Hydroscope is able to reduce the performance prediction error on the raw data coming from the boat by utilising 3 important tools :
- weather enrichment : adds weather context to the dataset with variables that cannot be measured in-situ (waves notably)
- ship enrichment: adds context about the state of the ship, which cannot be measured otherwise by onboard sensors
- mathematical processing : applies a mathematical treatment, using machine learning tools, to the data, transforming it into human-readable content.
The first two tools allow Hydroscope to have access to the full picture of the ship, and it’s environment, without which data analysis is only partial at best. The last tool allows the processing of this sizeable amount of data in order to extract the useful information for the sailors.
Each tool is essential to reduce the amount of “blur” and “uncertainty” which is often surrounds performance analysis. Combined in this way, these tools allow for a very fine analysis of the different factors affecting the yacht’s performance, making Hydroscope a uniquely accurate tool to process sailing data.