Stefan Bosse

• PD Dr. rer. nat.
• Lecturer and Senior Researcher / Privatdozent (Assoc. Prof.) at University of Bremen

Data-driven models used for predictive classification and regression tasks are commonly computed using floating-point arithmetic and powerful computers. We address constraints in distributed sensor networks like the IoT, edge, and material-integrated computing, providing only low-resource embedded computers with sensor data that are acquired and pr...

In the field of Structural Health Monitoring (SHM) using Guided Ultrasonic Waves (GUW), machine learning (ML) approaches for data analysis are becoming increasingly popular. Especially, deep learning with artificial neural networks (ANN) has proven effective due to its ability to process a large amount of data. ANN are commonly employed in damage l...

Detecting and characterizing hidden damages in composite materials like Fibre-Metal Laminates (FML) remains a challenge. Guided Ultrasonic Waves (GUW) or X-ray imaging are commonly used to detect these damages, but their interpretation remains limited. Data-driven predictor models can detect damages in structures using GUW time-dependent signals, b...

Machine learning techniques such as deep learning have already been successfully applied in Structural Health Monitoring (SHM) for damage localization using Ultrasonic Guided Waves (UGW) at various temperatures. However, a common issue arises due to the time-consuming nature of collecting guided wave measurements at different temperatures, resultin...

This Issue of Engineering Proceedings assembles the papers presented at the 9th International Electronic Conference on Sensors and Applications (ECSA-9), held online on 1–15 November 2022, through the sciforum [...]

Agent-based modelling (ABM), simulation (ABS), and distributed computation (ABC) are established methods. The Internet and Web-based technologies are suitable carriers. This paper is a technical report with some tutorial aspects of the JavaScript Agent Machine (JAM) platform and the programming of agents with AgentJS, a subset of the widely used Ja...

Short-time and short-range device-to-device and device-to-service communication in ad-hoc mobile networks is a challenge. A prominent example of such a mobile device is the smartphone carried by users with a typical speed of 1m/s. Most Internet-of-Things (IoT) devices and smart sensors are connected via the Internet. Although, Internet access is wi...

Virtualization is the abstraction of details. Algorithms and programming languages provide abstraction, too. Virtualization of hardware and embedded systems is becoming more and more important in heterogeneous environments and networks, e.g., distributed and material-integrated sensor networks. Communication and data processing with a broad range o...

Dealing with distributed and parallel computing in strong heterogeneous environments, e.g., distributed sensor networks, is still a challenge at the algorithmic, communication, and application levels. Heterogeneity is related to different computer and network (communication) architectures. Virtualization can hide and unify heterogeneity. In additio...

Finding classified rectangular regions of interest (ROIs) in underwater images is still a challenge, and more so if the images pose low quality with respect to illumination conditions, sharpness, and noise. These ROIs can help humans find relevant regions in the image quickly or they can be used as input for automated structural health monitoring (...

In this Article, the targeted adjustment of the relative density of laser additive manufactured components made of AlSi10Mg is considered. The interest in demand-oriented process parameters is steadily increasing. Thus, shorter process times and lower unit costs can be achieved with decreasing component densities. Especially when hot isostatic pres...

In this paper, the temperature scaling approach (TS) for temperature compensation of guided ultrasonic waves (GUW) is presented. In many previous works, it could be observed that the amplitudes of the GUW change with temperature. In the TS approach, it is assumed that for each transducer configuration several functions \(M\left( f,T\right) \) exist...

Detection of hidden damages in Fibre Metal Laminates (FML) is a challenge. Damage detection, classification, and localization is a part of the lower levels of Structural Health Monitoring (SHM) and is critical for damage diagnosis. SHM is an extremely useful tool for ensuring integrity and safety, detecting the evolution. Early damage detection and...

Agent-based modelling (ABM), simulation (ABS), and distributed computation (ABC) are established methods. The Internet and Web-based technologies are suitable carriers. This paper is a technical report with some tutorial aspects of the JavaScript Agent Machine (JAM) platform and the programming of agents with AgentJS, a sub-set of the widely used J...

