Open Access

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.

In this paper we present a new initiative to promote collaborative learning through industry partnered, interdisciplinary, student and user centred projects. This was achieved through the development of rehabilitation devices augmented with gamified software. Today development of software systems often requires people from different specialities who can work in multidisciplinary teams to achieve a common objective. A key challenge, therefore, is producing graduates with an understanding of a number of disparate skills across many discipline boundaries. Undergraduates may be knowledgeable in one specific discipline but will not be aware of the issues brought to bear by other relevant disciplines. In an effort to overcome this limitation, a cross-discipline course “Serious Games and Welfare Technology” was developed that allows students from different disciplines to work together to produce innovative, technology- supported health solutions. The course, an EU funded Erasmus+ initiative, was supported by a MOOC and enabled multi- disciplined and multinational teams to produce solutions for leading Health technology companies in the areas of rehabilitation and aging support. Following the first year of offering the course with a cohort of students from 5 countries, we report on the experiences and outcomes achieved from a number of viewpoints.

Microcontroller-based sensor systems offer great opportunities for the implementation of safety features for potentially dangerous machinery. However, in general they are difficult to assess with regard to their reliability and failure rate. This paper describes the safety assessment of hardware and software of a new and innovative sensor system. The hardware is assessed by standardized methods according to norm EN ISO 13849-1, while the use of model checking is presented as an approach to solve the problem of validating the software.

Safety applications require fast, precise and highly reliable sensors at low costs. This paper presents signal processing methods for an active multispectral optical point sensor instrumentation for which a first technical implementation exists. Due to the very demanding requirements for safeguarding equipment, these processing methods are targeted to run on a small embedded system with a guaranteed reaction time T < 2 ms and a sufficiently low failure rate according to applicable safety standards, e.g., ISO-13849. The proposed data processing concept includes a novel technique for distance-aided fusion of multispectral data in order to compensate for displacement-related alteration of the measured signal. The distance measuring is based on triangulation with precise results even for low-resolution detectors, thus strengthening the practical applicability. Furthermore, standard components, such as support vector machines (SVMs), are used for reliable material classification. All methods have been evaluated for variants of the underlying sensor principle. Therefore, the results of the evaluation are independent of any specific hardware.

At previous SIAS conferences, we presented a novel opto-electronic safety sensor system for skin detection at circular saws jointly developed with the Institute for Occupational Safety and Health of the German Social Accident Insurance (IFA). This work now presents the development results of our consecutive research on a prototype of a sensor system for more general production machine applications including robot workplaces. The system uses offthe shelf LEDs and photodiodes in combination with dedicated optics and a microcontroller system to implement a so-called spectral light curtain.

Recent studies point out that spoofing attacks using facial masks still are a severe problem for current biometric face recognition (FR) systems. As such systems are becoming more frequently used, for example, for automated border crossing or access control to critical infrastructure, advanced anti-spoofing techniques are necessary to counter these attacks. This work presents a novel, cross-modal approach that enhances existing solutions for face verification and uses multispectral short wave infrared (SWIR) imaging to ensure the authenticity of a face even in the presence of partial disguises and masks. It is evaluated on a dataset containing 137 subjects and a variety of spoofing attacks. Using a commercial FR system, it successfully rejects all attempts to counterfeit a foreign face with a false acceptance rate FARcf = 0% and most attempts to disguise the own identity with FARdg = 1% at a false rejection rate of FRR < 5% using SWIR images for verification.

Entering the work envelope of an industrial robot can lead to severe injury from collisions with moving parts of the system. Conventional safety mechanisms therefore mostly restrict access to the robot using physical barriers such as walls and fences or non-contact protective devices including light curtains and laser scanners. As none of these mechanisms applies to human-robot-collaboration (HRC), a concept in which human and machine complement one another by working hand in hand, there is a rising need for safe and reliable detection of human body parts amidst background clutter. For this application camera-based systems are typically well suited. Still, safety concerns remain, owing to possible detection failures caused by environmental occlusion, extraneous light or other adverse imaging conditions. While ultrasonic proximity sensing can provide physical diversity to the system, it does not yet allow to reliably distinguish relevant objects from background objects.This work investigates a new approach to detecting relevant objects and human body parts based on acoustic holography. The approach is experimentally validated using a low-cost application-specific ultrasonic sensor system created from micro-electromechanical systems (MEMS). The presented results show that this system far outperforms conventional proximity sensors in terms of lateral imaging resolution and thus allows for more intelligent muting processes without compromising the safety of people working close to the robot. Based upon this work, a next step could be the development of a multimodal sensor systems to safeguard workers who collaborate with robots using the described ultrasonic sensor system.

