Kerman Lopez de Calle, a researcher working for the Smart Information Systems Unit at the technology centre, has submitted his thesis entitled “On the use of context information for an improved application of data-based algorithms in condition monitoring”, whose main aim is to analyse the role played by context in terms of monitoring algorithms in the field of machine condition monitoring.
The main objective of this research work is to demonstrate the potential for improvement that techniques and methodologies related to prescriptive analytics can provide in industrial maintenance applications.
Context- and Template-Based Data Compression Approach to Improve Resource-Constrained IoT Systems Interoperability
In this thesis, we present a novel data compression approach for text-based data formats, namely Context- and Template-based Compression (CTC), which is specially designed taking into account the limitations of resource-constrained devices and networks.
Como resultado principal de esta tesis, se presenta una metodología para asistir el desarrollo de sistemas innovadores, heterogéneos y confiables. La metodología propuesta combina y adapta: modelos para el desarrollo de nuevo producto; aproximaciones para el desarrollo de sistemas confiables; enfoques para el desarrollo de sistemas complejos; y técnicas de control estadístico de procesos e indicadores clave de rendimiento.
This research work aims at supporting data analysts through the different KDD (Knowledge Discovery in Databases) phases towards the achievement of energy efficiency and thermal comfort in tertiary buildings.
This PhD study aims to improve the accuracy of MTs and also to develop knowledge for traceable coordinate measurement machine (CMM) measurements on MTs. The technology to run a dimensional measurement on an MT already exists but the knowledge to do traceable measurements is under research, as it is reported in this thesis.