Data Management

DEMSA: a DT-enabled Middleware for Self-adaptive Smart Spaces

Heating, Ventilation, and Air Conditioning (HVAC) systems account for a significant portion of energy consumption within buildings. In order to balance the effect of thermal comfort vis-a-vis energy savings, HVAC control strategies have been …

SmartSPEC: A framework to generate customizable, semantics-based smart space datasets

This paper presents SmartSPEC, an approach to generate customizable synthetic smart space datasets using sensorized spaces in which people and events are embedded. Smart space datasets are critical to design, deploy and evaluate systems and …

Sentaur: Sensor Observable Data Model for Smart Spaces

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 …

SmartSpec

SmartSPEC is a smart space simulator and data generator that creates customizable smart space datasets using semantic models of spaces, people, events and sensors. We employ ML-based approaches to characterize and learn attributes of the embedded people and events in a sensorized space and apply an event-driven simulation strategy to generate realistic simulated data about the space (events, trajectories, sensor datasets, etc.). The SmartSPEC architecture consists of two main components:

SmartSPEC: Customizable Smart Space Datasets via Event-Driven Simulations

This paper presents SmartSPEC, an approach to generate customizable smart space datasets with information about sensorized spaces in which people and events are em- bedded. Smart space datasets are critical to design, deploy and evaluate robust …

JENNER: Just-in-time Enrichment in Query Processing

Emerging domains, such as sensor-driven smart spaces and social media analytics, require incoming data to be enriched prior to its use. Enrichment often consists of machine learning (ML) functions that are too expensive/infeasible to execute at …

LOCATER: Cleaning WiFi Connectivity Datasets for Semantic Localization

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 …

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 …

Transitioning from testbeds to ships: an experience study in deploying the TIPPERS Internet of Things platform to the US Navy

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 …

Sieve: A Middleware Approach to Scalable Access Control for Database Management Systems

Current approaches for enforcing Fine Grained Access Control (FGAC) in DBMS do not scale to scenarios when the number of access control policies are in the order of thousands. This paper identifies such a use case in the context of emerging smart …