Success Stories
Highlighted projects of inLab FIB
The project “Developement of automation technology” is an initiative led by Supertronic with the participation of TECNIO inLab FIB center, focused on the automation of the selection and creation process of plastic envelopes for printed circuit boards (PCB’s).
The aim of the i-MovE project is to generate a collaborative data space that facilitates access to urban mobility information to all actors in the transport sector. This space will contain different types of data with different spatial and temporal aggregation frames.
The company Friselva, together with the Alimentaria Guissona Corporation (bonÀrea) and with the participation of the inLab FIB from UPC as a technology center, is working on the Hydroless operational group project.
The inLab FIB participates in a innovative project to develop an interactive assistant based in Artificial Intelligence (AI), designed to help solve quality issues.
This project aims to implement Industry 4.0-based technologies to make communications, data collection and supervision of unconnected machinery within a medical/ hospital environment.
In today’s digital age, mobile applications have become an integral part of our daily lives, but they have also increased the risks of cybersecurity. Companies face the challenge of protecting their applications and user data in an environment of constantly evolving threats.
The goal of this project is to develop a technological tool to measure, analyze and reduce the environmental impact within the industrial environment.
The inLab FIB participates in the project for the creation of a Communication Coach for executives and companies together with the communication professionals of the company Commly.
The inLab FIB participates in an innovative project for the development of an interactive assistant based on Artificial Intelligence (AI), designed to facilitate the creation of extensive documents. This system will guide the user step by step in the elaboration of texts, ensuring coherence and precision.
This project seeks to develop a machine learning model to identify risk situations before starting climbing with self-insurer, helping the staff of the center to detect dangers automatically and precisely.
SEAT has contacted inLab FIB and LaCàN to raise the possibility of developing a joint project to scale the use of ARCO and the ePGD library, currently validated for simple models, to solve NVH parametric problems with a realistic car geometry.
InLab FIB collaborates with Nubem sytems helping in the analysis and research of possible protection and detection tools and techniques that they can incorporate into their suite of cybersecurity services, as well as the evaluation of current services.