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29th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2024

作者： Redeker, Magnus Quirin, Dennis Schroeder, Rafael Klausmann, Tobias Löwen, Alexander Wollbrink, Alexander Stichweh, Heiko Althoff, Simon Bender, Amelie Sextro, Walter Hesse, Marc Fraunhofer Iosb IOSB-INA Lemgo Fraunhofer Institute of Optronics System Technologies and Image Exploitation Germany Bielefeld University Cognitronics & Sensor Systems Germany Friedrich Remmert GmbH Germany R & D Systems Engineering Lenze Se Germany Paderborn University Faculty of Mechanical Engineering Dynamics and Mechatronics Paderborn33098 Germany Weidmüller Group Germany

ISBN: (纸本)9798350361230

The holistic application of data-driven value-adding services (DDSs) to shop-floor assets (SFAs;e.g. equipment, machines, components) is a major obstacle, particularly for small and medium-sized enterprises (SMEs): Due to the high complexity and required expertise in various disciplines. It is necessary to i) select suitable DDSs for a relevant component in production, ii) provide data for their training, iii) deploy the DDSs in the given IT/OT infrastructure, and iv) setup data-streams between SFAs, DDSs, and dashboards. Currently, many companies are implementing flagship projects that go through the necessary steps for individual components, but these isolated solutions are not scalable due to the need for manual intervention. This paper describes how to completely automatize the four steps and their consolidation in a scalable Industry 4.0 one-stop-shop solution. To achieve this goal, each asset is equipped with an Asset Administration Shell (AAS) that specifies, in particular, the represented asset's capabilities, the data required to apply such a capability and the data generated by a capability. Based on the AASs of SFAs, DDSs, and computing resources (CRs), a matching service suggests automatically which DDSs would add value to which SFAs and, for each SFA-DDS match, in which CR to deploy the DDS. A trade fair demonstration provides strong support for the statements made: The one-stop-shop solution including the automatic matching greatly simplifies the application of data-driven services and, in some cases, even makes it possible at all. © 2024 IEEE.

关键词： AAS-based one-stop-shop Industry 4.0-solution Data-driven value-adding services Shop-floor optimization

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Digital Twin to Enhance Offshore Power-to-X Platforms with Operational Alarm Management 57

Digital Twin to Enhance Offshore Power-to-X Platforms with O...

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18th IFAC Workshop on Time Delay systems, TDS 2024

作者： Bodenstein, Frederike Dieckmann, Stefan Dittler, Daniel Geschke, Alexander Jazdi, Nasser Weyrich, Michael Institute of Industrial Automation and Software Engineering University of Stuttgart Pfaffenwaldring 47 Stuttgart70569 Germany Max Planck Institute for Dynamics of Complex Technical Systems Sandtorstraße Magdeburg39106 Germany

The operation of innovative process plants like offshore Power-to-X platforms that produces green hydrogen and derivatives poses critical risks for the environment and personnel as well as the operating company. This is due to the high system complexity, the energies and materials used and the associated high investment and maintenance costs. To keep these risks low, the occurrence of corresponding critical cases must be avoided, for which reason the personnel must be optimally assisted and enabled in their tasks during all phases of the platform life cycle. We have therefore enhanced a digital twin presenting a teleoperation platform that allows modular use of assistance systems. As a proof of concept, an alarm management system is presented. © 2024 The Authors.

关键词： Investments

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Automated Visual Vegetation Detection for Weed Management on Transportation Infrastructure 5

Automated Visual Vegetation Detection for Weed Management on...

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Automated Visual Inspection and Machine Vision V 2023

作者： Werner, Christoph S. Frey, Simon Reiterer, Alexander Fraunhofer-Institute for Physical Measurement Techniques IPM Freiburg Germany Department of Sustainable Systems Engineering INATECH Albert-Ludwigs-University Freiburg Germany

ISBN: (数字)9781510664562

ISBN: (纸本)9781510664555

Vegetation on traffic routes is not only an aesthetic problem. On railways and roads, it poses a safety risk by reducing the elasticity of track beds or damaging road surfaces. Therefore, complex weed management is indispensable. This is currently achieved mainly through the extensive use of herbicides or manual removal, which pollutes the environment and incurs high costs. These negative impacts can be mitigated by an automated vegetation detection which allows efficient, targeted treatment and preventive long-term monitoring. A reliable method to achieve this is to exploit the characteristic spectral fingerprint of vegetation: Chlorophyll shows a high reflectivity in the green and infrared spectral region while strongly absorbing red and blue light. We present such a visual monitoring system comprising multiple cameras and an active illumination which is employed on railroads. The individual cameras address different spectral regions and are superimposed through a position-synchronized triggering to obtain a multi-spectral image. Multi-pixel binning greatly extends the dynamic range of the cameras and, in combination with active illumination and high-speed dark frame recording, allows operation during day and night without degradation from ambient light conditions. The system achieves about 5 mm effective resolution and can operate up to a speed of 100 km/h. This is possible through embedded real-time pre-processing and data reduction already in the camera units. A processing delay of less than 100 ms is the consequence which allows targeted actuation of weed-treatment methods (e.g., spray nozzles) during movement. In combination with GNSS-sensors geo-referenced documentation of the coverage rate is possible. © 2023 SPIE.

