TPGIT Migrant worker Registration and Tracking System

Abstract

Migrant workers form a significant part of Tamil Nadu’s labour force, yet they continue to face challenges such as lack of official identification, language barriers, fragmented job information, and limited access to welfare support. Current labour management practices rely heavily on manual processes, leading to inaccurate records, delayed verification, and poor visibility of workforce distribution. To overcome these gaps, this project introduces an intelligent Migrant Worker Registration and Support Platform that digitally manages worker information, employment details, and welfare accessibility. The system enables fast and inclusive registration through a multilingual interface and generates a unique Migrant ID (MID) for each worker. QR-based identity verification allows employers and authorities to authenticate worker profiles quickly and securely. To analyze workforce concentration across Tamil Nadu, the OPTICS (Ordering Points To Identify the Clustering Structure) clustering algorithm is applied to location data, enabling the system to identify high-density migrant zones and emerging labour clusters in real time. The platform also supports document uploads, employer reporting, and role-based profile access to improve reliability and accountability. In addition, the system provides workforce trend analytics, helping policymakers forecast labour demands more accurately. A notification module ensures that workers receive timely updates on job opportunities and welfare schemes. These features collectively enhance transparency and enable proactive planning for migrant resource management. By combining digital identification, intelligent clustering, and centralized workforce mapping, the proposed system enhances transparency, strengthens labour governance, and ensures timely support for migrant workers across the state.

Introduction

Migrant workers are individuals who move within a country or across borders in search of employment opportunities. They contribute significantly to sectors such as agriculture, construction, domestic work, and services but often face challenges including low wages, exploitation, poor working conditions, and limited legal protection.

The existing migrant worker management systems in India are fragmented and inefficient. State labour portals operate independently without a unified national framework, making cross-state tracking difficult. While Aadhaar provides identity verification, it does not contain employment-related information. Employment exchanges have limited effectiveness, NGO initiatives are localized, and employer-managed registration systems lack standardization and transparency. These limitations hinder effective workforce management and policy planning.

To address these issues, the proposed TN Migrant Connect Web Application is a centralized digital platform designed to manage, monitor, and verify migrant workers across Tamil Nadu. The system provides multilingual registration, secure worker identification through QR-based Migrant IDs (MID), document validation, employer verification, and workplace mapping. By integrating these features, the platform aims to improve transparency, accountability, and efficiency in labour management.

The system enables migrant workers to register easily through a mobile-friendly interface in multiple languages. Each registered worker receives a unique Migrant ID and QR code, allowing quick and secure identity verification by employers and government authorities. The platform also supports secure document upload and validation to ensure authenticity and facilitate transparent recruitment processes.

A key feature of the proposed system is the use of OPTICS clustering and geo-spatial analysis to map worker locations, identify labour clusters, and analyze migration patterns. This helps authorities make informed decisions regarding workforce planning, resource allocation, and welfare program implementation. Real-time notifications keep workers informed about job opportunities, verification updates, and government welfare schemes, while support services provide legal assistance and guidance in multiple languages.

The system supports three main user groups:

• Authorities: Monitor workforce distribution, analyze migration trends, and plan labour policies.
• Workers: Register, access employment opportunities, receive welfare information, and manage their profiles.
• Employers: Verify worker identities, manage employment records, and improve workforce accountability.

The development environment includes hardware such as an Intel i5 processor, 8 GB RAM, and stable internet connectivity. The software stack consists of Windows 10/11, PHP or Python, MySQL database, React.js for the frontend, and supporting technologies such as Google Maps API, email services, and SMS gateways.

The major modules of the system include:

1. TN Migrant Connect Web App – Centralized platform for migrant worker management.
2. User Management – Role-based access for authorities, workers, and employers.
3. Migrant Registration – Multilingual worker registration and profile creation.
4. Unique ID & QR Code Generation – Secure identification and verification.
5. Document Management – Upload and validation of worker documents.
6. Employer Verification – Worker authentication and employment tracking.
7. Workplace Mapping – Labour cluster identification using OPTICS clustering.
8. Notification & Support – Real-time updates, welfare information, and legal assistance.

Conclusion

In conclusion, this project delivers a comprehensive digital solution for managing migrant workers in Tamil Nadu through multilingual registration, MID generation, QR-based verification, and secure document validation. It improves transparency, workforce tracking, and accountability with features like employer verification and workplace mapping using OPTICS clustering for data-driven decision-making. The system benefits authorities, employers, and workers by enabling efficient management, easy verification, and better access to welfare services. Built with reliable technologies, it ensures scalability and usability, while future enhancements can further expand its capabilities and reach.

References

[1] React.js 17.0 or higher – https://reactjs.org [2] HTML – https://developer.mozilla.org/en-US/docs/Web/HTML [3] CSS – https://developer.mozilla.org/en-US/docs/Web/CSS [4] MySQL 5.7 – https://dev.mysql.com/doc/refman/5.7/en/ [5] Python – https://www.python.org [6] PHP 7.4 or higher – https://www.php.net/releases/7_4_0.php [7] WampServer – https://www.wampserver.com/en/ [8] XAMPP – https://www.apachefriends.org/index.html [9] Google Maps API – https://developers.google.com/maps/documentation [10] \"Learning React: Modern Patterns for Developing React Apps\" by Alex Banks and Eve Porcello – A comprehensive guide to building dynamic web apps using React.js 17.0 and beyond. [11] \"HTML and CSS: Design and Build Websites\" by Jon Duckett – An accessible and visually rich book for mastering HTML and CSS for responsive web design. [12] \"Learning MySQL: Get a Handle on Your Data\" by Seyed M.M. Tahaghoghi and Hugh Williams – An in-depth book on MySQL 5.7 database design, queries, and optimization. [13] \"Fluent Python: Clear, Concise, and Effective Programming\" by Luciano Ramalho – A modern Python reference, ideal for projects using Python 3.7 or higher. [14] \"PHP and MySQL Web Development\" by Luke Welling and Laura Thomson – A definitive book for PHP 7.4+ and MySQL integration in web applications. [15] \"Mastering WAMP: A Complete Guide to Windows, Apache, MySQL, and PHP\" by Akash Singh – A practical guide to setting up and managing WAMP-based environments. [16] \"Getting Started with Google Maps API\" by Scott Davis – A quick-start resource for integrating mapping and geolocation services into web platform

Copyright

Copyright © 2026 B. Vigneshwaran, Dr. J. Sundaravanan, M. Mohammed Riyaz, S. Kalidasan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.