Sensors and intelligent systems integration

The integration of sensors, both physical and biochemical, microsystems (MEMs, NEMs) and signal processing, recognition and learning systems using artificial intelligence and neuromorphic computing techniques, offers great expectations in the  digital transition field and in applications in areas such as the environment, the automotive industry, robotics and home automation, surveillance, health and agriculture.

Furthermore, the use of multisensory signal processing systems (combining vision, sound, chemical, mechanical sensing, etc.) requires complex sensory fusion techniques, generally adapted to each circumstance, using hardware learning techniques that automatically adapt to the physical imperfections of the systems, while extracting and learning more abstract high-level representations.

The aim of this area is to create synergies between groups working in the different fields of sensors, microsystems and signal processing, which are likely to generate many projects with a clear industrial orientation.