关键词： Vegetation

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eDEM-CONNECT: An Ontology-Based Chatbot for Family Caregivers of People with Dementia 12th

eDEM-CONNECT: An Ontology-Based Chatbot for Family Caregive...

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12th International Conference on Mobile Communication and Healthcare, MobiHealth 2023

作者： Boiting, Maurice Tschorn, Niklas Suravee, Sumaiya Yordanova, Kristina Halek, Margareta Jagoda, Franziska A. Lüdtke, Stefan Burmann, Anja Fraunhofer Institute for Software and Systems Engineering ISST Dortmund44147 Germany Institute for Data Science Universität Greifswald Greifswald17489 Germany School of Nursing Science Faculty of Health Universiät Witten/Herdecke Witten58453 Germany Institute for Visual and Analytic Computing Universät Rostock Rostock18059 Germany

ISBN: (纸本)9783031606649

Home care of people with dementia (PwD) is mainly organized and carried out by non-professional family caregivers, who struggle to interpret the needs of PwD correctly and are confronted with the challenging behavior of their relatives. Although support services for family caregivers are widespread in Germany, they are rarely used due to the fact that information is poorly organized and relatives are faced with a flood of disorganized, outdated, and confusing content. Due to the technical development of chatbot technologies (ChatGPT), chatbots gain more and more relevance. Based on the new technological possibilities, we developed an online communication and service platform with an integrated chatbot within the eDEM-CONNECT project, with the aim of making structured and easily understandable information accessible for family caregivers. This work focuses on the development of a chatbot pipeline that has broad domain knowledge through a provided ontology on the topic of agitation of PwD. This allows the chatbot to provide relevant and peer-reviewed information to family members. In our approach, a patient history is first taken based on several diagnostic questions so that relevant information can be output in a later step. For this purpose, we demonstrate that agitations in natural language can be correctly recognized by the used BERT model and that our developed chatbot is able to select further diagnostic questions based on the predictions of a Markov logic network. © ICST institute for Computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Neurodegenerative diseases

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A multi-agent approach with verifiable and data-sovereign information flows for decentralizing redispatch in distributed energy systems

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Energy Informatics 2025年第1期8卷 1-27页

作者： Heess, Paula Holly, Stefanie Körner, Marc-Fabian Nieße, Astrid Radtke, Malin Schick, Leo Stark, Sanja Strüker, Jens Zwede, Till Branch Business and Information Systems Engineering Fraunhofer FIT Wittelsbacherring 10 Bavaria Bayreuth95444 Germany OFFIS - Institute for Information Technology Escherweg 2 Lower Saxony Oldenburg26121 Germany FIM Research Center University of Bayreuth Wittelsbacherring 10 Bavaria Bayreuth95444 Germany

The need to harness the flexibility of small-scale assets for system stabilization, including redispatch, is growing rapidly with the increasing prevalence of distributed generation, such as photovoltaic systems and heavy loads, in particular heat pumps and electric vehicles. Integrating these resources into the redispatch process presents special requirements: On the one hand, building trust with the owners of such assets requires privacy and a reasonable degree of autonomy and engagement. On the other hand, besides the system’s scalability and robustness, the verifiability and traceability of provided data are essential for grid operators who depend on the reliable provision of redispatch services. To date, research and practice have encountered significant challenges in defining a system that enables the inclusion of decentralized flexibilities while satisfying necessary requirements. To that end, we present a novel conceptual system design that addresses these challenges by combining a multi-agent system (MAS) approach with verifiable information flows through digital self-sovereign identities (SSIs) and Zero-Knowledge-Proofs (ZKPs). Single agents, as edge devices, operate locally and autonomously, respecting customer preferences, while MAS provide the ability to design robust, reliable, and scalable systems. SSI enables agents to manage their data autonomously, while ZKPs are used to protect users’ privacy through selective data disclosure which allows the verification of the correctness of information without disclosing the underlying data. To validate the feasibility of this design, a case study is included to demonstrate the functionality of key sub-processes, such as baseline optimization, aggregation, and disaggregation, in a realistic scenario. This case study, supported by a prototype implementation, provides initial evidence of the concept’s soundness and lays the groundwork for future evaluation through extensive simulations and field testing. Together

