Olga Saukh

Assistant Professor at TU Graz, Institute for Technical Informatics
Scientist at Complexity Science Hub Vienna

Research Projects

This page lists research projects I was working on during my Ph.D. and postdoc years.

OpenSense: Open Sensor Network for Air Quality Monitoring

Duration: 2010-2013

OpenSense is a research project dedicated to monitoring air quality in urban areas with mobile wireless sensor nodes to better understand spatial variation of main air pollutants in cities. Several groups from ETH Zurich and EPF Lausanne are involved in the project. Our group at ETH Zurich successfully operates a network of ten OpenSense stations installed on top of VBZ trams in Zurich. Please visit the OpenSense Zurich project page for more details on our activities in the project. The project is funded by Nano-Tera.ch.

There are many research challenges directly and indirectly related to setting up and operating a network of low-cost sensors on top of trams. For example, how to select a set of trams for installing the stations, to quantify the impact of mobility on sensor measurements and how to do the sensor calibration in the mobile setting.

OpenSense II: Crowdsourcing High-Resolution Air Quality Sensing

Duration: 2014-2016

In OpenSense II we will leverage the results of the previous Nano-Tera.ch project OpenSense, particularly on: mobile monitoring of air pollution, sensor and communication platforms, calibration methods, sensor data gathering and visualization, statistical modeling, activity recognition, and personalized health recommendations. By adding the dimension of crowdsourcing and human-centric computation we will study possibilities to incentivize users to make available states based on physical measurements, such as location, motion and pollution, through their mobile personal devices or monitoring assets that they can install in their homes or on their cars.

inUse: Increasing Usability of Sensor Generated Data

Duration: 2013-2014, I was a co-PI in this project

In order to make sensor data useful, despite the lack of expert supervision in the loop, context annotations, analysis and modeling become key components in setting up sensor data-based applications: only if sensors and sensor data are annotated and enriched by information describing their meanings, quality, validity scope, measurement procedure, and connections with closely correlated data, they can be understood and used by the general public. The kind of useful context ranges from sensor and measurement descriptions (time, location, sensor type, validity, time of last calibration, measurement quality, etc.) to advanced context derived by aggregating, combining, analyzing, and enriching raw data, e.g., in the form of analytical models, annotations, and correlations.

inUse demonstrates the usability of air pollution data currently being gathered by the OpenSense network in Zurich. This data is used to calculate pollution maps with a higher temporal and spatial resolution than available from state-of-the-art maps based on the data from conventional measurement stations.

AWARE: Autonomous Operation of Wireless Sensor-Actuator Networks

I was lucky to take part in the execution of AWARE project as a Ph.D. student at the University of Bonn, Germany. The goal was to design, develop and experiment with a platform providing the middleware and the functionalities required for the cooperation among aerial flying objects, i.e. autonomous helicopters, and a ground sensor-actuator wireless network, including mobile nodes carried by people and vehicles. The platform enables the operation in sites with difficult access and without communication infrastructure. In order to verify the success in reaching the objectives, the project considers the validation in two different applications: civil security / disaster management and filming dynamically evolving scenes with mobile objects. Three general experiments in a common scenario have been conducted in order to integrate the system and test the functionalities required for the above validations.

Structural Health Monitoring with Wireless Sensor Networks

During my Ph.D. and shortly after I was working on a couple of projects dedicated to structural health monitoring with WSN technology. In civil engineering practice, monitoring of civil structures had always been done with conventional wired systems. These mature systems combine high-fidelity sensor values with a reliable and robust system performance. However, the installation, primarily the cabling, is very time-consuming and expensive. Many application scenarios benefit from using wireless sensor networks due to their attractive properties of being cable-free and easy to deploy, which allows minimizing installation cost and time. Although WSN technology allows considerable cost reduction, actual deployments of wireless systems are still very limited due to numerous challenges that need to be solved: handling reliably high sampling rates and large data volumes, assuring system reliability, and achieving an acceptable system lifetime. Moreover, WSNs still need to offer enough transparency for civil engineers to concentrate on assessing the state of the structure by easily tuning acquisition parameters and reconfiguring parts of the measurement system.