Due to the increasing use of the different composite materials in lightweight applications, such as in aerospace, it becomes crucial to understand the different damages occurring within them during life cycle and their possible inspection with different inspection techniques in different life cycle stages. A comprehensive classification of these da...

Most Internet-of-Things (IoT) devices and smart sensors are connected via the Internet using IP communication driectly accessed by a server that collect sensor information periodically or event-based. Although, Internet access is widely available, there are places that are not covered and WLAN and mobile cell communication requires a descent amount...

In this paper, a hybrid distributed-parallel cluster software framework for heterogeneous computer networks is introduced that supports simulation, data analysis, and machine learning (ML), using widely available JavaScript virtual machines (VM) and web browsers to accommodate the working load. This work addresses parallelism, primarily on a contro...

Most traffic flow control algorithms address switching cycle adaptation of traffic signals and lights. This work addresses traffic flow optimisation by self-organising micro-level control combining Reinforcement Learning and rule-based agents for action selection performing long-range navigation in urban environments. I.e., vehicles represented by...

This issue of Engineering Proceedings gathers the papers presented at the 8th International Electronic Conference on Sensors and Applications (ECSA-8), held online on 1–15 November 2021, through the sciforum.net platform developed by MDPI [...]

Manufacturing processes are increasingly adapted to multi-material part production to facilitate lightweight design via improvement of structural performance. The difficulty lies in determining the optimum spatial distribution of the individual materials. Multi-Phase Topology Optimization (MPTO) achieves this aim via iterative, linear-elastic Finit...

Augmented reality is well known for extending the real world by adding computer-generated perceptual information and overlaid sensory information. In contrast, simulation worlds are commonly closed and rely on artificial social behaviour and synthetic sensory information generated by the simulator program or using data collected off-line by surveys...

Structural health monitoring (SHM) is a promising technique for in-service inspection of technical structures in a broad field of applications in order to reduce maintenance efforts as well as the overall structural weight. SHM is basically an inverse problem deriving physical properties such as damages or material inhomogeneity (target features) f...

This issue of Engineering Proceedings gathers the papers presented at the 7th International Electronic Conference on Sensors and Applications (ECSA-7), held online on 15–30 November 2020 through the sciforum.net platform developed by MDPI.

Most traffic flow control algorithms address switching cycle adaptation of traffic signals and lights. This work addresses traffic flow optimisation by self-organising micro-level control combining Reinforcement Learning and rule-based agents for action selection performing long-range navigation in urban environments, i.e., vehicles represented by...

This issue of Proceedings gathers the papers presented at the 6th International Electronic [...]

Traffic flow optimisation is a distributed complex problem. Traditional traffic and logistics flow control algorithms operate on a system level and address mostly switching cycle adaptation of traffic signals and lights. This work addresses traffic flow optimisation by self-adaptive micro-level control by combining Reinforcement Learning and rule-b...

Common Structural Health Monitoring systems are used to detect past damages occurred in structures with sensor networks and external sensor data processing. The time of the damage creation event is commonly unknown. Numerical methods and Machine Learning are used to extract relevant damage information from sensor signals that is characterised by a...

Machine learning (ML) techniques are widely used in structural health monitoring (SHM) and non-destructive testing (NDT), but the learning process, the learned models, and the prediction consistency are poorly understood. This work investigates and compares a wide range of ML models and algorithms for the detection of hidden damage in materials mon...

Modelling and simulation of social interaction and networks are of high interest in multiple disciplines and fields of application ranging from fundamental social sciences to smart city management. Future smart city infrastructures and management are characterised by adaptive and self-organising control using real-world sensor data. In this work, h...

Recent trends like internet-of-things and internet-of-everything require new distributed computing and communication approaches as size of interconnected devices moves from a cm^3- to the sub-mm^3-scale. Technological advance behind size reduction will facilitate integration of networked computing on material rather than structural level, requiring...

This issue of Proceedings gathers the papers presented [...]

Der Entwurf und die Simulation komplexer mechatronischer und verteilter intelligenter Systeme erfordern eine einheitliche Systemmodellierungs-und Programmiersprache. Die-se Arbeit stellt JavaScript als eine vereinheitlichte Modellierungs-und Programmierspra-che vor, indem JavaScript mit einer semantischen Typsystem JST erweitert wird, um die Lücke...

