IoT Enabled Condition Monitoring
In this course, you will gain knowledge and practical skills in utilizing IoT technologies, data analytics and machine learning algorithms for effective condition monitoring of industrial systems.
Facts and figures
Target group: Operators,engineers and managers working in different industrial fields such as railway, mining, construction, process, etc. The course can also be adapted to specific needs.
Prerequisites: High school, bachelor's degree or equivalent.
Scope: 40 hours
Language: English
Location: Fully digital
Price: SEK 6,000 excluding VAT
Registration: Link to registration is further down the page. Luleå University of Technology reserves the right to cancel the course if there are too few participants.
Content of the course:
The training package consists of the following content:
- Sensor and sensor technology
- IoT implementation
- Data processing, signal processing and machine learning
- Condition monitoring
- AI for maintenance analysis
After completing the course, you will be able to
- Understand IoT concepts and architectures, exploring sensor networks and connectivity protocols for data collection from industrial assets.
- Analyse and interpret the data using advanced data analytics techniques, identifying patterns, anomalies, and potential failures.
- Develop predictive models using machine learning algorithms.
- Identify early signs of deterioration, predict maintenance requirements, and optimize maintenance schedules.
- Demonstrate the designing and implementing IoT-enabled condition monitoring systems.
Course structure
Five days and eight hours of teaching, hands-on, and lab work. The exact dates will be decided together with the course participants.
Teachers
Matti Rantatalo, Associate Professor
Praneeth Chandran, postdoctoral researcher
Taoufik Najeh, associate senior lecturer
Registration of interest
- Register your interest here
Luleå University of Technology reserves the right to cancel the course in case of too few registrations.
Updated: