RFID-Enabled Autonomous Logistics Management (REALM)
The project seeks to use RFID and complex event process to track instruments and objects in International Space Station (ISS).
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The project seeks to use RFID and complex event process to track instruments and objects in International Space Station (ISS).
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Anonymous energy data comprising energy usage, solar generation, and local weather is often released in the public domain to aid sustainability research. However, such anonymous data may leak information such as the location of the consumer. In this project, we are designing techniques to mitigate localization attacks on such data.
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The project develops a solar electric vehicle charging station for electric vehicles and the design of intelligent charging algorithms that maximize the use of renewables.
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The project seeks to develop smart glasses that can perform real-time gaze tracking and eye monitoring for safety and medical applications such as fatigue detection.
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The project involves developing energy and grid optimization techniques to integrate energy storage with renewable sources in the grid.
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The project uses machine learning and optimization approaches to analyze energy data at city-scale. Moreover, it involves the development of smart applications that provide energy-efficiency recommendations to buildings.
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