This paper explores the data cleaning challenges that arise in using WiFi connectivity data to locate users to semantic indoor locations such as buildings, regions, rooms. WiFi connectivity data consists of sporadic connections between devices and …
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 …
This paper describes the collaborative effort between privacy and security researchers at nine different institutions along with researchers at the Naval Information Warfare Center to deploy, test, and demonstrate privacy-preserving technologies in …
This paper proposes SmartBench, a benchmark focusing on queries resulting from (near) real-time applications and longer-term analysis of IoT data. SmartBench, derived from a deployed smart building monitoring system, is comprised of: 1) An extensible …
This paper describes a middleware framework for IoT smart spaces, SemIoTic, that provides application developers and end-users with the semantic domain-relevant view of the smart space, hiding the complexity of having to deal with/understand …
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 …
Internet of Thing (IoT) systems, such as smart buildings and smart cities, provide services to users (individuals and organizations) in various aspect of our lives. To provide such services, IoT systems need to handle data captured from multiple …
Current buildings rely on predefined rules to control the temperature in rooms disregarding their residents’ thermal comfort. Multiple approaches have been presented in the literature to tackle this issue (e.g., by enabling occupants to express their …