Deep learning and Artificial Intelligence - ITCL

Deep learning and Artificial Intelligence

Deep learning and Artificial Intelligence

In this field, ITCL has been developing machine learning technologies, Big Data and Data Science, neural networks or artificial intelligence for more than ten years, and in the last three years of Blockchain, for the massive handling of data of heterogeneous origin. The objective is to enhance the value of large volumes of information from different environments, and facilitate their exploitation as structured information in an innovative business model driven by data or ‘data-powered’.

This line of research allows us to take on the development of knowledge and technologies that contribute to filling the gaps that may exist between the needs of end users and the possible existing enabling technologies. 

In a specific and non-exclusive way, we work in technological fields such as virtual and augmented reality, computer vision, automatic speech recognition, recognition of audio signals and mobility applications, industry (modelling systems, simulation and prediction of the behaviour of machines and manufacturing processes, with the development of virtual twins that allow their design and subsequent optimisation).

Technologies in which ITCL works:

  • Machine learning

  • Big Data

  • Data Science

  • Neural networks

  • Artificial Intelligence

  • Data powered

  • Blockchain

  • Virtual Reality

  • Augmented Reality

  • Computer Vision

  • Modelling

  • Simulation

  • Prediction of machine behaviour

  • Manufacturing Processes

  • Virtual cufflinks

Projects

Mindtooth – Wearable device to decode the human mind by means of neurometrics for a new concept of intelligent interaction with the environment.

Mindtooth will enable truly "intelligent" and "cooperative" interaction between human actors (e.g., car drivers, airplane pilots, factory workers) and the devices around them through the use of brain signals.

Duration: 2020 - 2022

NeuroCPS4 Maintenance – Neuromorphic Anomaly Detector

NeuroCPS4Maintenance is a project that aims to develop and demonstrate a neuromorphic edge anomaly detector that is robust against conceptual drift, alerts to faults early and provides fast, real-time response for predictive maintenance applications in high-demand industrial scenarios (industrial press). This anomaly detector will be based on deep learning algorithms (LSTM) and implemented on system on chips (SoC).

Duration: March 2021 - 2022

HOSMARTAI – Intelligent Hospital Development

The HosmartAI project will create a common open integration platform, with the necessary tools to facilitate and measure the benefits of integrating digital technologies (robotics and AI) into the healthcare system.

Several large-scale pilot projects will make it possible to evaluate the various improvements in several hospital environments:
Medical diagnosis, surgical interventions, disease prevention and treatment, rehabilitation support and long-term care.

Duration: 2021 - 2024

FitDrive – Control Device for Drivers

FitDrive is a project whose purpose is to minimize the risk of accidents through the use of a monitoring device for drivers. The goal of determining fitness to drive is to strike a balance between minimizing driving-related road safety risks to the individual, the community, maintaining the driver's lifestyle and their employment-related mobility independence.

Duration: 2021 - 2024

Sudoe Hospital 4.0 – Intelligent energy management in hospital buildings

Hospitals are buildings of continuous use, which have very specific air conditioning requirements in their different spaces and are conditioned to a climatological evolution characteristic of the Sudoe territory. Inefficient management or their inadequacy lead to incensive costs, avoidable emissions and inefficiency of public investment in their construction and maintenance.

Duration: October 2019 - March 2022

INUNDATIO – Automation of flood risk modeling in headwaters through Artificial Intelligence and BigData.

INUNDATIO ofrece un modelo de sistema de gestión de avenidas súbitas (flash floods) en cabeceras de cuenca basado en su caracterización hidromorfológica, la toma contínua de datos hidrometeorológicos (lluvia + caudal), la comparación con datos históricos, la simulación de escenarios de riesgo y el análisis de la vulnerabilidad para las vidas humanas y los elementos materiales.

Duración: Octubre 2019 - Abril 2022

Fandango – Advanced automotive component manufacturing through reliable and secure digital twins

Fandango is aimed at improving operational efficiency in the automotive components sector by acting on the visibility of information in the supply chain, maximizing product quality and optimizing maintenance processes. It will employ the use of digital twins to detect the occurrence of problems earlier and predict outcomes more accurately than pure simulation models.

Project duration: 2018 - 2022

Productio – Industrial improvement through enabling technologies

Research on various technologies, techniques, tools, methodologies and knowledge aimed at increasing the operational capacity of industrial processes (Overall Equipment Efficiency - OEE) within the framework of the connected industry. The project has enabled the adoption of productive and maintenance solutions in the connected industry by implementing digital security.

Duration: 2016-2020

tecnologias habilitadoras

Ciberfactory – Technology enablers in cyberphysical and virtual environments for the industry of the future

The Technological Enablers project deals with the industrial research of enabling technologies to increase the technological capacity of the ITCL, and its competitiveness in the technological sector that will facilitate us to bring the experiences closer to the regional industrial interests.

Duration: 2019 - 2020

Ciberfactory

ProefiAIRE – Development of tools for the control and improvement of the energy efficiency of vacuum and compressed air production systems.

The project has conducted research on the monitoring and intelligent control of the energy efficiency of vacuum and compressed air installations, key in the industrial sector to reduce inefficiencies in the use of this equipment.

Duration: 2018 - 2021

Ciber4gr0 – Cybersecurity in the agro-food industry

The objective of the Cyber4gr.0 project is to conduct a technical feasibility study to analyze the application of the Cybersecurity Seal in the field of Industry 4.0 in general and in the Agri-Food industry in particular, as well as the feasibility study of granting the Seal in digital mode using BlockChain technology to ensure its free consultation, as well as its inviolability and immutability.

Duration: 2018 - 2019

Inspector – Inspection and maintenance in the connected industry

The objective of the project is to investigate various technologies, techniques, tools, methodologies and knowledge aimed at automating and optimizing the management of inspection and maintenance within the framework of the connected industry. This project will facilitate the adoption of Inspection and Maintenance solutions with a high degree of automation, efficiency and competitiveness.

Duration: 2017 - 2021