State of the Art Report

Date: 2024
Programs: Microsoft Office, Zotero
Technologies: IoT/IIoT, CPS, Edge/Fog/Cloud Computing, AI, Machine Learning

About the Project
This State of the Art Report (STAR) on Knowledge Modeling & Sensors was created as part of a course for the Josef Ressel Center for Knowledge-based Visual Data Analysis in Industrial Production. The aim was to provide a well-founded analysis of current technologies, methods and challenges relating to the use of industrial data. The focus was on the role of intelligent sensor technology, structured data models and modern system architectures in the context of Industry 4.0, IIoT and machine learning. Due to the growing variety and volume of data in modern production environments, the ability to process and integrate data efficiently is becoming a key competence. Based on peer-reviewed publications, the report provides a structured analysis of relevant technologies for the acquisition, processing and use of industrial sensor data. The results help to lay the foundations for further research at the center and to prepare practical solutions for real industrial problems.

Technical Appropach
The report is based on a structured literature search conducted in April 2024 using scientific databases such as IEEE Xplore, ScienceDirect, Google Scholar, ResearchGate and the AI supported platform scienceOS. The search focused on publications from 2019 to 2024 and was based on topic-specific keywords. The relevance of the articles was systematically evaluated using defined exclusion criteria (e.g. language, availability, duplicates, subject-specificity). The selected publications were then analyzed according to four core categories:

1. sensor technology & data acquisition
2. data modeling
3. system architectures
4. performance & usability

This structured approach made it possible to establish cross-connections between the works and to draw a comprehensive picture of current technological developments.

Retrospective
Although it is not a classic development project, the STAR was an intensive analysis process with high relevance for application-oriented research. The literature review clearly showed how inconsistent and heterogeneous industrial data infrastructures still are today - both in terms of sensor integration as well as data models and system interfaces. The discussion of smart sensors, semantic data structures and distributed data processing via edge/fog/cloud concepts was particularly valuable. The report not only highlights current challenges, but also shows strategic solutions for effectively using data for predictive maintenance, efficiency analyses or automated decisions. As a contribution to the Josef Ressel Center, the work lays an important theoretical foundation for future research and practical projects.