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Abstract Exploration and exploitation of deep space and the deep oceans has powered much technological progress. With their extreme operating environments, these two remote and hostile domains have posed many challenges and has produced many solutions. The study of each of these extreme environments has significantly enhanced our understanding of the other, and the technologies that enable prospecting and extracting resources in one environment can often be adapted for use in the other. For both deep space and deep ocean, there is much to be learned from other sectors such as the medical industry as well. For example, medical imaging technologies such as magnetic resonance imaging and computed tomography scans resemble the non-destructive testing techniques used in space and deepwater energy business. Similarly, robotic surgery is analogous to Mars Rovers and remotely operated vehicles used under water, and remote patient monitoring for more personalized and effective healthcare is comparable to the data analytics and machine learning used for proactive health monitoring in deep space and deep ocean. Digital transformation has been impacting all industries, and deep space and deep ocean are no exception. Digital transformation has three primary foundations: data-digital information; analytics-using the data to make better decisions, faster; and connectivity-data exchange between humans, machines, and devices. Various technologies enable and cut across these domains including sensors, cloud computing, edge analytics, automation and robotics, 3D printing, augmented reality, and artificial intelligence all underlain and enabled by accessible, affordable, and reliable energy. The objective of this paper is to explore the potential of such technologies at intersections between deep space and deep ocean. It will also document how the deep space and deep oceans hey have learned from each and have also leveraged advances in other sectors, principally medical and healthcare.
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Hosam Abu Zeid
Hani Elshahawi
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Zeid et al. (Mon,) studied this question.
synapsesocial.com/papers/68e6d1b2b6db64358764fc44 — DOI: https://doi.org/10.4043/35370-ms
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