Nickson Kipruto Rop@nickson_k_rop347

EmergencyCore is an advanced disaster management system designed to help emergency responders by providing real-time disaster analysis, weather predictions, and damage assessments. Key Features: Disaster Report Analysis: Users input disaster reports with urgency levels. The system analyzes the report using Grok AI to classify the disaster, assess severity, and provide safety recommendations. Weather Forecasting: Users can get weather predictions for any location, including risk assessments and safety tips based on weather conditions. Damage Assessment: Users upload images showing disaster damage. The system processes the image to assess the extent of the damage and offers initial feedback for further action. Aid Recommendation System: The app predicts the type of aid required based on factors like deaths, disaster duration, and cost, using a trained Random Forest model. User Interface: Built with Gradio, the app features an intuitive interface for easy reporting, weather requests, and damage image uploads. Technologies Used: Python: Main programming language for backend. Grok AI: Analyzes disaster reports and generates insights. Gradio: Creates the interactive interface for user input and displaying results. Scikit-learn: Used for training machine learning models, such as the Random Forest model for aid recommendations. Pandas: Manages and processes disaster data for machine learning. How It Works: Disaster Report Analysis: The user inputs a report, which is processed by Grok to classify the disaster and suggest necessary actions. Weather Forecasting: The app provides location-based weather forecasts with risk assessments. Damage Assessment: Users upload images of the damage, and the system evaluates them, suggesting follow-up actions.