关键词： Decentralized systems

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Integrity Estimation of Twitter Based Event Recognition Using Scrutiny of Analyzed Data 2

Integrity Estimation of Twitter Based Event Recognition Usin...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Siva Rama Lingham, N. Parameswari, M. Karthick, P. Priya, T. Subha Rathi Rajesh, G. Jagannathan, J. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Knowledge Institute of Technology Department of Computer Science and Engineering Salem India Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College Department of Computer Science and Engineering Chennai India School of Engineering and Technology Jeppiaar University Chennai India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Department of Software and Systems Engineering Vellore Katpadi632014 India

ISBN: (纸本)9798350328202

Twitter has been observed to be one of the essential data resources for dependable event accreditation. In any case, Twitter-based event affirmation structures can't guarantee assessment concerning their attestation results. Talk statement has been locked in starting late to enable liberal event Recognition. This problem is not yet evident in light of the assumption that most people tend to think that they have a specific limit to the data on Twitter that have frames based on events based on Twitter. Current appraisals see new pieces by seeing and looking at the significant psychological aspects of hitting the details on Twitter. No matter, the scale of the visual cues can be well established, with the intention that it is essential to design an integrated Twitter experiment with another set of extensible data resources to rectify this problem. The problem is the processes by which you should wholeheartedly investigate all converted data because it has different data structures, transfer times, etc. This issue of address, the paper proposes a framework for evaluating the use of Twitter-based events and examines two types of data resources for the reliability of impact testing. Our framework uses the resultant of the request obtaining by various events and relevant to the articles on it. This paper has improved the cleaning test with the proposed process how the integrity estimation of twitter based event can be recognized with the help of group of analyzed data. The evaluation indicates that the proposed system provides visible high-level testing events and a variety of low-level testing events. © 2024 IEEE.

关键词： Impact testing

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Dynamic Multimedia Encryption Using a Parallel File System Based on Multi-Core Processors 4

Dynamic Multimedia Encryption Using a Parallel File System B...

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4th IEEE International Conference on Data engineering and Communication systems, ICDECS 2024

作者： Simi Margarat, G. Malathi, S. Pasumpon Pandian, A. Anakath, A.S. Kannadasan, R. New Prince Shri Bhavani College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Grt Institute of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Tiruttani India Care College of Engineering Department of Computer Science and Engineering Trichy India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India School of Computer Science and Engineering Department of Software Systems Tamil Nadu Vellore India

ISBN: (纸本)9798350393354

A new parallel file system and multi-core processor-based dynamic multimedia encryption method is presented in this study. Multimedia encryption efficiency and security were the main goals, addressing massive data sets and high-speed processing. We created a dynamic encryption algorithm for multimedia content, supported by a strong parallel file system and tuned for multi-core processing. Multiple tests showed significant improvements in encryption and decryption times, retaining short durations for real-time applications. After encryption, the system maintained multimedia content quality and accuracy with data integrity rates nearing 100%. Balanced CPU utilization showed efficient resource use and processor load management. The system's excellent throughput efficiency showed its capacity to process enormous amounts of data. These results indicate that parallel file systems and multi-core CPUs may solve multimedia encryption problems. Adaptable and scalable, the system supports many multimedia formats and sizes. This paper proposes a multimedia encryption system that improves performance data security and integrity, paving the way for safe multimedia processing advances. © 2024 IEEE.

关键词： Cryptography

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Evaluation of emissions and performance of a diesel engine running on graphene nanopowder and diesel–biodiesel-ethanol blends

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Environmental Science and Pollution Research 2025年第3期32卷 1466-1479页

作者： Noorollahi, Yaser Asli-Ardeh, Ezzatollah Askari Jahanbakhshi, Ahmad Khodayari, Ali Gorjian, Shiva Department of Biosystems Engineering University of Mohaghegh Ardabili Ardabil Iran Mechanical Engineering of Biosystems Department Lorestan University Khorramabad Iran Chemistry Department Faculty of Science University of Mohaghegh Ardabili P.O. Box 179 Ardabil Iran Tehran Iran Fraunhofer Institute for Solar Energy Systems ISE Heidenhofstraße 2 Freiburg Im Breisgau79110 Germany

