UJI researcher Sergi Trilles obtains a Leonardo grant from the BBVA Foundation to create a platform that will link the internet of things and artificial intelligence



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## UJI researcher Sergi Trilles obtains a Leonardo grant from the BBVA Foundation to create a platform that will link the internet of things and artificial intelligence

25/07/2024 |
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* [![ beca-fbbva-sergio-trilles _37A2006](/com/investigacio/arxiu/noticies/2024/7/beca-fbbva-sergio-trilles/_37A2006.jpg)](#)

Sergi Trilles Oliver, an established R3 researcher in the GEOTEC group, has won one of the BBVA Foundation's Leonardo Grants for Researchers and Cultural Creators in the Computer Science and Data Science category, worth 40,000 euros, to carry out the project "CoAIoT: Platform for the use of artificial intelligence in the Internet of Things through the sharing of local micro-models between communities of devices".

Leonardo grants are a highly competitive call with a success rate of 4%. In the 2024 call, 58 grants were awarded out of a total of 1,423 applications and are targeted at researchers aged between 30 and 45. The aim is to support the work of researchers and cultural workers who are in the midst of a highly innovative scientific, technological or cultural career.

Sergi Trilles Oliver is a researcher in the GEOTEC group (Geospatial Technologies and Geographic Information Systems), part of the Institute for New Imaging Technologies (INIT). He holds a PhD in Geospatial Information Integration from the UJI since 2015 and has worked as a researcher at the Digital Earth and Reference Data Unit of the Joint Research Centre (JRC) of the European Commission in Italy, among others.

The project selected by the BBVA Foundation aims to combine the Internet of Things (IoT) and artificial intelligence (AI), which, according to the researcher, "should be the perfect symbiosis" because the IoT (the collective network of devices connected by a technology that facilitates communication between them and also with the cloud) "can produce the amount of data needed to feed the machine learning of AI".

In addition, the latest IoT devices enable edge computing, which offers remarkable performance for running small AI models. However, there are several challenges, such as the instability of the data generated by these devices, the lack of data at the time of deployment, or the impossibility of creating individual AI models for each device.

The project aims to generate communities of IoT devices based on their context (location and time), similarity and purpose, with the aim of sharing pre-trained micro-models between these communities, thus facilitating the applicability of AI from the moment of device deployment. The ultimate goal is to make these devices more intelligent and able to make instantaneous decisions at the point of use, without the need to connect to distant server clouds.

To this end, a platform will be designed and validated to facilitate this connection, which could be applied in numerous business models, such as smart cities, industry 4.0 or healthcare, among others.

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