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to operate as a coherent network. This requirement can be theoretically fulfilled in a number of ways, including hardware approaches, e.g. the (wired or wireless) dissemination of the same clock signal
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authentication address digital risks, the physical interfaces of CPS (such as sensors and communication links) remain vulnerable and are often overlooked. A system cannot easily distinguish between genuine and
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decision-making. Examples include crowd management and large-scale communication networks based on cellular or wireless sensors. For instance, during mass gatherings such as the sport matches (e.g
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mortalities, economic loss, and human health risks through contaminated seafood. A low-cost, deployable sensor network based on mussels could provide real-time environmental intelligence, supporting regulatory
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impacts and suboptimal decision-making. Examples include crowd management and large-scale communication networks based on cellular or wireless sensors. For instance, during mass gatherings such as the sport
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: Wireless communications, signal processing, optimisation, machine learning, as well as programming and implementation skills Objectives: To design sensors and a data acquisition system for the experimental
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- Control of Communication networks - Markovian Processes - Network Based Localisation / Radio based connectivity - Adaptive bandwidth - Mesh networking - Wireless Sensor Networks - Edge Computing - Time
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wireless sensor networks as well as research and education within Life Science, smart electronic sensors and medical systems. The Department of Electrical Engineering is an international workplace with
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capable of leveraging signals from terrestrial base stations, non-terrestrial networks such as LEO satellite, and complementary on-board sensors. Specifically, it will: To design reconfigurable airborne
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with top Flemish universities to match our research domains: 6G and Wireless Internet of Things communication Automotive CMOS and beyond CMOS 3D system integration Advanced nano-interconnects Advanced