Today, there are environmental problems all over the world due to the emission of greenhouse gasses caused by the combustion of diesel fuel. The excessive consumption and drastic reduction of fossil fuels have prompted the leaders of various countries, including Iran, to put the use of alternative and clean energy sources on the agenda. In recent years, the use of biofuels and the addition of nanoparticles to diesel fuel have reduced pollutant emissions, improved the environment, and enhanced the physicochemical properties of the fuel. The current research deals with the experimental evaluation of emissions and performance of a diesel engine running on graphene nanopowder together with diesel–biodiesel-ethanol blends. The engine variables studied included the engine speed (in three stages 1800, 2200, and 2600 rpm) and three types of fuel including graphene nanoparticles (with values of 25 and 50 ppm), biodiesel (with volume percentages of 4, 6, and 8), and ethanol (with volume percentages of 2 and 4). The results showed that the power and torque of the D86 + B8 + E6 + G50 fuel increased on average by 20.26% and 28.76% at all engine speeds compared to the D100 fuel. The use of D86 + B8 + E6 + G50 fuel resulted in a significant reduction in CO (38.84%), UHC (21.24%), and NOx (19.92%) emissions compared to D100 fuel. In addition, a significant increase in CO2 emissions (23.19%) was observed. The results of this study clearly show that the use of biofuels and the addition of nanopowder to D100 fuel are very effective methods to improve combustion, performance, and emission characteristics in diesel engines. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Biodiesel

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On the Current State of Industrial Data Science: Challenges, Best Practices, and Future Directions 57

On the Current State of Industrial Data Science: Challenges,...

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18th IFAC Workshop on Time Delay systems, TDS 2024

作者： von Enzberg, Sebastian Weller, Julian Brock, Jonathan Merkelbach, Silke Panzner, Melina Lick, Jonas Kühn, Arno Dumitrescu, Roman Fraunhofer Institute for Mechatronic Systems Design Zukunftsmeile 1 Paderborn33102 Germany Hochschule Magdeburg-Stendal Breitscheidstr. 2 Magdeburg39114 Germany Advanced Systems Engineering Heinz Nixdorf Institute Fürstenallee 11 Paderborn33102 Germany

Data science provides organizations with the capability to draw insights from large amounts of data. Numerous sectors such as banking and marketing leverage this potential already. In comparison, industrial enterprises are slow in creating profit from their data. This originates from various factors, such as availability and quality of data, reliability of solutions, or a lack of organizational embedding. Traditionally, Industrial Data Science (IDS) is referred to as the application of data analytics within industrial settings. In this paper, we expand this definition, positioning IDS as an interdisciplinary field to encompass the holistic integration and organization of data science efforts into industrial enterprises. We provide three contributions. First, we conduct a thorough literature review on current issues and the state of the art of implementing IDS. Second, we conduct eight interviews with practitioners from different industrial enterprises to identify best practices and research gaps. Third, we condense our findings into a single framework which structures multiple layers of IDS in real-world organizations, such as projects, organizational embedding, and roles. Our findings can lead practitioners and academics in their quest to streamline their IDS efforts, guiding them into structured application and further research directions. © 2024 The Authors.

关键词： Smart manufacturing

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Impersonated Human Speech Chatbot with Adaptive Frequency Spectrum 3

Impersonated Human Speech Chatbot with Adaptive Frequency Sp...

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3rd International Conference on Intelligent Communication and Computational Techniques, ICCT 2023

作者： Chettiar, Gautam Shukla, Amogh Nalwaya, Preet Sethi, Karman Prakash, Surya Vellore Institute of Technology Dept. of Communication Engineering Vellore India Department of Software Systems Vellore Institute of Technology Vellore India Indian Institute of Information Technology Allahabad Department of Electronics and Communication Engineering Prayagraj India

ISBN: (纸本)9781665453578

Recent trends in artificial intelligence and natural language processing models have led to the generation of highly efficient and versatile intelligent chatbot models., which have the potential to supplant human speech to the level of conversational proficiency. The proposed method creates a chatbot model that trains itself on open conversation datasets and aims to impersonate without compromising the emotional sentiments in the voice. These datasets extract from the applications such as WhatsApp., Telegram., Messenger., or any other chatting platform. Datasets convert to a machine-readable format., which is dynamically updated in real-time during the conversation., and then using speech conversion algorithms convert the reply into the desired individual's voice. The proposed model's conversational ability depends on the amount of conversation data., which gives the output in the person's voice frequency. By using an NLP-based chatbot trained on personalized data using KNN., and handling misses by pipelining the chatbot inputs to the GPT-2 model., the model can generate human-like replies even if there is data insufficiency. The natural replies are complemented with matching human voice and tone characteristics by using the vocoder model., which matches the spectral characteristics of the target voice onto the required voice. This opens a plethora of commercial and therapeutic applications that provide excellent insights into implementing natural communication models for humanoid and robotics innovations. © 2023 IEEE.

关键词： Sentiment analysis

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