Morocco Shield AI 🛡️

National Strategic Resilience & Decision Support System (February 2026 Crisis)

Lead Engineer: Taha Chaabi
Institution: École Centrale Casablanca
Event: Gemini Hackathon 2026
Status: MVP Operational | SDK 2026 Certified

---

📌 Executive Summary

Morocco Shield AI is a sophisticated command-and-control dashboard designed to navigate the Water-Energy-Food Nexus crisis during the climatic disruptions of February 2026 in Morocco. By correlating unstructured maritime logistics data with real-time agricultural vision analysis, the system provides a centralized intelligence hub for national resilience.

🌊 The Strategic Context (February 2026)

Morocco is currently facing a dual systemic failure that requires immediate AI intervention:

1. The Energy Crisis: Exceptional 5.8m swells at the Jorf Lasfar petroleum terminal have halted all ship-to-shore unloading. With Casablanca reporting zero diesel stock, the national logistics grid is at a standstill.
2. The Agricultural Crisis: Massive floods in the Loukkos and Gharb regions threaten high-value berry exports. The lack of diesel fuel prevents the operation of heavy-duty drainage pumps, leading to imminent crop death (anoxia).

🚀 Key Modules

1. Energy & Logistics Correlation Engine

• Predictive Risk Modeling: Gemini 1.5/2.0 analyzes maritime reports and local news to predict systemic fuel outages with a 95%+ probability.
• Strategic Triage: The engine generates actionable advice for the "Office des Changes" and transport authorities to prioritize fuel for time-sensitive perishables.

2. Multimodal Agri-Vision Sentinel

• Automated Damage Assessment: Uses Computer Vision to identify crop types (blueberries, strawberries, sugar beets) and estimate water-logging severity from drone or field imagery.
• Nexus Correlation: The AI specifically analyzes the "Double-Crisis" impact: determining how much crop loss is directly attributable to the fuel shortage preventing water evacuation.

3. Engineering Resilience Index ($I_{Res}$)

We have integrated a custom mathematical model to quantify national stability: $$I_{Res} = \frac{Fuel_{Available}}{Delay_{Logistics} + Flood_{Severity}}$$ This index allows the government to prioritize zones where high fuel stocks can mitigate high flood intensity.

🛠️ Technical Architecture

• LLM Core: Google Gemini (gemini-flash-latest) via the official Google GenAI SDK 2026.
• Framework: Streamlit for high-performance dashboard visualization.
• Data Processing: Multimodal handling using PIL (Python Imaging Library) for vision-to-text reasoning.
• Security: Environment-based API key management using python-dotenv.

⚙️ Installation & Deployment

1. Clone the Repository:

   git clone [https://github.com/YourUsername/MoroccoShieldAI.git](https://github.com/YourUsername/MoroccoShieldAI.git)
   cd MoroccoShieldAI

2. Install Dependencies:

   pip install -r requirements.txt

3. Configure Environment: Create a .env file in the root directory:

   GEMINI_API_KEY=your_secured_google_api_key
   

4. Launch Dashboard:

   streamlit run app.py

🎓 Academic Background

This project was developed by Taha Chaabi, a 2nd-year engineering student at École Centrale Casablanca. It leverages advanced concepts in Data Science, Complex System Architecture, and Climate Resilience to solve real-world logistical bottlenecks in the Moroccan economy.

---

Developed for the Gemini Hackathon 2026. Data used reflects the simulated climatic conditions of the February 2026 Morocco crisis.