Keynote/Tutorial Speakers

Abstract:Environmental monitoring can be essentially described as a set of continuous or frequent measurements of environmental parameters which are fundamental to assess the state of the environment, the achievement of predefined objectives, law enforcement, the detection of new environmental issues, and environmental short and medium term forecasting. Monitoring at a micro-scale is related to monitor and track one or more parameters in a small and limited geographical context, such as the control of gaseous emissions of a factory. In terms of micro-scale, environmental monitoring is generally used to control emissions of pollutants, whether gaseous or liquid. By opposition, macro-scale monitoring involves a vast geographical area, such as the control of water quality of a lake.

For occasional measurement of environmental pertinent quantities, the natural solution is either to use dedicated, manually operated instruments if the measurement is to be made on site, or to take a sample of the media and make the measurements in an adequate laboratory. The last solution is sometimes required because of the difficulty of measuring on site namely chemical and biological quantities. For continuous environmental monitoring, automated measuring systems are needed.

After an introduction on environmental monitoring and how to approach air, water and soil monitoring, the presentation details a wireless sensor network designed to monitor the quality of the water of the Tagus River estuary near Lisbon, Portugal. This distributed automated measuring system is composed of several measuring sites (nodes of the network) each one installed on an anchored buoy. The hardware of each node includes, inside the buoy, sensors for temperature, pH, turbidity, electrical conductivity, dissolved oxygen, and heavy metals concentration and their conditioning circuits, a processing unit (microcontroller), a radio transceiver, a GPS, and a power supply. Sensors require periodic calibration. Thus, they are placed inside a tank where are introduced reference solutions for calibration purposes and samples of the river water for measurement using electronic controlled pumps and valves. On the outside of the buoy are the transceiver and GPS antennas and a solar panel used to recharge the batteries of the power supply. The hardware and the software of each node turn it into a smart sensor continuously operating and periodically sending data to a land-based central unit (a PC) that performs advanced data processing, data presentation and internet publication. The software of the central unit includes a Kohonen self-organized map based algorithm that allows identification of pollution events, one of the main purposes of the overall system.

Bio: Pedro Silva Girão (M’00–SM’01) is a Full Professor of the Department of Electrical Engineering, Instituto Superior Técnico, University of Lisbon, and a Senior Researcher, the Head of the Instrumentation and Measurements Group, and the Coordinator of the Basic Sciences and Enabling Technologies of the Instituto de Telecomunicações (IT). His main research interests include instrumentation, transducers, measurement techniques, and digital data processing, particularly for biomedical and environmental applications. Metrology, quality, and electromagnetic compatibility are also areas of regular activity.

Dr. Girão is a Senior Member of the IEEE, Distinguished Lecturer of IEEE/I&MS, and a regular reviewer of IEEE Trans. on Instrumentation and Measurement, Trans. On Biomedical Circuits and Systems, Sensors Journal, and Signal Processing Letters and member of the technical program committee of IEEE IMTC, SPICES, SSD, CIVEMSA, Sensors and MeMeA (co-chair in 2014) and maintains a strong relationship with IMEKO, being a member of the Advisory Board and Honorary Chair of TC-19.

Abstract: In a cyber-physical system (CPS) the computational and physical elements closely interact. In most cases, CPS are designed as a network of interacting elements with physical input and output instead of as standalone devices. This extension over legacy embedded systems allows a next round in distributed intelligence for a very broad range of applications, i.e. for intelligent systems and applications. Improved observability and controls through online condition monitoring don't only allow functions like predictive maintenance, but enable completely new servicification models. The presentation gives a short overview on the historical development of CPS, discusses selected applications in detail, shows possible solutions for today's problems, and envisages interesting R&D directions of tomorrow.

Bio: Prof. Dr.-Ing. Axel Sikora holds a diploma of Electrical Engineering (Dipl.-Ing./M.Sc.) and a diploma of Business Administration (Dipl. Wirt.-Ing., MBA), both from Aachen Technical University. He has done a Ph.D. in Electrical Engineering at the Fraunhofer Institute of Microelectronics Circuits and Systems, Duisburg, with a thesis on SOI-technologies. After various positions in the telecommunications and semiconductor industry, he became a professor at the Baden-Wuerttemberg Cooperative State University Loerrach in 1999. In 2011, he joined Offenburg University of Applied Sciences, where he leads the Institute of Reliable Embedded Systems and Communication Electronics (ivESK). Since b/o 2016, he is also deputy member of the board and head of the business unit "Software Solutions" at Hahn-Schickard Association of Applied Research (Germany). In 2002, he founded the Steinbeis Transfer Center Embedded Design and Networking, which was successfully spun off as STACKFORCE GmbH in 2014.

His major interest is in the system development of efficient, energy-aware, autonomous, secure, and value-added algorithms and protocols for wired and wireless embedded communication.

Dr. Sikora is author, co-author, editor and co-editor of several textbooks and more than one hundred papers in the field of embedded design and wireless and wired networking. Amongst many other duties, he serves as member of the Steering Board of Embedded World Conference.

Abstract: This talk presents some of the recent approaches for image classification and segmentation. Segmentation tasks are very challenging especially in the medical imaging context. The recent advances in feature extraction and classification makes some of the challenging problems tractable. First a brief overview of some of the recent feature extraction techniques is presented. This is followed by insights into Random Forest classifier. Finally a interactive training application ‘ilastik’ is explained. ilastik provides real-time feedback of the current classifier predictions and thus allows for targeted training and overall reduced labeling time. In addition, an uncertainty measure can guide the user to ambiguous regions of the data. Once the classifier has been trained on a representative subset of the data, it can be exported and used to automatically process a very large number of images.

Bio: Dr. Kumar Rajamani is Architect at Robert Bosch Engineering and Business Solutions. Prior to joining Bosch he spent three years at GE Global Research (GRC), with the Medical Image Analysis lab. He was primarily involved in quantitative imaging of cancer. Earlier to GE, Kumar was Senior Scientist at Philips Research and Head of IT-Department at Amrita University. His research focus includes Medical Image Analysis, Health care technologies for emerging markets. He has seven patents filings. Kumar completed his Ph.D. in Biomedical Engineering from University of Bern, Switzerland.