PRESTO: high-PeRformancE Social-media crowdsensing acceleraTiOn

Welcome to PRESTO

This module is aimed at providing the underlying computing support for achieving real-time execution of our “Social Sensing as a Service” framework. As part of this goal, it is also necessary to provide efficient computing support for all the off-line processing tasks (e.g., DNN training) with the least amount of computing resources (e.g., memory capacity and processing elements) within the shortest possible time frame.


Research Team

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José Luis Abellán Miguel

(Module Coordinator)

Universidad Católica de Murcia

jlabellan@ucam.edu

https://orcid.org/0000-0003-3550-720X

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Baldomero Imbernón Tudela

Universidad Católica de Murcia

bimbernon@ucam.edu

https://orcid.org/0000-0002-2758-8364

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Antonio Llanes Castro

Universidad Católica de Murcia

allanes@ucam.edu

https://orcid.org/0000-0002-9802-4240

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José Carlos Periñán Pascual

Universitat Politècnica de València

jopepas3@upv.es

https://orcid.org/0000-0002-6483-4712

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Andrés Muñoz Ortega

Universidad de Cádiz

andres.munoz@uca.es

https://orcid.org/0000-0002-8491-4592



Acknowledgement

Agencia Estatal de Investigación

PRESTO is part of the research project "Smart multi-modal crowdsensing-based system as a service oriented to the prediction of social problems (ALLEGRO)", grant PID2020-112827GB-I00 funded by MCIN/AEI/ 10.13039/501100011033.

Contact Us

For further information, contact José Luis Abellán Miguel: jlabellan@ucam.edu