TY - JOUR A1 - Loose, Harald T1 - Autonomous mobile robots for outdoor tasks JF - Mechanika N2 - This paper presents a low-cost hardware platform for outdoor robots, being suitable for education, industrial prototyping and private use. The choice of components is discussed, including platform, sensors and controller as well as GPS and image processing hardware. Furthermore, a software approach is proposed, allowing students and researchers to easily implement own algorithms for localization, navigation and the tasks to fulfill. Several robots can be integrated in a framework which connects various different hardware platforms, called the BOSPORUS network. Together with other components, they form an intelligent network for gathering sensor and image data, sensor data fusion, navigation and control of mobile platforms. The architecture of a reference platform on the campus of the Brandenburg University of Applied Sciences is presented and evaluated. Y1 - 2007 U6 - https://doi.org/10.5755/j02.mech.36230 VL - 68 IS - 6 SP - 70 EP - 73 PB - Kaunas University of Technology CY - Kaunas ER - TY - CHAP A1 - Orlowski, Maximilian A1 - Knauff, Emilia A1 - Marquardt, Florian T1 - Towards Personal Assistants for Energy Processes Based on Locally Deployed LLMs T2 - Proceedings of the 17th International Conference on Agents and Artificial Intelligence (ICAART 2025) , 2025, Porto, Portugal N2 - This paper presents a coaching assistant for network operator processes based on a Retrieval-Augmented Gen- eration (RAG) system leveraging open-source Large Language Models (LLMs) as well as Embedding Models. The system addresses challenges in employee onboarding and training, particularly in the context of increased customer contact due to more complex and extensive processes. Our approach incorporates domain-specific knowledge bases to generate precise, context-aware recommendations while mitigating LLM hallucination. We introduce our systems architecture to run all components on-premise in an our own datacenter, ensuring data security and process knowledge control. We also describe requirements for underlying knowledge doc- uments and their impact on assistant answer quality. Our system aims to improve onboarding accuracy and speed while reducing senior employee workload. The results of our study show that realizing a coaching assistant for German network operators is reasonable, when addressing performance, correctness, integration and locality. However current results regarding accu- racy do not yet meet the requirements for productive use. Y1 - 2025 U6 - https://doi.org/10.5220/0013175600003890 SP - 695 EP - 706 PB - SCITEPRESS ER - TY - JOUR A1 - Stein, Stefan A1 - Pilgermann, Michael A1 - Sedlmayr, Martin T1 - Systematic Evaluation of Manufacturer Disclosure Statements for Medical Device Security (MDS2) to Strengthen Hospital OT Security Measures – Lessons Learned JF - Studies in health technology and informatics N2 - The growing number of connected medical devices in hospitals poses serious operational technology (OT) security challenges. Effective countermeasures require a structured analysis of the communication interfaces and security configurations of individual devices. State of the art: Although Manufacturer Disclosure Statements for Medical Device Security (MDS2, Version 2019) offer relevant information, they are rarely integrated into cybersecurity workflows. Existing studies are limited in scope and lack scalable methodologies for systematic evaluation. Concept: This study analyzed 209 MDS2 documents and 161 security white papers to extract structured information on ports, protocols, and protective measures. Over 52,000 question–answer pairs were converted into a machine-readable format using customized parsing and validation routines. The aim was to establish whether this dataset could inform risk assessments and future applications involving Large Language Models (LLMs). Implementation: The analysis revealed 367 distinct ports, including common protocols such as HTTPS (443), DICOM (104), and RDP (3389), as well as vendor-specific proprietary ports. Approximately 40% of the devices used over 20 ports, indicating a broad attack surface. OCR errors and inconsistent formatting required manual corrections. A consolidated dataset was developed to support clustering, comparison across vendors and versions, and preparation for downstream LLM use, particularly via structured SBOM and configuration data. Lessons learned: Although no model training was conducted, the structured dataset can support AI-based OT security workflows. The findings highlight the critical need for up-to-date, machine-readable manufacturer data in standardized formats and schemas. Such information could greatly enhance the automation, comparability, and scalability of hospital cybersecurity measures. Y1 - 2025 U6 - https://doi.org/10.3233/SHTI251404 VL - 331 SP - 256 EP - 264 ER -