CARTIF Projects
REMODEC
Smart Planning and Comprehensive Implementation for the Rapid and Sustainable Reconstruction of Regions After Disasters
Description
REMODEC reserach, develop and validate an intelligent system for the planification and integral deployment of solutions destinated to a quick, sustainable and resilient reconstruction of territories after natural disasters. The project integrates modular construction, emergency paviments, autonomous water purification systems and energy generation, joint with digital technologies based on AI, predictive models, multiagent systems, generative design and digital twin. The solution allow coordinate resources, optimize logistics and support decision-making on complex scenarios, reducing time-response and improving the adaptation to different emergencies.
Objectives
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- Define technological requirements and a post-disaster territorial ontology that enables the characterization and integration of the information needed for REMODEC’s various technological solutions.
- Investigate intelligent multi-agent systems capable of dynamically coordinating available technological and logistical resources to respond effectively to post-disaster scenarios.
- Develop probabilistic predictive models for adaptive logistics planning, using techniques such as POMDP and Bayesian networks to manage uncertainty and adapt decisions in real time.
- Investigate hybrid AI algorithms and explainable artificial intelligence (XAI) techniques to optimize comprehensive logistics and provide transparent and justified recommendations to operational managers.
- Optimize the hydraulic design of capacitive deionization (CDI) cells using CFD simulation, seeking to maximize their water purification performance, homogenize flow, and minimize pressure drops, while maintaining the system’s compactness and portability.
Actions
- Definition of technological requirements and development of a post-disaster territorial ontology, providing a common information base for the integration and coordination of project solutions.
- Research and development of an intelligent core based on multi-agent systems (MAS-AI) to autonomously and coordinately manage resources, inventories, and logistical constraints in emergency scenarios.
- Development of probabilistic predictive models and hybrid optimization algorithms, combining POMDPs, Bayesian networks, metaheuristics, and deep learning techniques to adapt and optimize logistical planning under uncertainty.
- Development of explainable artificial intelligence (XAI) mechanisms and validation of the intelligent system, aimed at generating understandable and justified recommendations and verifying the robustness and operational effectiveness of the solution in dynamic and complex simulated scenarios.
- Hydraulic modeling and CFD simulation of CDI cells, analyzing geometric configurations, spacers, inlets and outlets, velocity profiles, dead zones, turbulence, pressure drops, and pressure distribution to optimize the portable water purification system.
Expected Results
- Post-disaster territorial ontology and set of technological requirements, designed to structure information and serve as the basis for integrating the various solutions developed in REMODEC.
- Intelligent coordination hub based on multi-agent systems, capable of dynamically managing the deployment of technological resources, inventories, and logistical constraints in post-disaster situations.
- Predictive models and logistics optimization algorithms under uncertainty, capable of adapting planning in real time using POMDPs, Bayesian networks, metaheuristics, and deep learning techniques.
- Intelligent decision support system with XAI capabilities, providing transparent and justified recommendations and experimentally validated in dynamic and complex simulated scenarios.
- Optimized hydraulic design of CDI cells and design recommendations obtained through CFD, aimed at achieving uniform flow, minimal pressure drop, high deionization efficiency, and a compact and portable system, contributing to the water purification prototype for post-disaster environments.
R&D Line
- Development of solutions based on AI for support on construction decision.
Partners
CDTI Science Missions and Innovation
MIG-20251141
Total Budget: 5,810,977€
CARTIF Budget: 325,000€
Duration: 01/01/2026 – 31/12/2029
Responsible
Roberto Medina Aparicio
Divison of Industrial and Digital Systems
Networking
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