I initiated and I am the principal investigator of student project ELMO. Electricity profiLe MOnitoring (ELMO) is energy monitoring with Commercially-Off-The-Shelf (COTS) hardware. Acquisition systems are deployed for 43 sewing machines at the department of Textile & Design (TD) of Reutlingen University. This is followed by a longer unattended operation of the data acquisition. A data evaluation makes different operating conditions visible.
System design and implementation, application and research are covered by various representatives from three university departments. ELMO is an interfacultative project among the following cooperation partners
- Department of Computer Science (INF); Prof. Dr. Christian Decker (Principal Investigator)
- Department of Textile & Design (TD); Prof. Dr. Katerina Rose
- Department of Engineering (TEC); Prof. Dr. Debora Coll-Mayor, Prof. Dr. Antonio Notholt
Main objectives of ELMO are
- Provide real energy consumption data for research and teaching at the university.
- Previously manually recorded operating conditions, including maintenance and utilization, can be automatically captured in the application context.
With ELMO, a 24/7 energy recording system is available in a real environment at the university. It improves the coordination of teaching activities at the machines and leads to a better learning experience for students. It supports the planning and use of financial investments in maintenance and equipment acquisition. In addition, ELMO serves as a continuous data source for current research in the field of digitization of energy markets.
Features and Use Cases
Energy consumption is a base information enabling lots of interesting use cases. ELMO implements the following features:
- Monitoring energy consumption of 43 sewing machines at a 1-minute interval
- Indication of available and occupied machines for teaching coordination
- Tutor presence indicator
- Monitoring and tracking of maintenance intervals when a machine operation hours are exceeded
- Various profile statistics on machine usage
- Live energy consumption display
Outstanding: Teaching, Research and Application closely Connected
Teaching: Students of the faculty INF apply their knowledge from different modules of Business Informatics in a concrete application project. You work in a team with modern agile project methods. Complete project documentation and code are publicly available as open source.
Application: Prof. Rose (Faculty TD) wants to improve resource utilization. Students should be able to use better learning conditions. The maintenance of the machine park should be supported purposefully. A usage analysis should better quantify investments in machines.
Research: Prof. Coll-Mayor and Prof. Noholt (Faculty TEC) investigate how energy use and distribution can be controlled by new data-based methods. ELMO as a data source of a real application environment expands previous energy consumption simulations and allows new types of scientific investigations and contributions to be made.
Relation to Reutlingen University (HSRT)
The HSRT campus offers a unique environment for implementing such a project within one semester. The campus combines the key partners of the cooperation. External impact is visible through public documentation as well as the manifold use of ELMO in research, teaching and resource management.
Funding: funds of the 2017 Teaching Award of the HSRT from Prof. Dr. C. Decker flexibly finance the ELMO project with extremely short lead times.
The ELMO student project was awarded this term’s MHP prize for the best bachlor project in in Business Informatics. My congrats to the students. Great job! :-)