Projects

Current Projects

  • Data 4.0: Challenges and Solutions

    The objective of this project is within the scope of Industry 4.0 and consists of proposing new solutions to problems that arise in the mass management of industrial series in three lines: Pre-processing, Visualization and Analysis.

    Data pre-processing: from RAW data to rich data: investigate and propose techniques and tools to cover the steps of cleaning, preparation and reduction of large volumes of raw data and develop a first level of data developed.

    Rich data visualization: compare different large viewing environments volumes of data in order to select the appropriate one that facilitates the capture of knowledge of the expert and thus allows to guide the task of generating useful information.

    Data Analysis: Generate useful information from complex data using complex analysis methods that combine descriptive, prescriptive and semantic data analysis techniques

Past Projects

  • 4V. Volumen, Velocity, Variety and Veracity in innovative data management

    The aim of the coordinated project was to develop innovative solutions that will face some challenges in data management in the Digital Society. It is characterized by the large volume of accessible data, quality and heterogeneous origin, whose integration can produce an added value that is still not being used.
    This objective is related to the 4 Vs that are characteristics of analysis and research in the environment called Big Data. Thus, to achieve the proposed objective, SPEED and VOLUME were considered in the production of data from the perspective of EFFICIENCY, both in the storage and in the query of large volumes of data and / or streams.
    of data. The VARIETY from the perspective of the SEMANTIC EXPLOITATION of the data both in mobile and fixed environments, in order to obtain added value information from the existing data and, finally, the VALIDITY from the perspective of the QUALITY analysis of the open data and its repair in the event that it is necessary.

  • SAMON: a Sleep Apnea Monitoring System:

    Patients suspected of suffering Sleep Apnea and Hipopnea Syndrome (SAHS) have to undergo sleep studies such as expensive polysomnographies to be diagnosed. Healthcare professionals are constantly looking for ways to improve the ease of diagnosis and comfort for this kind of patients as well as reducing both the number of sleep studies they need to undergo and the waiting times. Relating to this scenario, some research proposals and commercial products are appearing, but all of them record the physiological data of patients to portable devices and, in the morning, these data are transmitted to hospital computers
    where physicians analyze them by making use of specialized software. We are developing an alternative proposal that promotes not only a transmission of physiological data but also a real-time analysis of these data locally at a mobile device. This local analysis allows the detection of anomalous situations as soon as they are generated and so, offers the chance of reacting earlier.

  • AINGERU

    Development of an innovative tele-assistance system that overcomes current services limitations and offers new functionalities.

  • MOLEC

    Development of an innovative system to monitor patients with cardiac arrythmia that allows a continuous analysis of of hear signals (ECG) in real time on a local device.

  • OBSERVER (Ontology Based System Enhanced with Relationships for Vocabulary hEterogeneity Resolution)

    OBSERVER uses multiple pre-existing ontologies to access heterogeneous distributed and independently developed data repositories .The content of each data repository is described by one or more ontologies expressed using a system based on Description Logics. Each data repository is viewed at the level of the relevant semantic concepts. Information request to OBSERVER is specified as a DL expression based on concepts in a user domain ontology. OBSERVER uses ontological inferences to classify the query and determine relevant data repositories and translates the DL expressions to the local query languages of the data repositories. Mechanisms dealing with partial translations obtained by using synonym relationships and incremental enrichment of the answers by combining them are implemented. Moreover, it also considers the substitution of a term by combinations of hyponym and hypernym relationships which result in the change in the semantics of the query.