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BL(u)E CRAB: A User-Centric Framework for Identifying Suspicious Bluetooth Trackers

Given the pervasiveness of Bluetooth Low Energy (BLE)-based devices, detecting unwanted or suspicious trackers is challenging, especially due to their heterogeneity, cross-platform compatibility issues, and inconsistent detection methods. BL(u)E CRAB …

LOADS: LiDAR-based Privacy-Preserving Queue Monitoring and Analysis

Long queues in retail and public environments can frustrate customers and negatively impact user experiences. Traditional camera-based monitoring systems are effective in analyzing queues, however, the potential for identification raises privacy …

A Privacy-Enabled Platform for COVID-19 Applications

We present our experiences in adapting and deploying TIPPERS, a novel privacy-enabled IoT data collection and management system for smart spaces, to facilitate the monitoring of adherence to COVID-19 regulations in a university campus and a military …

SemIoTic: Bridging the Semantic Gap in IoT Spaces

This demonstration showcases the SemIoTic middleware which provides inhabitants of an IoT space, as well as developers of applications, with a semantic view of the space. Participants will have an opportunity to see how useful IoT applications can be …