In the presented project, new approaches for the prevention of hand movements leading to hazards and for non-contact detection of fingers are 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. Two new detection principles are explained. The first is the distinction between skin and wood or other material by spectral analysis in the near infrared region. Using LED and photodiodes it is possible to detect fingers and hands reliable. With a kind of light curtain the intrusion into the dangerous zone near the blade can be prevented. The second principle is video image processing to detect persons, arms and fingers. In the first stage of development the detection of upper limb extremities within a defined hazard area by means of a computer based video image analysis is investigated.

Sicherheitsanforderungen an Transponder steigen mit zunehmendem Einsatz - in der Produktion, Logistik und Handel - insbesondere beim Endverbraucher bei der stationären und mobilen Nutzung. Standards und derzeit gebräuchliche Radio Frequency Identification (RFID-)Protokolle beinhalten bisher nur wenige Sicherheitsmechanismen und in proprietären Protokollen wird nur ein Teil davon genutzt. Insbesondere im Bereich der Low-Cost-Transponder werden nur einfache Sicherheitsfunktionen implementiert, die einen geringen Widerstandswert zu besitzen scheinen. Mit Verschlüsselungs-, Challenge-Response-Verfahren und digitalen Signaturen stehen allerdings Mechanismen zur Verfügung, mit denen ein hoher Widerstandswert erreicht werden kann. Diese Mechanismen werden jedoch bisher nur teilweise und bei hochpreisigen Transpondern verwendet. Hier werden einige zur Erreichung der Sachziele der Informationssicherheit bei RFID-Transpondern eingesetzte und einsetzbare Mechanismen dargestellt und hinsichtlich ihrer Anwendbarkeit und Angreifbarkeit bewertet. U.a. sind dies Back-Office-Verschlüsselung, Silent Tree Walking, Meta-IDs, Re-Encryption und distanzbasierte Zugriffskontrolle. Die Ergebnisse zeigen, dass Verfahren zur Erreichung eines mittleren bis hohen Sicherheitsniveaus (Widerstandswert gegen Angriffe) vorhanden sind. Im Beitrag wird je ein relevanter Mechanismus zur Erreichung der drei Sachziele der Informationssicherheit Verfügbarkeit, Vertraulichkeit und Pseudonymität bewertet: Verfügbarkeit: Widerstandswert gegen Strahlenbelastung bei medizinischen Anwendungen. Vertraulichkeit: Dazu wurde der Widerstandswert des Passwortschutzes von Transpondern mit Hilfe eines Brute-Force-Angriffs untersucht. Pseudonymität: Anwendbarkeit von Meta-ID-Verfahren.

Several hundred accidents involving the use of circular saws and resulting in injury, to hands or fingers occur each year in Germany. In the presented project, new approaches for the prevention of hand injuries and for the contactless detection of fingers are being investigated for comprehensive protection on circular saws. The basic principles can be applied to other machines with manual loading and/or unloading. This paper describes several principles to distinct human skin and wood and a safety guard that prevents touching the rotating blade. In a first approach a reliable protective device with functional diversity has been developed using a passive infrared sensor in combination with a capacitive field sensor. Second the distinction between skin and wood or other material is done by dedicated kind of spectral analysis in the near infrared region. With a kind of light curtain the intrusion into the dangerous zone near the blade can be prevented. The safety guard protects the operator’s hand within 50 ms. The forces of the protective system peak at no more than 120 N. We are presenting a complete strategy for such different tasks as cutting wedges, stopped cutting and hidden cutting, which have a very high odds ratio.

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.