Paper accepted at CIKM 2022

Our paper on supporting sensor-based smart space analytical applications has been accepted at CIKM 2022.

Sentaur: Sensor Observable Data Model for Smart Spaces

Peeyush Gupta, Sharad Mehrotra (University of California, Irvine); Shantanu Sharma (New Jersey Institute of Technology); Roberto Yus (University of Maryland, Baltimore County); and Nalini Venkatasubramanian (University of California, Irvine)

This paper presents Sentaur, a middleware designed, built, and deployed to support sensor-based smart space analytical applications. Sentaur supports a powerful data model that decouples semantic data (about the application domain) from sensor data (using which the semantic data is derived). By supporting mechanisms to map/translate data, concepts, and queries between the two levels, Sentaur relieves application developers from having to know or reason about either capabilities of sensors or write sensor specific code. This paper describes Sentaur data model, its translation strategy, and highlights its benefits through real-world case studies.