Tata Innoverse Solver Hunt8

Tata Innoverse SolverHunt 8 Submission. Built a realtime face mask detection and social distancing detector.

AI & Machine LearningJupyter NotebookMIT

Abstract

Tata Innoverse Solver Hunt8 is an open-source AI & Machine Learning project. Tata Innoverse SolverHunt 8 Submission. Built a realtime face mask detection and social distancing detector. It is built using Jupyter Notebook, Keras. Key capabilities include: live video surveillance to fight against covid-19 spread; The project can be integrated with embedded systems for application in airports, railway stations, offices, schools, and public places to ensure that public safety guidelines are followed; Real time face mask detection and for social distancing tracking the crowd movement across the day time. The complete source code is publicly available on GitHub under the MIT License, making it a useful reference for students building an AI & Machine Learning mini project or final-year project.

1. Introduction

Tata Innoverse SolverHunt 8 Submission. Built a realtime face mask detection and social distancing detector.

2. Objective

Tata Innoverse SolverHunt 8 Submission. Built a realtime face mask detection and social distancing detector.

This project demonstrates how Jupyter Notebook, Keras can be applied to a real-world AI & Machine Learning problem.

3. Key Features / Modules

  • live video surveillance to fight against covid-19 spread
  • The project can be integrated with embedded systems for application in airports, railway stations, offices, schools, and public places to ensure that public safety guidelines are followed.
  • Real time face mask detection and for social distancing tracking the crowd movement across the day time.
  • Hot-spot area can be monitored by security forces from central station.
  • If AI based solution used by authority then there will be less chance get infected security forces.

4. Technology Stack

Jupyter NotebookKeras

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

  • Python 3.8 or later with Jupyter Notebook / JupyterLab (or Google Colab)
  • pip for dependencies
  • Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/hritik5102/Tata_Innoverse_SolverHunt8.git
cd Tata_Innoverse_SolverHunt8

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

  • Deploy the model as a web app with Streamlit, Flask or FastAPI
  • Compare against an additional model and report the metric difference
  • Add explainability (SHAP / Grad-CAM)

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

  1. What dataset does the project use and how was it pre-processed?
  2. Which algorithm / model architecture is used and why was it chosen over alternatives?
  3. How are training and testing data split, and how is overfitting avoided?
  4. Which evaluation metrics (accuracy, precision, recall, F1) are reported and what do they mean here?
  5. How would you deploy this model for real users?

9. Source Code & License

This project is developed by hritik5102 and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.

View Source on GitHubDownload ZIP

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