🚦 Smart Traffic Violation Pattern Detector Dashboard v0.1.0

📝 Overview

This project is a Streamlit web application designed to analyze traffic violation data. It provides a user-friendly interface to explore, visualize, and gain insights from traffic violation datasets. Users can upload their own data, perform analysis, and view summaries and trends.

📘 Documentation: For a comprehensive understanding of the project, please refer to our detailed core documentation:

• 1. System Architecture (Basic): High-level overview, architecture diagrams, and directory structure.
• 2. Page Development Details: In-depth analysis of each page, purpose, and dependencies.
• 3. Visual Diagrams: Detailed Architecture, Data Flow, and Component Interaction diagrams.

🎯 Features

• Dataset Management:
  • Upload your own CSV datasets.
  • View and browse the loaded dataset.
• Numerical Analysis:
  • Get a quick overview of your dataset, including shape and sample rows.
  • View detailed information about each column, including data types and descriptive statistics.
• Data Visualization:
  • Generate various plots to visualize data distributions and relationships.
• Trend Analysis:
  • Analyze trends in the data over time.
• Map Visualization:
  • Visualize geographical data on an interactive map.
• Correlation Analysis:
  • Explore correlations between numerical columns with a heatmap.

🚀 How to Run

1. Clone the repository:

   git clone https://github.com/saidulalimallick04/smart-traffic-violation-pattern-detector-dashboard.git
   cd smart-traffic-violation-pattern-detector-dashboard

2. Choose your package manager:

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   🌟 Primary Method: Using uv (Recommended)

   1. Create and activate a virtual environment:

      # Create a virtual environment
      uv sync

   2. Run the application:

      uv run streamlit run app.py

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   🐢 Alternative Method: Using pip

   1. Create and activate a virtual environment:

      python -m venv .venv
      
      # Activate the virtual environment
      # On Windows (Command Prompt)
      .\.venv\Scripts\activate
      # On Windows (PowerShell)
      .\.venv\Scripts\Activate.ps1
      # On macOS/Linux
      source .venv/bin/activate

   2. Install dependencies:

      pip install .

   3. Run the application:

      streamlit run app.py

📂 Project Structure

.
├── .gitignore
├── .python-version
├── app.py
├── core
│   ├── __init__.py
│   ├── analysis_plot.py
│   ├── dashboard_plot.py
│   ├── dashboard_summary.py
│   ├── data_generator.py
│   ├── data_variables.py
│   ├── sidebar.py
│   ├── trend_plot.py
│   ├── utils.py
│   └── visualization_plot.py
├── dataset
│   └── Indian_Traffic_Violations.csv
├── generated_fake_traffic_datasets
│   └── 2025-11-24
│       ├── 01_traffic_dataset.csv
│       └── 02_traffic_dataset.csv
├── map_data
│   ├── 01_INDIA_STATES.geojson
│   └── 02_INDIA_STATES.geojson
├── uploded_file_others
│   └── (empty)
├── pages
│   ├── 01_Numerical_Analysis.py
│   ├── 02_Visualize_Data.py
│   ├── 03_Trend_Analysis.py
│   ├── 04_Map_Visualization.py
│   ├── 09_Upload_Dataset.py
│   └── 10_View_Dataset.py
├── pyproject.toml
├── requirements.txt                              # Project Dependencies
├── PROJECT_DOCUMENTATIONS
│   ├── PROJECT_BLUEPRINT_1-BASIC.md                  # System Architecture & Overview
│   ├── PROJECT_BLUEPRINT_2-PAGE_DEVELOPMENT_DETAILS.md # Detailed Page Analysis
│   ├── PROJECT_BLUEPRINT_3-VISUAL_DIAGRAMS.md        # Architecture & Data Flow Diagrams
├── README.md
├── uploded_file_relateds
└── uv.lock

📦 Dependencies

The main dependencies for this project are listed in the pyproject.toml file. They include:

• numpy>=2.3.5 - Numpy
• datetime - Python Standard Library
• pandas>=2.3.3 - Pandas
• seaborn>=0.13.2 - Seaborn
• streamlit>=1.51.0 - Streamlit
• streamlit-local-storage>=0.0.25 - Streamlit Local Storage
• folium>=0.16.0 - Folium
• streamlit-folium>=0.18.0 - Streamlit Folium
• faker>=38.2.0 - Faker

Recent Updates

• 2025-12-09:

  • Documentation & AI Integration: Saidul finalized the comprehensive project blueprint and integrated AI analysis tools (Claude/Gemini) for advanced debugging.
  • Agile Artifacts: Created detailed Product and Sprint backlogs to track team velocity.

• 2025-12-05:

  • Branding: Mrunalini unveiled the new "CollisionX India" platform identity, incorporating a custom logo and unified color theme across the dashboard.
  • Refactoring: Vijay G optimized the utility functions in core/utils.py to handle large datasets more efficiently.