Ubiquitous computing and The Internet-of-Things (IoT) grow rapidly in today's life and evolving to Self-organizing systems (SoS). A unified and scalable information processing and communication methodology is required. In this work, mobile agents are used to merge the IoT with Mobile and Cloud environments seamless. A portable and scalable Agent Pr...

Augmented reality is well known for extending the real world by adding computer-generated perceptual information and overlaid sensory information. In contrast, simulation worlds are commonly closed and rely on artificial sensory information generated by the simulator program or using data collected off-line. In this work, a new simulation paradigm...

Energy distribution as a main part of energy management in self-powered micro-scale networks like sensor net- works is a challenge with the goal to satisfy a safe and reliable operational state on system and node level. Under the assumption that nodes are arranged in mesh-like networks with links posing the capability to transfer energy between nod...

Tragende Strukturen werden typischerweise in Bezug auf relevante Lastfälle entworfen, wobei statische Formen und vorgegebene Materialeigenschaften angenommen werden, die während des Entwurfs und der Materialauswahl ausgewählt werden. Neue Technologien, die das Design von Strukturen ermöglichen, die lokale Eigenschaften im Betrieb als Reaktion auf L...

Abstract: Data mining, especially as applied to social science data, is a rapidly changing and emerging field. Data mining (DM) is the name given to a variety of computer-intensive techniques for discovering structure and for analyzing patterns in data. Using those patterns, DM can create predictive models, or classify things, or identify different...

Monitoring of mechanical structures is a Big Data challenge concerning Structural Health Monitoring and Non-destructive Testing. The sensor data produced by common measuring techniques, e.g., guided wave propagation analysis, is characterized by a high dimensionality in the temporal domain, and moreover in the spatial domain using 2D scanning. The...

Monitoring of mechanical structures is a Big Data challenge concerning Structural Health Monitoring and Non-destructive Testing. The sensor data produced by common measuring techniques, e.g., guided wave propagation analysis, is characterized by a high dimensionality in the temporal domain, and moreover in the spatial domain using 2D scanning. The...

Materials Informatics addresses commonly the design of new materials using advanced algorithms and methods from computer science like Machine Learning and Data Mining. Ongoing miniaturization of computers down to the micro-scale-level enables the integration of computing in structures and materials that can be understand as Materials Informatics fr...

Materials Informatics addresses commonly the design of new materials using advanced algorithms and methods from computer science like Machine Learning and Data Mining. Ongoing miniaturization of computers down to the micro-scale-level enables the integration of computing in structures and materials that can be understand as Materials In-formatics f...

This book represents my Habilitation Thesis and addresses the challenges of unified and distributed computing in strong heterogeneous environments ranging from Sensor Networks to Internet Clouds by using Mobile Multi-Agent Systems. A unified agent behaviour model, agent processing platform architecture, and synthesis framework should close the oper...

This issue of Proceedings gathers the papers presented at the 4th International Electronic Conference on Sensors and Applications (ECSA-4), held online on 15–30 November 2017 through the sciforum.net platform developed by MDPI. The annual ECSA conference was initiated in 2014 on an online basis only, to allow the participation from all over the wor...

This introduction presents an overview of the key concepts discussed in this book. The book suggests that the implementation of material-integrated sensing can either follow a top-down or a bottom-up approach. Basing a product on material-integrated intelligent systems leads to increased complexity in product development. The book discusses the des...

This chapter considers parameter identification problems and discusses several deterministic techniques for the extraction of information on searched-for parameters from sensor data. These techniques will rely on some physical model for the data acquisition process. It will also rely on deterministic mathematical algorithms to stably compute search...

The mobile agent represents a mobile computational process that can migrate in networks, for example, the Internet domain, as well as in sensor networks. Multiagent systems (MASs) represent self-organizing societies consisting of individuals following local and global tasks and goals including the coordination of information exchange in the design...

Cloud computing is a new computation paradigm used to process a large amount of data, commonly in a distributed environment. Cloud-based computing was primarily used in business processes and consumer-producer scenarios offering distributed databases and services. In the meantime, a cloud can be any decentralized computing architecture, recently ex...

