Program (updated!)

Friday, March 17  9:45 - 10:00

S0: Welcome and Introduction

Chairs: Pascal Hirmer (University of Stuttgart, Germany), Jadwiga Indulska (The University of Queensland, Australia), Gabriele Civitarese (University of Milan, Italy)

Friday, March 17 10:00 - 10:30

Paper Session 1: Human Activity Recognition

Chair: Gabriele Civitarese (University of Milan, Italy)

Bonpagna Kann; Sandra Castellanos; Philippe Lalanda: Evaluation of Regularization-based Algorithms in Human Activity Recognition

Friday, March 17 11:00 - 12:00

Paper Session 2: Data Cleaning in Context-Aware Systems

Chair: Gabriele Civitarese (University of Milan, Italy)

Aboubakr Benabbas; Marco Grawunder; Daniela Nicklas: Context-aware Outlier Detection for Sensor Data Stream Processing  

Daniel Del Gaudio; Tim Schubert; Mohamed Abdelaal : RTClean: Context-aware Tabular Data Cleaning using Real-time OFDs 

Friday, March 17  12:00 - 13:00

Keynote: Computational Behavior Analysis -- Pushing the Boundaries towards usable Digital Health

Chair: Pascal Hirmer (University of Stuttgart, Germany)

Thomas Plötz (Georgia Institute of Technology, USA)

We live in an era in which the number of smart devices is now greater than the number of humans living on Earth. Such smart devices include smartphones and wearables but also the myriad of IoT devices that are integrated into the very built environment we live in. As such, the field of mobile and ubiquitous computing is transforming many-if not all-areas of our lives. This overall transformation has great potential for many application areas. Most prominently, it is now possible to continuously and unobtrusively record rich behavior data that can inform objective health assessments thereby serving as basis for improved care and treatment, and thus well-being. The basis for effective health assessments are robust and reliable methods for human activity recognition - more generally referred to as sensor-based Computational Behavior Analysis (CBA). From a technical perspective, the analysis task translates into a time-series assessment problem, yet with a number of domain-specific constraints and requirements. In response to challenges such as noisy sensor data, ambiguous ground truth annotation, and typically limited size sample datasets CBA researchers have developed and validated sensor data analysis and machine learning methods that focus on these domain specifics and thus enable effective operation. In this talk, I will give an overview of where the broader field of Computational Behavior Analysis is today before I focus on current and next frontiers specifically related to smart sensor data analysis. I will illustrate how the constraints and requirements of real-world application scenarios force pushing boundaries of core sensor data analysis research as well as real-world deployments.

Friday, March 17  14:00 - 15:30

Paper Session 2: Data management in Context-Aware Systems

Chair: Daniel Del Gaudio (University of Stuttgart, Germany)

Satoshi Yoshimura; Hirohiko Suwa; Teruhiro Mizumoto : Mobile Health System using Facial Image for Assessment of Work Engagement, Recovery and Reattachment

Kanaka Sai Jagarlamudi; Arkady Zaslavsky; Seng W Loke; Kevin Lee: Validating Quality of Context in Pervasive Computing Systems: Surf Life Saving Use Case

Yunxuan Li; Pascal Hirmer; Christoph Stach: CV-Priv: Towards a Context Model for Privacy Policy Creation for Connected Vehicles

Friday, March 17 15:30 - 15:45

S5: Discussion, Feedback and Farewell