WINTER SCHOOL

PRACTICALS DESCRIPTION

DAY 2

Practical A: Vision-based Localization Using Fiducial Markers

T. Krajnik, J. Ulrich
Chronorobotics laboratory, Czech Technical University

In this practical we will learn to use a simple, but efficient vision-based localization system based on printers black and white markers. The system can detect, localize and track several fiducial markers in images captured by off the shelf cameras.

Requirements: PC/Laptop with Linux (Ubuntu), Basic skills C/C++ 

Practical B: Phytosensing – Using Plants as Sensors

T. Aust, E. Buss
Department of Computer and Information Science, Cyber Physical Systems, University of Konstanz

In the practical session, we will begin by providing a brief overview of our idea of utilizing plants as environmental sensors. Following that, we will present a selection of gathered plant physiological data from already conducted experiments. The participants will use this data to learn about data preprocessing, including tasks such as data cleaning and smoothing as well as feature extraction, selection and representation in the context of plant physiological signals. Further, the participants will learn about machine learning techniques, i.e., deep learning or statistical approaches for classifying time series, which they will apply to the preprocessed data to infer the environmental condition of the plant based on its physiological signals.

Requirements: Some basic experience in Python and programming

Practical C: Bio-hybrids in Water – Approaches and Methods
R. Thenius, W. Rajewicz, N. Helmer
Institute of Biology, Artificial Life Lab, University of Graz

In this practical different methods to detect substances in the environment will be presented, and methods to detect changes in the environment will be discussed. Further the participants have the ability to work with real-world data to learn how to evaluate behavioural and physiological changes in life forms, induced by changes in the environment.  

Requirements: Experience in Python 3, especially regarding handling of CSV-files. Experiences with Pandas or Python statistical packages are advantageous.

DAY 3

Practical D: Simple Bee Colony Temperature Measuring Process

V. Komasilovs, A. Kviesis
Faculty of Information Technologies, Latvia University of Life Sciences and  Technologies

The aim of this practical workshop is to demonstrate implementation of a simple bee colony temperature monitoring solution. Within the workshop the following topics will be discussed: overall architecture for end-to-end data handling, hardware components and assembly, peculiarities of embedded software, cloud software and its deployment specifics, data visualisation using Grafana.

Requirements: PCs/laptops with Linux. Basic knowledge of electronics and programming are beneficial. Examples will be in C/C++, Python and will cover the usage of Docker, MQTT

Practical E: Modelling Bio-hybrid Multi-level Complex Systems

M. Stefanec, D. Hofstadler, L. Fedotoff
Institute of Biology, Artificial Life Lab, University of Graz

In complex, biological, self-organising social systems, group or swarm effects occur at a higher system level through interactions at the microscopic level (interactions between individuals). These phenomena often lead to group effects, new properties emerge through the interactions. In this practical session, we will approach such complex biological systems from the modelling side, using a bottom-up approach to model a system that exhibits swarm intelligent properties.

Requirements: none

DAY 4

Practical F: Brain-Computer Interface – Controlling Virtual Reality with Brain Signals

S. Kober, L. Berger
Institute of Psychology, Neuropsychology & Neuroimaging, University of Graz

In this practical, we will record brain signals using the electroencephalogram (EEG) and use these signals to control virtual reality (VR) scenarios. Therefore, the recorded EEG signal will be processed in real-time, a virtual environment will be designed, and finally, the EEG signals and the virtual environment will be synchronised. The aim is to use the brain signals to control the VR.

Requirements: none

Practical G: Modelling and 3D Printing for Bio-hybrids
A. Ilgün
Institute of Biology, Artificial Life Lab, University of Graz

In the project HIVEOPOLIS, we put the emphasis on technological (software and hardware) and material design-led mechanisms to create closed feedback loops between honeybees and their immediate environment as well as the ecosystem at large. Many structural, mechanical, modular, thermal, biological, and environmental requirements must be met in order for a beehive design to support all technologies and an entire honeybee colony. We take advantage of the potentials of 3D printing in two key ways to compromise many competing criteria, such as durability and precision, with biologically compatible, and ideally 100% biologically resourced or grown materials: scaffolds made of porous, quickly produced parts and mechanically precise, durable parts. We will practise two types of 3D modelling techniques in this practical, which are geared toward 3D printing as a fabrication method. In an associative parametric modelling environment, we will base our design thinking on individually established -or in teams- biohybrid design scenarios, and produce finished prototypes that combine these two ends of material needs.
Objectives: 1. Create hybrid designs that are part human invention and part systemic living entities or use a living system to participate (guide you) in the design of something. Which functional criteria need more top down design methods and engineered materials? Which functional criteria can be fulfilled via using porous mycelium materials? 2. And in all cases, using hypothesis testing as a design method.

Requirements: none