PROTEA-M: MARCO MULTIMODAL PARA LA COMUNICACIÓN INCLUSIVA EN SITUACIONES DE INUNDACIÓN
Resumen
Los sistemas de alerta temprana constituyen la principal herramienta para la notificación y orientación de la población en situaciones de emergencia; sin embargo, aún utilizan mensajes estandarizados que no consideran diferencias cognitivas y comunicativas. Esta limitación afecta directamente a las personas con Trastorno del Espectro Autista, que requieren formas estructuradas y predecibles de organización de la información para la comprensión y la toma de decisiones en contextos de riesgo. Este trabajo presenta el framework PROTEA-M (Program for Readiness and Organized Training in Emergencies for Autistic Individuals - Multimodal), un modelo predictivo-generativo multimodal orientado a la producción de contenidos inclusivos para la preparación en escenarios de inundación. El modelo estima el perfil comunicativo y el plan de intervención y, a partir de esta estimación, genera Historias Sociales personalizadas. El módulo predictivo utiliza un ensemble de Extreme Learning Machines con fusión de evidencias y calibración probabilística, presentando un rendimiento superior a los baselines, con una precisión de 0.6923 y ROC-AUC de 0.9782, además de una mejor calidad probabilística. El módulo generativo produce narrativas multimodales mediante modelos de lenguaje, traduciendo variables clínicas en secuencias visuales y textuales organizadas. PROTEA-M contribuye a la evolución de los sistemas de alerta al incorporar personalización comunicativa y accesibilidad cognitiva.
Biografía del autor/a
Desarrollador móvil Flutter, especializado en diseño responsivo e integración de aplicaciones mediante API REST. Licenciado en Ingeniería de Computación por la Universidade Paulista y Magíster en Ingeniería de Computación por la Universidad de Pernambuco. Certificado como Professional Scrum Master por Scrum.org y como Flutter Developer por AndroidATC.
Graduado en Ingeniería Eléctrica por la Universidad Federal de Pernambuco (1978), Magíster en Ingeniería Eléctrica por la Universidad Federal de Pernambuco (1995) y Doctor en Ciencias de la Computación por el Centro de Informática de la Universidad Federal de Pernambuco (2007). Profesor Adjunto II de la Universidad Católica de Pernambuco y de la Escuela Politécnica de la Universidad de Pernambuco.
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