This completion opens the way for fully scalable Hivecell stack processing power to be used at locations onboard ship, resulting in significant bandwidth savings and improved response times for ‘smart’ shipowners and managers.
In a maritime industry awash with smart devices yet tied to centralised systems management, cloud storage is increasingly connecting the dots, with processing power ‘at the edge’ enabling only information relevant to decision-making to be uploaded. On top of reducing hardware and data traffic, edge computing saves on server maintenance and training, while integration is easier.
Hivecell delivers a plug and play ‘hive’ of smart cells, deployed on the ship in an ‘edge-as-service’ solution that requires no hardware investment. Crunching data in situ, the distinctive yellow cells pre-process relevant information for upload. Trials at Hivecell using the virtualised METIS Data Fusion Server (DFS) validated Hivecell edge-as-a-service as ready to work with existing METIS cloud-computing software.
“Following the trials, Hivecell can be offered as an integral part of the innovative artificial intelligence-based solutions METIS has developed to empower shipping’s digital transformation,” said METIS chief executive officer Mike Konstantinidis. “METIS and Hivecell are each innovators in their specialised domains, and each looks forward to identifying common opportunities to implement game-changing solutions that can accelerate maritime digitalisation.”
“There’s a lot of talk from companies who claim to be able to provide computing power at the edge, but a ship is certainly the true edge,” said Jeffrey Ricker, co-founder and CEO of Hivecell. “Our solution is programmed with existing hardware and is simple to deploy, enabling the fleet managers to process data from the METIS system more easily than ever before, which enables faster decision making.”
While non-exclusive, the agreement between METIS and Hivecell also opens the way for further development work focusing on improving system redundancy and deploying more machine-learning (ML) at the edge using open-source cloud computing, said Mr Konstantinidis.
“Both companies continue to work towards greater integration and interoperability, as part of a common commitment that we see as seamlessly providing additional value to shipping customers,” he said.