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This project aims to co-design, develop and validate a proof of concept of a conversational assistant based on generative AI, designed to offer psychological first aid in traumatic situations and natural disasters.
The project aims to complement current fraud‑prevention systems with an internal model capable of analysing transactional behaviour and member profiles, detecting anomalous patterns that may indicate suspicious operations. This new approach, based on internal data and advanced analysis and modelling techniques, seeks to significantly reduce fraud risk and strengthen trust in digital processes.
The project aims to explore the potential of computer vision techniques and artificial intelligence to automatically identify players' limbs, opening up new possibilities for analysis and monitoring in the field of sports.
AIDA is a project that aims to contribute to improving the operational efficiency based on the demand of the Aerobús service, for transport from the center of Barcelona to El Prat airport, with the use of innovative solutions based on AI and data.
In this session, CIDAI, in collaboration with 3Cat, presented the results and knowledge acquired during the execution of one of the High Impact Projects where multimodal generative AI tools have been used.
This solution offers an answer to the difficulty of managing PDF documents and other dense text files in unstructured formats, and will allow for more agile and accurate querying of large data sets.
A project to predict the number of calls received by SEM-061 regarding medical emergencies is crucial to improve resource management, optimize waiting times and guarantee immediate and quality care. Being able to anticipate moments of greatest demand will allow SEM to have a support tool to assess the distribution of resources in a more efficient way.
The project aims to harness advanced deep learning techniques to dynamically generate visual representations which encapsulate the key elements of news stories.
This project worked on two very different use cases within the agricultural sector: expanding knowledge in the application of antibiotics in livestock farms and a collaboration with the Center for Swine Studies to develop artificial intelligence and computer vision algorithms for life cycle monitoring.
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