroscope data is stored on servers that are powered by renewables, reducing their environmental footprint even more.
low website consumption #
This website, is made to be as efficient as possible to keep loading times to a minimum. It’s coded as a static site with hardly any sever side computations, doesn’t use heavy user tracking tools (such as google analytics) and doesn’t employ fancy javascript animations.
remote data collection #
Although the Hydroscope team is always happy to meet its clients in person, most of our interactions are done online, significantly reducing the emissions liked to transport.