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that reproduces, in a web environment, the visualisation and annotation interfaces defined in the project; • Ingestion, cleaning and storage pipelines (image, depth, metadata) with continuous integration testing
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web frameworks, REST/GraphQL APIs, automated testing). • Continuous integration and continuous delivery (CI/CD) in a cloud environment. • Functional validation and performance of the prototype in a
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for the development of the prototype should be entirely synthetic. For this purpose, generative artificial intelligence tools (5)(GenAI) should be used to create users with different profiles and relevant datasets
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and functional requirements of the system, analysis of data sources and characteristics, definition of performance metrics and criteria for comparison between approaches. 3) Initial prototype
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modules, for the agent management tools and for the conversation generation process. 3) Prototype: Development of an initial prototype of the multi-agent system architecture, including the preliminary
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architecture design • Collaboration in the requirements survey and system architecture design. • Definition of metrics and selection of tools (training frameworks, vector databases, APIs). 3) Prototype
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functional and non-functional requirements for the models to be developed. 3) Prototype: Development of prototypes for race simulation models and strategy suggestion algorithms. Initial testing with simulated
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of different security mechanisms, including guardrails, to filter malicious content and detect prompt injections, and testing on a functional prototype (e.g., through attack simulations in a red teaming logic
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of videos/images already collected in a real environment at the Hospital da Misericórdia da Mealhada and which will be made available; definition of accuracy and latency metrics. 3) Implementation and