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Marine pollution is a growing worldwide concern, affecting health of marine ecosystems, human health, climate change, and weather patterns. To reduce underwater pollution, it is critical to have access to accurate information about the extent of marine pollutants as otherwise appropriate countermeasures and cleaning measures cannot be chosen. Currently such information is difficult to acquire as existing monitoring solutions are highly laborious or costly, limited to specific pollutants, and have limited spatial and temporal resolution. In this article, we present a research vision of large-scale autonomous marine pollution monitoring that uses coordinated groups of autonomous underwater vehicles (AUV)s to monitor extent and characteristics of marine pollutants. We highlight key requirements and reference technologies to establish a research roadmap for realizing this vision. We also address the feasibility of our vision, carrying out controlled experiments that address classification of pollutants and collaborative underwater processing, two key research challenges for our vision.
We outline design and lines of development of autonomous tools for the computing Grid management, monitoring and optimization. The management is proposed to be based on the notion of utility. Grid optimization is considered to be application-oriented
6G technology targets to revolutionize the mobility industry by revamping the role of wireless connections. In this article, we draw out our vision on an intelligent, cooperative, and sustainable mobility environment of the future, discussing how 6G
Analyzing and controlling large distributed services under a wide range of conditions is difficult. Yet these capabilities are essential to a number of important development and operational tasks such as benchmarking, testing, and system management.
In numerical computations, precision of floating-point computations is a key factor to determine the performance (speed and energy-efficiency) as well as the reliability (accuracy and reproducibility). However, precision generally plays a contrary ro
With the wide bandwidths in millimeter wave (mmWave) frequency band that results in unprecedented accuracy, mmWave sensing has become vital for many applications, especially in autonomous vehicles (AVs). In addition, mmWave sensing has superior relia