1. Data and analysis
Capture, processing, structuring, and exploitation of technical data from sensors, embedded systems, experimental logs, or digital sources.
This area includes:
- data acquisition and logging
- cleaning and dataset preparation
- exploratory analysis
- pattern and behavior detection
- technical visualization
- variable monitoring and tracking
2. Applied AI
Application of artificial intelligence techniques to technical problems, information flows, and engineering process support.
Depending on the project, this may include:
- data classification and interpretation
- automation of technical tasks
- assistance systems
- computer vision
- decision support models
- AI-based tools for experimental or production environments
3. Sensors and electronics
Design and integration of solutions based on sensors, data acquisition, communication, and electronic platforms for prototypes or experimental systems.
This line may include:
- instrumentation
- telemetry
- microcontrollers and embedded systems
- signal conditioning and reading
- communication interfaces
- integration with software and visualization
4. Control & prototyping
Development of systems where software, electronics, and physical behavior combine to validate ideas, build prototypes, and explore real-world applications.
This area includes:
- software-hardware integration
- automation
- basic or advanced control depending on the application
- test benches and experimental systems
- functional prototypes
- behavior validation
5. Applications
The Lab's technologies and workflows can be applied to different contexts, depending on the project type:
- embedded systems
- monitoring and instrumentation
- automation
- telemetry
- system behavior analysis
- data-based technical tools
- vehicle and motorsport applications
- experimental platforms and prototypes