Intelligent Sensor Systems

This group strives to develop intelligent sensor systems for biomedical applications, Structural Health Monitoring (SHM) and Predictive maintenance tasks. This is accomplished by combining heterogeneous technologies pertaining to the acoustic, Micro-Electro-Mechanical-Systems (MEMS), signal processing, embedded systems, and sensor network fields.  

In particular, embedded systems for acoustic and ultrasonic (US) inspections are investigated. Key requirements for easy and wide-range applicability of such SHM systems include high selectivity and accuracy in damage detection and localization, low hardware complexity and low power consumption for in-situ, real time operation, wireless communications to ease the deployment on large and complex structures. These features are not simultaneously available in present-days SHM systems as they represent cutting-edge challenges for state-of-the-art research. In this context, the group is working toward the development of a new generation of piezoelectric devices which enable imaging of large 2D areas through the differential output signal of a single sensor. Moreover, the group investigates time-frequency representations and intelligent data fusion techniques to enhance the inspection accuracy.

ERC Fields

  • PE7_2 - Electrical and electronic engineering: semiconductors, components, systems 
  • PE7_8 - Signal processing 
  • PE6_2 - Computer systems, parallel/distributed systems, sensor networks, embedded systems, cyber physical systems 

Scientific Coordinator: Prof. Luca De Marchi 

Faculty

Luca De Marchi

Associate Professor

PhD Students and Research Fellows

Antonio Carbone

Research fellow

Massimiliano Menghini

Research fellow

Teaching tutor

Masoud Mohammadgholiha

PhD Student

Research fellow

Lorenzo Mistral Peppi

Research fellow

Francesca Romano

Research fellow

Matteo Zauli

PhD Student

Research fellow

Teaching tutor

Federica Zonzini

PhD Student

Teaching tutor

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