This chapter outlines the principles of different components of a sensor node and the challenges to integrate sensor nodes in materials and mechanical structures. The front end of the data acquisition system amplifies and filters the signal of the sensor node. An amplifier and filter are crucial components in the initial signal processing. In data...

Communication is a central part of distributed data processing in sensor networks, influencing performance and operation significantly. A communication network is basically represented with a network connectivity graph (NCG) with nodes (computers, subnetworks, mobile devices, sensors) and edges connecting the nodes, representing the technical commu...

Sensor fusion (also known as multisensor data fusion) is a well-known technique to increase the robustness and confidence of a sensor signal processing system by using multiple sensor outputs to improve a decision-making process. The fusion process can be classified in different levels namely raw sensor-level fusion before any preprocessing, featur...

An advantage of machine learning (ML) compared with numerical algorithms is the ability to handle problems with a nonpolynomial (NP) complexity class, that is, an exponential increase of computation time with respect to the data size. A practically oriented classification of ML schemes suitable for information extraction in sensor networks and supp...

The deployment of embedded systems for sensor data processing can be found in the following areas: structural monitoring and control, structural health monitoring, load monitoring, adaptive and morphing structures, and tactile sensing. The raw sensor output of a structural monitoring or tactile sensing system reflects the lowest level of informatio...

Energy-aware systems address the minimization of the energy consumption and the energy management optimizing the usage of limited energy resources to safekeeping the system vividness, which present different strategies. The first major area focuses on the design of low-power systems reducing the power consumption of electronic devices; the second a...

Monitoring of mechanical structures is a Big Data challenge and includes Structural Health Monitoring (SHM) and Non-destructive Testing (NDT). The sensor data produced by common measuring techniques, e.g., guided wave propagation analysis, is characterized by a high dimensionality in the temporal and spatial domain. There are off- and on-line metho...

Ubiquitous computing and The Internet-of-Things (IoT) grow rapidly in today's life and evolving to Self-organizing systems (SoS). A unified and scalable information processing and communication methodology is required. In this work, mobile agents are used to merge the IoT with Mobile and Cloud environments seamless. A portable and scalable Agent Pr...

In the past decades there was an exponential growth of computer networks and computing devices, connecting computers with a size in the m3 range. The Internet-of-Things (IoT) emerges connecting everything, demanding for new distributed computing and communication approaches. Currently, the IoT connects devices with a size in the cm3 range. But new...

Materials Informatics; starting another view. The Scaling Issue must be addressed if computation is shift within materials. Scaling of algorithms and architectures towards the design of distributed material-integrated embedded systems is required! Connecting Physical and Logical Worlds: Sensorial and Adaptive Materials are examples for Distributed...

Smart mobile devices are fundamental date sources for crowd activity tracing. Large-scale mobile networks and the Internet-of-Things (IoT) expand and become part of pervasive and ubiquitous computing offering distributed and transparent services. With the IoT, Crowd Sensing is extended by Things Sensing, creating heterogeneous smart environments. A...

Among the Internet-of-Things, one major field of application deploying agent-based sensor and information processing is Structural Load and Structural Health Monitoring (SLM/SHM) of mechanical structures. This work investigates a data processing approach for material-integrated and mobile ubiquitous SHM and SLM systems by using self-organizing mobi...

Load-bearing engineering structures typically have a static shape fixed during design based on expected usage and associated load cases. But neither can all possible loading situations be foreseen, nor could this large set of conditions be reflected in a practical design methodology—and even if either was possible, the result could only be the best...

Today sensor data processing and information mining become more and more complex concerning the amount of sensor data to be processed, the data dimension, the data quality, and the relationship between derived information and input data. This is the case especially in large-scale sensing and measuring processes embedded in Cloud environments. Measu...

Today sensor data processing and information mining become more and more complex concerning the amount of sensor data to be processed, the data dimension, the data quality, and the relationship between derived information and input data. This is the case especially in large-scale sensing and measuring processes embedded in Cloud environments. Measu...

