LLM assistant for IoT Platform
This thesis explores a novel approach to this problem by leveraging advances in Large Language Models (LLMs) as an intelligent orchestration and configuration layer. The core deliverable is a program that accepts a structured or free-form user description of an intended IoT solution (for example: ta...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10459.1/468817 |
| Acceso en línea: | https://hdl.handle.net/10459.1/468817 http://hdl.handle.net/10459.1/468817 |
| Access Level: | acceso abierto |
| Palabra clave: | LLM IA Cloud Platform Data Docke |
| Sumario: | This thesis explores a novel approach to this problem by leveraging advances in Large Language Models (LLMs) as an intelligent orchestration and configuration layer. The core deliverable is a program that accepts a structured or free-form user description of an intended IoT solution (for example: target devices, data flows, latency and security constraints, analytics needs) and automatically generates the necessary configuration, infrastructure orchestration, and deployment actions to instantiate a customized IoT platform. The system combines LLM-based requirement interpretation with deterministic infrastructure tooling (infrastructure as code, container orchestration, device provisioning scripts, and CI/CD pipelines), applying policy templates and security best practices where appropriate. The result is an end-to-end path from natural language intent to a functioning, observable IoT deployment. |
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