INDIAN-INFRA-AI-INSIGHTS.STREAMLIT.APP

A Snowflake, Streamlit-powered AI application to analyze, predict, and improve India's infrastructure across diverse sectors using advanced AI techniques and data visualization.

https://github.com/mahanteshimath/AI_for_Good_SF

🚀 Features

Accident Severity Prediction
- AI-driven predictions to analyze accident probability and severity based on environmental, road, and vehicle conditions.
Road Accident Analysis
- Comprehensive analysis of road accidents (2019-2022) with trends, causes, and preventive recommendations.
Real-Time Air Quality Index (AQI)
- Displays real-time AQI data across Indian cities with advanced visualizations.
Petrol Demand Prediction
- Forecasts fuel demand trends to optimize resource allocation and infrastructure planning.
Civil Aviation Analysis
- Insights into passenger growth, operational efficiency, and market trends (1990-2019).
AI Civil Engineer
- An assistant specialized in leveraging AI for civil engineering projects.
Infrastructure Failure Analysis
- Identifies reasons for project failures and provides actionable recommendations.

🎯 Goals

Leverage AI and data to enhance infrastructure planning and maintenance.
Provide actionable insights for government, planners, and citizens.
Promote sustainable development through data-driven decisions.

📊 Data Sources

Snowflake Data Marketplace: Large-scale datasets on infrastructure and public utilities.
data.gov.in: Open government datasets.
Weather APIs: Real-time AQI data.
Custom Datasets: Tailored for specific analysis.

🛠️ Technologies

Frontend: Streamlit
Backend: Snowflake (for data storage, processing, and advanced analytics)
Visualization: Plotly, Matplotlib
AI Models: Machine Learning for predictions, accident analysis, and trend forecasting

🧩 Architecture

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Data Ingestion: Data collected from Snowflake, APIs, and custom uploads.
Processing: Data cleaning, validation, and embedding creation using Snowflake and Streamlit utilities.
Visualization: Dynamic dashboards with charts, heatmaps, and interactive visualizations.

4. User Interaction: Intuitive interface for entering inputs, viewing results, and exploring insights.

📁 Project Structure

├── .devcontainer
│   └── devcontainer.json
├── .streamlit
│   └── config.toml
├── Home.py
├── README.md
├── pages
│   ├── AI_Civil_Engineer.py
│   ├── Accident_Severity_Prediction_Using_AI.py
│   ├── Accidents_Analysis_Prevention_Using_AI.py
│   ├── Architecture.py
│   ├── Hypothesis.py
│   ├── Indian_Civil_Aviation.py
│   ├── Indian_Roads.py
│   ├── Indian_Trains.py
│   ├── Infra_Projects_Failure_Reasons.py
│   ├── Petrol_Need_prediction.py
│   ├── Realtime_AQI_Across_India.py
│   └── Snowflake_Powered_Accident_Analysis_bot.py

🔥 Unique Highlights

Accident Prediction: AI models predict accident severity and probability based on real-world inputs.
Interactive Features: Animated charts, heatmaps, and sentiment analysis for accident discussions.
Scalable: Built using Snowflake and Streamlit for handling large datasets with ease.

🌟 How to Use

Navigate through sections: Use the sidebar to access different features like accident prediction, AQI analysis, and more.
Enter Inputs: Provide required details for prediction or analysis (e.g., vehicle number, road conditions).
View Results: Explore insights, predictions, and recommendations through dynamic charts and tables.