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In 1620, the Mayflower embarked on an uncertain journey across the Atlantic Ocean, with more than 100 pilgrims on board hoping to begin a new life in the New World. Now, 400 years later, The Mayflower Autonomous Ship (MAS) will follow in the footsteps of the original ship from Plymouth, England to Plymouth, Massachusetts. Only this time, there will be no human captain or onboard crew. It will be one of the first full-sized, fully-autonomous and unmanned vessels to cross the Atlantic Ocean.
A new generation of autonomous ships
The MAS project is a global collaboration led by marine research organization Promare. Conceived as a way to commemorate the 400th anniversary of the Mayflower voyage, it could have long-lasting implications for the shipping industry and the future of oceanographic research.
The autonomous shipping market is projected to grow from $90BN today to over $130BN by 2030. However; many of today's autonomous ships are just automated and do not dynamically adapt to new situations. Using an integrated set of IBM's AI, cloud, and edge technologies, ProMare is aiming to give the Mayflower the ability to operate independently in some of the most challenging circumstances on the planet.
Crossing the Atlantic safely with Red Hat Enterprise Linux
The Mayflower will be under the command of an AI Captain: a number of interlinked cognitive systems that enable it to sense, think and act at sea.
The Mayflower’s AI Captain uses onboard cameras to gather visual input and identify potential hazards such as other vessels or debris floating in the water. The ship’s vision system is being developed and trained using deep learning models on shore, running on IBM Power systems powered by Red Hat Enterprise Linux (RHEL), the industry’s leading enterprise Linux platform.
Onboard, two of the systems, Autonomy Manager and Safety Manager, also run on RHEL. The AI Captain Autonomy Manager makes decisions and provides recommended actions based on long term goals.
The Safety Manager monitors these decisions and validates them as ‘safe’ in the immediate area. This includes, for example, steering clear of localized hazards that could cause damage to the Mayflower. In order to provide safe operation the Safety Manager may take appropriate action such as assuming control over the ship’s steering and propulsion, activating emergency equipment or restarting the system.
Running on Red Hat Enterprise Linux locally, the edge computing system is designed to support mission-critical workloads. The Mayflower will not have access to high-bandwidth connectivity throughout its voyage. Edge devices will collect and analyze ship data and store it locally. When connectivity is available, it will be uploaded to edge nodes located onshore and sync with IBM Cloud. The team will also be able to push updates of the AI Captain's training model.
RHEL is well suited for this application because of its multi-, hybrid cloud capabilities, giving developers the ability to move applications from on-premises systems to the cloud, to the edge of computer networks (such as the Mayflower Autonomous Ship) and back. RHEL also provides the required levels of reliability for a mission which cannot afford any system failures in the middle of the ocean.
The vessel will carry three research pods containing an array of sensors and scientific instrumentation that scientists will use to advance understanding in a number of vital areas such as maritime cybersecurity, marine mammal monitoring, sea level mapping and ocean plastics.
Putting a research ship to sea can cost tens of thousands of dollars a day and is limited by how much time people can spend onboard – a prohibitive factor for many of today's marine scientific missions. It is hoped that the Mayflower Autonomous Ship will become a cost-effective and flexible platform for gathering data that will help safeguard the health of the ocean and the industries it supports.
About the author
Stefanie Chiras is Senior Vice President of Partner Ecosystem Success at Red Hat, leading Red Hat’s global partner ecosystem engagement, and plays a critical role in increasing the understanding of the value of Red Hat's product portfolio within the ecosystem, defining the strategy for partnering with Red Hat for customer success.