• 2025-11-26:

  • Map Visualization: Saidul successfully integrated Open Source GeoJSON files to resolve region mismatch issues in the Map Module.
  • Trend Analysis: Rakshitha implemented the "Peak Hour Traffic" analysis to identify high-risk time windows.

• 2025-11-25:

  • Performance Tuning: Darsana and Saniya worked on optimizing the filter logic, reducing the dashboard load time by 40%.
  • Advanced Plots: Sanjana added the "Severity Heatmap" to visualize accident intensity by location.

• 2025-11-22:

  • Fake Data Engine: Saniya and Poojitha enhanced the data_generator.py to produce realistic synthetic violations for stress testing.
  • Bug Fixes: Anshu resolved a critical merge conflict that was affecting the deployment pipeline.

• 2025-11-20:

  • Numerical Analysis: Mrunalini deployed the "Numerical Analysis" page, adding descriptive statistics and data quality checks.
  • Error Handling: Saidul fixed the pyarrow.lib.ArrowInvalid serialization error in the dataframe viewer.
  • Data Validation: Saniya added strict type checking for the CSV loader to reject malformed files earlier in the pipeline.
  • Documentation: Rakshitha updated the inline docstrings for all new utility functions.

• 2025-11-18:

  • UI Polish: Ishwari and Harika refactored the HTML/CSS components to ensure a responsive design on mobile devices.
  • Page Routing: Poojitha streamlined the Sidebar navigation for better user experience.
  • Accessibility: Rakshitha audited the color contrast ratios of the charts to ensure they met WCAG standards.
  • Performance: Vijay G implemented memoization for the sidebar data loader to prevent reloading on every interaction.

• 2025-11-16:

  • Data Visualization: Sanjana and Ishwari launched the initial "Visualize Data" page with Bar and Pie charts for vehicle distribution.
  • HTML Debugging: Harika fixed table rendering issues with assistance from AI debugging tools.
  • Chart Styling: Darsana applied a custom color palette to the Matplotlib figures to match the platform theme.

• 2025-11-13:

  • Sidebar Integration: Poojitha finalized the multi-page sidebar structure, enabling seamless switching between 5 different modules.
  • Asset Management: Mrunalini organized the static assets (images, CSS) and established the project folder structure.

• 2025-11-09:

  • Data Upload Feature: Divija implemented the CSV file uploader with validation for required columns.
  • Data Cleaning: Vijay G wrote the utility scripts to clean null values and standardize date formats.
  • Unit Tests: Darsana added initial unit tests for the data loader to ensure file compatibility.

• 2025-11-04:

  • Git Workflow: Anshu established the Git structure and resolved initial merge conflicts for the team of 13.
  • Repo Initialization: Saidul set up the repository, virtual environment, and app.py skeleton.
  • Environment Config: Rakshitha created the pyproject.toml and requirements.txt to manage dependencies.

• 2025-11-01:

  • Project Kickoff: Team CollisionX India assembled. Saidul (Lead) defined the architecture and assigned initial modules to:
    • Development: Ishwari, Harika, Divija, Amith, Sanjana, Darsana, Poojitha, Saniya, Vijay, Rakshitha.
    • UI/UX: Mrunalini.
    • Version Control: Anshu.

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👥 Authors / Team CollisionX India

The dedicated team behind the Smart Traffic Violation Pattern Detector Dashboard.

Team Member	Role / Key Contribution
Saidul Ali Mallick	Team Lead & Lead Developer. Initialized Main Repo, handled Architecture, Documentation, and Map Visualization.
Anshu Gupta	Developer & Git Specialist. Managed Shared Repository, defined Branching Strategy, handled Merges, and assisted with Frontend integration.
Mrunalini P	Developer, UI/UX & Branding. Created "CollisionX India" platform identity, Logo, and Key Frontend Developer for core UI pages.
Ishwari Deshmukh	Frontend Developer & Analyst. Built visualization pages and handled Streamlit layout components.
Harika Sayani	Developer. Contributed to page structure, HTML representation, and About page.
Divija V	Developer, Analyst & UI/UX. Implemented Data Upload, Graphical Representations, Visualization Page UI, and file handling logic.
Amith Shaji George	Developer, Analyst & QA Tester. Solved complex backend issues and contributed to dashboard logic.
Sanjana Gowrishetty	Developer & Analyst. Contributed to visual representation and plotting logic.
Darsana R	Developer, Analyst & UI/UX. Contributed to plotting modules, Frontend UI components, and dashboard integration.
Poojitha Borra	Developer & Analyst. Assisted with page routing and debugging.
Saniya Mahek	Developer & Analyst. Worked on data validation and filters.
Vijay Gudla	Developer & Analyst. Contributed to backend utility functions.
Rakshitha P	Developer & QA Tester. Assisted with testing and documentation.
Mounika Pinnika	QA Tester. Validated data integrity and handled cross-browser testing.
Mounika Sunkari	QA Tester. Assisted in test case execution and product verification.

Acknowledgment: We leveraged AI tools (Claude & Gemini) primarily for complex debugging where Saidul & Anshu led the analysis to resolve deep technical issues.

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