Sea Technology

JAN 2018

The industry's recognized authority for design, engineering and application of equipment and services in the global ocean community

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Page 35 of 52 January 2018 | ST 35 no longer have limitations. The combination of technolo- gy creates an immersive virtual reality (VR) environment with true 1:1 3D-scale models generated using repeat- able, millimetric data inputs. Now using a laptop, desk- top or smart device, geographically distributed teams can collaborate within a single VR session and be present in the same scene. The ability to explore and experience 3D content as if you were actually on site with a digi- tal representation of physical assets and the surrounding environment creates a seamless workflow environment from reality capture to virtual immersion. Actionable, in- sight-driven, preemptive data provides the "right" data delivered to the "right" stakeholder for greater impact. The future for ocean technology is now as compelling in its prospects as the ocean is deep. With initiatives such as the Nippon Foundation-GEBCO Seabed 2030 Project and the Shell Ocean Discovery XPRIZE pushing the fu- ture of ocean science and technology, this is indeed an exciting time for ocean exploration and utilization. Per- haps never before have we seen a more opportune mo- ment for collaboration between industry, the government and nonprofits. Together as we adopt these technologies we will create expanding business opportunities, stand up new industries and capture the public's imagination. Ultimately, the future ocean "enterprise" is collaborative, and to realize its potential we must seek to find that nex- us of business, scientific discovery and public interest. ST Review&Forecast Exploration and Discovery of Cuba's Deep Mesophotic Coral Reefs By John Reed Dr. Shirley Pomponi Dr. Dennis Hanisak Research Professors, Principal Investigators Cooperative Institute for Ocean Exploration, Research, and Technology, Harbor Branch Oceanographic Institute, Florida Atlantic University T he Cooperative Institute for Ocean Exploration, Re- search, and Technology (CIOERT) at Florida Atlan- tic University's Harbor Branch Oceanographic Institute (HBOI) recently led a joint scientific expedition with Cuban colleagues to map and characterize, for the first time, mesophotic coral ecosystems (MCEs) along the en- tire coastline of Cuba. MCEs are light-dependent ben- thic communities that occur in the "twilight zone" be- low shallow reefs and typically range from depths of 30 m to the bottom of the photic zone, which may extend to 150 m. Prior to this expedition, there was very little known about the extent and the health of Cuba's deep mesophotic reefs. After more than a year of planning, the 30-day research cruise circumnavigated Cuba and dis- covered deep coral reefs all along the shelf drop-off. Participants This project was jointly planned and in collaboration with organizations in Cuba and the U.S., including Cen- vances in material science and fabrication have provid- ed a new series of lighter, more flexible vehicle housing and hulls that can access greater depths without com- promising payload requirements. Less weight and more flexibility allow for the inherent cost of deployment to be reduced, and limitations on range, depth and power that were once the limiting factor are removed. With the addition of fly-way robotics and machine learning inte- grated into vehicle technology, a new form of workforce evolves. Depending on the applications, the new con- nectivity of ROVs, AUVs, ASVs and other robotics allows them to work alone or in tandem. Smart grids can be formed within the water column or along assets to moni- tor, inspect, repair and maintain them. New connectivity on the software side allows for vehicles to talk to each other, learn from each other and send messages to key resources. Using AI and robust algorithms, the power of these vehicles to connect transcends to the next level to a neural network. The ability to form smarts grids to map, collect and acquire information is an important devel- opment that will resonate with future applications like pipelines and other infrastructure inspections, biological monitoring and sampling, mapping, seismic monitoring, exploration, research and recovery, and so on. Artificial intelligence and machine learning incor- porate a wide range of digital capabilities that underpin many current subsea technologies. From data extraction and modeling to fabrication and engineering design, from ASV, AUV and robotic mechanics to marine trans- portation and shipping logistics, AI controls many of those activities. Machine learning is a subset of artifi- cial intelligence in which algorithms analyze data and, based on the knowledge garnered from those results, ad- just their logic on an ongoing basis to adapt to new and changing situations. Many of the recent advances in AI have originated from other sectors, university labs or the defense industry. AI's strength is built around organizing data from different sources, analyzing large-scale data sets to determine the interdependencies between data, with little or no human intervention. With the quest for actionable, preemptive data, tools that can mine it, shape it and then use it as the basis for decision making to opti- mize efficiencies are a clear choice in marine operations. Immersive collaboration powered by 3D data and AR/ VR technology is taking subsea, metocean, surface and atmospheric data to the next level. This emerging sector is fueled in part by two disparate technologies joined to- gether to create a virtual reality collaboration platform that enables geographically distributed individuals to explore and experience 3D content in real time. The growth of industrial and engineering AR and VR has been slow to infiltrate many marine operations for numerous reasons. Still considered a "nascent technology," many companies have been cautious on where and how to use it in applications, especially in the current risk- and cost- averse climate. In addition, the type and quality of 3D data inputs can be a real limiter. As subsea LiDAR, op- tical lasers, sensors and other data collection and moni- toring devices deliver more accurate, millimetric 3D data in an ASTM standardized e57 format, 3D data inputs

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