Bedrock uses autonomous subsea vehicles and cloud-based data to revolutionize seabed mapping

Sep, 2021 - by CMI


The company wants to replace the traditional way of mapping the seafloor with a new, fast, and smart method to access the super-accurate seafloor images and host them to their website.


The demand for renewable energy has pushed offshore wind energy to the top of many energy companies' priority lists, which involves taking a careful look at the sea bed where it will be installed. Bedrock, on the other hand, brings that mapping process into the 21st century with its AUV and advanced cloud-based service for data. Bedrock offers clients high-resolution maps of the seabed, which are made available through Mosaic, a popular web service that handles all of the analytics and hosting for its customers.


Earlier, the data was gathered, interpreted, and stored on ships. They don’t have a good internet connection and were intended to conduct anything from coastal assessments to ocean bed surveys and the data gathered is useless as it is in raw format. It must be presented and contextualized, as the size of data is around 10 TB. The traditional cloud-based systems are not the best way to handle around 20,000 sonar files.


The AUV designed by Bedrock is flexible for operating it, yields better quality data, and is reliable for underwater surveys. It gives better detailed and precise images as it can use increased frequency near the sea bed without harming the marine animals. That is useless for a ship floating on the surface due to much of what it needs to map is deeper than 75 meters. However, there are several advantages to building a craft that stays within 50 meters of the bottom, and that is precisely what Bedrock's AUV is intended to achieve.


As there is a hurry to participate in the emerging wind energy business, the existing market is focused on precise, sea-shore data than deep-sea data. This implies that data gathered is readily transferred for storage and processing based on the cloud than the traditional way. As a result, data can be analyzed and delivered more quickly, just in time for demand to soar.