SustainML Embedded Devices & Artificial Intelligence

Prof. Dr. Paul Lukowicz, SustainML’s partner, delivered an insightful talk on the future of cognitive technologies and their application in intelligent production.

The talk, hosted by DFKI Kaiserslautern's Embedded Intelligence group, focused on the challenges and opportunities of utilizing artificial intelligence (AI) on embedded devices with limited computational resources and centering on the fusion of AI and human intelligence, highlighting the significance of collaborative efforts between humans and autonomous systems to harness the full potential of AI.

One of the most promising applications of AI in intelligent production lies in its ability to leverage big data. By combining AI with vast amounts of data collected from sensors and devices, industries can gain valuable insights into their processes, reducing downtime and associated costs and the ability to predict and prevent potential issues in industrial equipment, such as electric motors. Data analysis on vibrations, temperature fluctuations, and power consumption allows for more informed decision-making, improving efficiency and productivity.

However, implementing AI on edge devices with limited computational resources presents a significant challenge. Energy efficiency becomes paramount in such scenarios, as traditional AI models can be computationally expensive and resource-intensive. To address this issue, Prof. Dr. Lukowicz takes a proactive approach and aims to enable practical AI applications on devices with constrained local computing capabilities by reducing computational requirements and optimizing machine learning algorithms.

These efforts not only contribute to efficient AI utilization but also have a positive impact on the environment. Reducing the energy consumption of running AI models diminishes the carbon footprint associated with these processes. It is aligned well with the growing concern for sustainable technology and the need to minimize the ecological impact of emerging innovations. 

This is where Green AI projects such as SustainML take on special relevance as they can be key to reducing the Machine Learning generated carbon footprint.

Furthermore, Prof. Dr. Lukowicz's talk emphasized the importance of addressing the ethical implications of AI in intelligent production. As autonomous systems and AI-driven technologies become more prevalent in industrial settings, ensuring they operate ethically and responsibly is crucial. Integrating human intelligence into AI systems enables a more comprehensive understanding of potential consequences and safeguards against biased decision-making or unintended adverse outcomes.


Short Bio. 

Prof. Dr. Paul Lukowicz is a Full Professor of AI at the RPTU in Kaiserslautern, Germany, and at the same time, is Scientific Director at DFKI Kaiserslautern, where he heads the Embedded Intelligence group. Previous positions include Full Professor of Embedded Systems at the University of Passau, Germany, and Full Professor in the Computer Engineering Dept. at the University for Health Sciences, Medical Informatics and Technology in Innsbruck, Austria. His research focuses on context-aware ubiquitous and wearable systems, including sensing, pattern recognition, system architectures, models of large-scale self-organized systems, and applications. Paul Lukowicz is running a wide range of German national and EU projects.

He is the Coordinator of the HumanE AI-Net, a giant networking project with more than 50 European partners, and acts as Editor for various scientific publications. He has served on over 50 program committees (including TPC Chair) at high-quality international conferences of all the main conferences within his research area.


All the SustainML participants: DFKI, Inria, IBM, University of Copenhagen, UpMemTechnische Universität Kaiserslautern, and eProsima. 


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