Robust modeling for information acquisition in biophysical and critical scenarios
The era of information and Big Data is an environment where multiple devices, always connected, generate huge volumes of information (paradigm of the Internet of Things). This paradigm is present in different areas: the Smart Cities, sport tracking, lifestyle, or health. The goal of this thesis is t...
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| Tipo de recurso: | tesis doctoral |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | español |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/17169 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/17169 |
| Access Level: | acceso abierto |
| Palabra clave: | 519.87:004 004.891 004:61 Robust modeling era of information Big Data the Internet of Things wearable devices biophysical and critical scenario Modelado robusto era de la información Internet de las Cosas dispositivos wearable entornos biofísicos y críticos Sistemas expertos Hardware Software Bioinformática 3304.16 Diseño Lógico |
| Sumario: | The era of information and Big Data is an environment where multiple devices, always connected, generate huge volumes of information (paradigm of the Internet of Things). This paradigm is present in different areas: the Smart Cities, sport tracking, lifestyle, or health. The goal of this thesis is the development and implementation of a Robust predictive modeling methodology using low cost wearable devices in biophysical and critical scenarios. In this manuscript we present a multilevel architecture that covers from the on-node data processing, up to the data management in Data Centers. The methodology applies energy aware optimization techniques at each level of the network. And the decision system makes use of data from different sources leading to expert decision system... |
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