Data evaluation is crucial for gaining information from sensor networks. Main challenges include processing speed and adaptivity to system change, both prerequisites for SHM-based weight reduction via relaxed safety factors. Our study looks at soft real time solutions providing feedback within defined but flexible, application-controlled intervals....

Combining different perspectives from materials science, engineering, and computer science, this reference provides a unified view of the various aspects necessary for the successful realization of intelligent systems. The editors and authors are from academia and research institutions with close ties to industry, and are thus able to offer first-h...

Ubiquitous computing and The Internet-of-Things (IoT) raises rapidly in today’s life and is becoming part of self-organizing systems (SoS). A unified and scalable information processing and communication methodology using mobile agents is presented to merge the IoT with Mobile and Cloud environments seamless. A portable and scalable Agent Processin...

The Internet-of-Things (IoT) gets real in today’s life and is becoming part of pervasive and ubiquitous computing networks offering distributed and transparent services. A unified and common data processing and communication methodology is required to merge the IoT, sensor networks, and Cloud-based environments seamless, which can be fulfilled by t...

Data evaluation is crucial for gaining information from sensor networks. Main challenges include processing speed and adaptivity to system change, both prerequisites for SHM-based weight reduction via relaxed safety factors. Our study looks at soft real time solutions providing feedback within defined but flexible, application-controlled intervals....

The ubiquitous development of information and communication technology enables new opportunities for products as well as for production and manufacturing systems. These systems will be able to learn and adapt their behaviour during the systems operation for a continuos optimization. This results in an increasing structural complexity and dynamics o...

Integration of sensors into various kinds of products and machines provides access to in-depth usage information as basis for product optimization. Presently, this large potential for more user-friendly and efficient products is not being realized because (a) sensor integration and thus usage information is not available on a large scale and (b) pr...

These authors contributed equally to this work. Abstract: Integration of sensors into various kinds of products and machines provides access to in-depth usage information as basis for product optimization. Presently, this large potential for more user-friendly and efficient products is not being realized because (a) sensor integration and thus usag...

Integration of sensors into various kinds of products and machines provides access to in-depth usage information as basis for product optimization. Presently, this large potential for more user-friendly and efficient products is not being realized because (a) sensor integration and thus usage information is not available on a large scale and (b) pr...

Design and Production processes become more and more complex. Today, industrial manufacturing environments consists of large-scale networks connecting smart sensors, embedded systems, server, desktop, and mobile computers. Mobile software Agents can be used in such strong heterogeneous environments with design, manufacturing, and logistics faciliti...

The design and simulation of an agent processing platform suitable for distributed computing in heterogeneous sensor networks consisting of low-resource nodes is presented, providing a unique distributed programming model and enhanced robustness of the entire heterogeneous environment in the presence of node, sensor, link, data processing, and comm...

One of the major challenges in Structural Monitoring of mechanical structures is the derivation of meaningful information from sensor data. This work investigates a hybrid data processing approach for material-integrated structural health and load monitoring systems by using self-organizing mobile multi-agent systems (MAS), and inverse numerical me...

2015 Abstract A novel and unified approach for reliable distributed and parallel computing using mobile agents is introduced. The agents can be deployed in large scale and hierarchical network environments crossing barriers transparently. The networks can consist of high-and low-resource nodes ranging from generic computers to microchips, and the s...

A novel and unified design approach for reliable distributed and parallel data processing in large scale networks consisting of high-and of low-resource nodes (ranging from generic computers to microchips) using mobile agents is introduced. This approach enables the development of sensor clouds of the future integrated in daily use computing enviro...

A novel and unified design approach for reliable distributed and parallel data processing in large scale networks consisting of high-and of low-resource nodes using mobile agents is introduced. This approach enables the development of sensor clouds of the future integrated in daily use computing environments and the Internet. Agents can migrate bet...

Multi-agent systems (MAS) can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based...

Embedded Systems used for control, for example in Cyber-Physical-Systems (CPS), perform the monitoring and control of complex physical processes using appli-cations running on dedicated execution platforms in a resource-constrained man-ner. Application-specific System-On-Chip (SoC) designs providing the execution plat-form have advantages compared...