MITTWEIDA UNIVERSITY OF APPLIED SCIENCES

Mittweida – System Electronics Research Group — RES4NET
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Mittweida University of Applied Sciences — Faculty Engineering Sciences

System Electronics Research Group

Multi-sensor monitoring & human-machine interaction for Industry 4.0

Industry 4.0 Healthcare & AAL 🌍 International partner
Mittweida University – System Electronics Research Group

Research overview

Application fields
Industry 4.0 Ambient Assisted Living Safety at work Healthcare
Technology Multi-sensor data fusion using statistical and AI methods; vibrotactile human-machine feedback systems
Activity Machine and process monitoring; human-machine interaction with wearable systems

Keywords

System and process monitoring Human-machine interaction Safety Decision support Environment detection Sensors

Research activities

Machine & process monitoring

  • Process assurance
  • Quality monitoring
  • Predictive maintenance

Combining information from pre-, in- and post-process stages through multi-sensory correlation with statistical and AI methods.

Human-machine interaction

  • Environmental monitoring
  • Decision support systems
  • Wearable systems
  • Healthcare & AAL applications

Case study — Safety Jacket

Case study Vibrotactile wearable device for accident prevention in logistics

Accidents in logistics and warehousing are often associated with serious harm to those affected. Very serious incidents occur due to avoidable carelessness around transport vehicles such as forklifts — a problem that autonomous systems will only make worse.

Existing warning systems — rotating lights or acoustic signals — frequently fail. Not because of technical flaws, but because of human perception: concentrated workers ignore signals due to the “cocktail party effect” and “tunnel vision”.

Tactile alarm systems offer a decisive advantage: people react much more quickly and confidently to physical contact that immediately penetrates their personal space. The research group has developed and is optimizing a vibrotactile wearable jacket capable of sensing incipient danger through multiple integrated sensors, alerting the wearer through haptic signals before a collision occurs.

Open challenges

  • 1 Miniaturized, statistics- and AI-based systems for predictive monitoring of production systems and quality control
  • 2 Miniaturized, fully automatic and stable assistance systems for the protection of people in high-risk areas, with human-oriented haptic feedback

Selected bibliography

1 Blümel K., Tagliaferri F., Kuhl M. “Algorithm for calculating distance and sensor-object angle from raw data of ultra-low power, long-range ultrasonic time-of-flight range sensors.” Procedia CIRP, 118, pp. 1061–1065 2023
2 Blümel K., Kuhl M., Hölzel F.A., Kunze K. “A microcontroller-based multi-sensor system using ultrasonic range sensors and radar sensors for sensor data fusion: accuracy study and performance test.” Proceedings of SPIE, 12621, 1262119 2023
3 Blümel K., Kuhl M. “A Vibrotactile Assistance System for Factory Workers for Accident Detection and Prevention in the Logistics Sector.” Lecture Notes in Networks and Systems, 674 LNNS, pp. 62–71 2023
4 Allmacher C., Seiderer A., Klimant P., Kuhl M. “Synergy Analysis and verification of connected Cyber Physical Systems using virtual commissioning.” Procedia CIRP, 99, pp. 639–644 2021

Video

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