Open Access

The FIVIS simulator system addresses the classical visual and acoustical cues as well as vestibular and further physiological cues. Sensory feedback from skin, muscles, and joints are integrated within this virtual reality visualization environment. By doing this it allows for simulating otherwise dangerous traffic situations in a controlled laboratory environment. The system has been successfully applied for road safety education applications of school children. In further research studies it is applied to perform multimedia perception experiments. It has been shown, that visual cues dominate by far the perception of visual depth in the majority of applications but the quality of depth perception might depend on the availability of other sensory information. This however, needs to be investigated in more detail in the future.

This paper presents the newly founded Institute of Visual Computing at the Bonn-Rhine-Sieg University of Applied Sciences in Sankt Augustin, Germany. The research focuses as well as an overview of current projects are going to be part of this presentation.

In this paper, we introduce an optical sensor system, which is integrated into an industrial push-button. The sensor allows to classify the type of material that is in contact with the button when pressed into different material categories on the basis of the material's so called "spectral signature". An approach for a safety sensor system at circular table saws on the same base has been introduced previously on SIAS-2007. This contactless working sensor is able to distinguish reliably between skin, textiles, leather and various other kinds of materials. A typical application for this intelligent push-button is the use at possibly dangerous machines, whose operating instructions include either the prohibition or the obligation to wear gloves during the work at the machine. An exemple of machines at which no gloves are allowed are pillar drilling machines, because of the risk of getting caught in the drill chuck and being turned in by the machine. In many cases this causes very serious hand injuries. Depending on the application needs, the sensor system integrated into the push-button can be configured flexibly by software to prevent the operator from accidentally starting a machine with or without gloves, which can decrease the risk of severe accidents significantly. Especially two-hand controls are incentive to manipulation for easier handling. By equipping both push-buttons of a two-hand control with material classification properties, the user is forced to operate the controls with his bare fingers. That limitation disallows the manipulation of a two-hand control by a simple rodding device.

The device (10) has a handrail (18) provided with an optical contactless monitoring device formed as an active sensor system, where the monitoring device is arranged in a region of a guide (14) of the handrail at a front base (16) of an escalator (12) or a moving pavement. The monitoring device has two transmission paths (28, 30) with wavelength bands that are different from each other, where one of the paths includes the handrail. Ratio or difference between signals of the paths is used for recognizing foreign bodies e.g. hands of adults and children.

In the presented project, a new approach for the prevention of hand movements leading to hazards and for non-contact detection of fingers is intended to permit comprehensive and economical protection on circular saws. The basic principles may also be applied to other machines with manual loading and / or unloading. With an automatic blade guard an improved integration of the protection system can be achieved. In addition a new detection principle is explained. The distinction between skin and wood or other material is achieved by a dedicated spectral analysis in the near infrared region. Using LED and photodiodes it is possible to detect fingers and hands reliably. With a kind of light curtain the intrusion of hands or fingers into the dangerous zone near the blade guard can be prevented.

This work addresses the problem of measuring psychological strain in humans by the use of physiological data. The aim of the work is the research, development and evaluation of a measurement system for the acquisition of such data from humans and the differentiation of psychological and physical strain with the help of machine learning algorithms. The developed system records and analyzes the ECG, the EMG, as well as the skin conductance, and combines these physiological parameters with the subject’s physical activity. The main purpose of this measurement system is to assess both types of strain in employees at their workplaces.

Die Steuerung sicherheitsrelevanter Funktionen von Maschinen wird heute vermehrt durch Software vorgenommen. Bei der Entwicklung und Prüfung sicherheitsrelevanter Software werden nach IEC 61508-3 zahlreiche Verfahren eingesetzt, um Fehler bei der Programmierung zu vermeiden. Die statische Analyse von Software ist dabei ein beliebtes Werkzeug, um Schwachstellen frühzeitig zu erkennen bzw. komplexe Algorithmen zu identifizieren, damit sie ausgiebigen Tests unterzogen werden können. Gemeinsam mit dem Fachbereich Informatik der Fachhochschule Bonn/Rhein-Sieg wurde ein Werkzeug entwickelt, mit dem die Qualität von SPS Software überprüft werden kann. Das Werkzeug steht kostenlos im Internet zum Download zur Verfügung. Der Beitrag beschreibt, wie die Qualität gemessen wird und worauf bei der Benutzung des Werkzeuges zu achten ist.