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AquaIntellect: A Semantic Self-learning Framework for Underwater Internet of Things Connectivity
The emerging paradigm of Non-Conventional Internet of Things (NC IoT), which is focused on the usefulness of information as opposed to the notion of high volume data collection and transmission, will be an important and dominant part of human life in the near future.
AdaptNet: Rethinking Sensing and Communication for a Seamless Internet of Drones Experience
In the evolving era of Unmanned Aerial Vehicles (UAVs), the emphasis has moved from mere data collection to strategically obtaining timely and relevant data within the Internet of Drones (IoDs) ecosystem.
Source Feature Compression for Object Classification in Vision-Based Underwater Robotics
New efficient source feature compression solutions are proposed based on a two-stage Walsh-Hadamard Transform (WHT) for Convolutional Neural Network (CNN)-based object classification in underwater robotics.
Location-aware Beamforming for MIMO-enabled UAV Communications: An Unknown Input Observer Approach
Numerous communications and networking challenges prevent deploying unmanned aerial vehicles (UAVs) in extreme environments where the existing wireless technologies are mainly ground-focused; and, as a consequence, the air-to-air channel for UAVs is not fully covered.
