Conferences
Meet us
Meet us in person at the upcoming conferences listed below.
Are you interested in joining and meeting team members of ECOMAI? Just send an short email!

Embedded world
Exhibition + Conference
11 – 13 March 2025 | Nürnberg, Germany
Conference Talks and Tutorials
March 11, 2025
Session 1.1 IOT & CONNECTIVITY
A Visionary Modelling Approach for Predictive Maintenance in a Highly Regulated Environment
Peter Lieber, SparxSystems Europe
Class 7.1: 14:00h – 17:00h
Introduction to tinyML – Running Deep Learning Models on Low-Power Micro-Controllers
Prof. Daniel Mueller-Gritschneder, TU Vienna
March 13, 2025
Session 7.7 EDGE AI // AI Assisted Motor Control, 12:15h – 12:45h
From Simulation to Silicon on a RISC-V with AI Accelerator
Steven Klotz, Infineon
Exhibition Booth 4-410
presenting partners: Moteon, SparxSystems Europe, Infineon, neuroConn
Use Case: AI for Platform Screen Door Systems (PSD). PSDs are used in public transportation and separate the waiting area from the rail line, preventing passenger contact with moving vehicles. These systems require high availability (99.4%+), leading to costly preventive maintenance. PdM (Predictive Maintenance) is not yet applied to PSD. This use case discusses the innovation development of Albayrak (Aldoor/Turkiye), a designer and manufacturer of PSD.
Intelligence for the IoT requires to stream huge amounts of data from edge sensors towards the cloud, where deep learning models interpret the data. EdgeAI moves deep learning models from the cloud onto the Edge platforms themselves offering huge gains in terms of connectivity requirements, energy, cost, privacy and end-to-end latency. tinyML or Extreme Edge AI moves the deep learning tasks even further right onto the microcontrollers connected to the sensors.
AI concepts offer sophisticated approaches for condition monitoring and control in embedded applications.
Imperfect simulation models can undermine the successful transfer of developed concepts, limiting their applicability in real systems.
Additionally, the limited computational power of real-time microcontrollers necessitates adaptations to ensure efficient execution of learned policies.
In this work, a reinforcement learning-based control policy for energy-efficient motor control is presented, highlighting the sim-to-real challenges of deploying this artificial intelligence controller. The AI control concept is studied in the context of a motor control application, with the microcontroller evaluated accordingly.
Additional focus is placed on the computational constraints of a low-resource RISC-V microcontroller,
presenting toolchain and optimization strategies for real-time operation on cost-effective hardware
EFECS 2024
5-6 December 2024 | Ghent, Belgium
Meet us in Person to discuss the lates development of ECOMAI:
- Director Funding Project Manager bei Infineon Technologies
- ECOMAI Commercial Project Leader
- Business Development / Research Projects Sparx Systems Europe
- ECOMAI Dissemination + Exploitation
Software Architecture Alliance
22. + 23. Oktober 2024 | München, Germany
Talk
Modellbasierte Architektur für die Entwicklung von IoT Geräten bei usePAT
Presenters
Salomé Wagner, Sparx Systems CE
Georg Heinz, usePAT GmbH
Diese Komplexität gab den konkreten Ausschlag für die Evaluation einer neuen Methodik. usePAT hat sich dabei entschieden, die modellbasierte Systementwicklung als strategisches Entwicklungselement über das gesamte Unternehmen einzuführen, um diese Komplexität zu meistern.
Die Herangehensweise:
- ermöglicht durch Daten-, Infrastruktur- und Applikationsarchitekturen eine ganzheitliche Entwicklung von IoT Systemen,
- dokumentiert diese Systementwicklung über den gesamten Lebenszyklus,
- stellt das Wissensmanagement auch bei Fehlentwicklungen sicher.
Diese Evaluation und Einführung der modellbasierten Systemarchitektur erfolgt im Rahmen des EU Förderprojektes PENTA „ECOMAI“, Ecological Motor Control and Predictive Maintenance with Artificial Intelligence.
Enterprise Architect
Global Summit 2024
September, 18 + 19 2024
online
Talk
Pioneering AI-driven MBSE Methodologies within a Diverse Ecosystem
Presenter
Salomé Wagner, Sparx Systems CE
The development of an AI-driven Model-Based Systems Engineering (MBSE) methodology within a robust ecosystem that bridges industry and academia – this is the Penta Project ECOMAI (Ecological Motor Control and Predictive Maintenance with AI).
This research project is founded by the European Union under the umbrella of the European Chips Act. Its goal is to address critical challenges such as energy efficiency and skill shortages in the semiconductor market. With members of the ECOMAI consortium, we explore the MBSE methodology, the barriers to adopt and the benefits of implementing. Features like call graph visualization are essential for the understanding, the modelling language essential for broad adoption.
The ECOMAI design kit for AI-enhanced drive systems will orchestrate hard- and software and will include the ECOMOD Modelling Toolbox. In this talk, we will give you an insight of this ongoing development.
2024 European Control Conference (ECC)
June 25-28, 2024
Stockholm, Sweden
Paper Contribution, Abstract
Energy-Aware Speed Regulation in Electrical Drives: A Load-Agnostic Motor Control Approach Via Reinforcement Learning
The paper introduces a novel design of a reinforcement learning agent. Compared to application-tuned classical control methods, the agent demonstrated advanced capability to save energy, showcasing its potential for future applications.
Authors
Klotz Steven, Buksch Thorsten, Infineon Technologies AG, Goswami Dip, Eindhoven University of Technology, Mueller-Gritschneder Daniel, TU Munich
ICENSOS 2023
4th to 6th April 2023
Konya, Turkey
Paper Contribution, Abstract
Machine Learning based Diagnostic Approach to Condition Monitoring of Railway Platform Screen Door Systems
by Şükrü Görgülü 1, İsa Koç 2, Necim Kırımça 3, Ömer Mermer 4, Mehmet Karaköse 5, and Mehmet Tankut Özgen 6 (1,6 Dept. of Electrical and Electronics Engineering, Eskişehir Technical University, Türkiye; 2 Dept. of Electrical and Electronics Engineering, Eskişehir Osmangazi University, Türkiye; 5 Dept. of Computer Engineering, Elazığ Fırat University, Türkiye; 1,2,3,4 Albayrak Makine Elektronik San. Tic. A.Ş. Eskişehir, Türkiye)