Sai Sathvik

Adaptable and quick to grasp new concepts, with a dedication to efficient information retention. Demonstrates a history of excellence in various endeavors and a commitment to fostering growth and development in both individual and team settings.

Certified from ranksheet in Microsoft Word,HTML.
Certified from COURSERA in Python Data Structures.
Certified by Suven Technology for Java Script internship
Certified in MS PowerPoint 2007 by Ranksheet.
Attended Undergraduate & Masters Asia Virtual Experience Program.
Winning Team - Smart India Hackathon, 2020.
Microsoft Learn Student Ambassador.

Containerization of   ATTENDANCE MANAGEMENT SYSTEM:

The Attendance Management System, developed using Python, leverages facial recognition technology to automate and streamline attendance tracking in educational institutions. By containerizing the system with Docker, we ensured consistent and scalable performance across various environments. The application is deployed on Azure, utilizing Azure Kubernetes Service (AKS) to orchestrate and manage processing. This setup allows the system to efficiently handle large volumes of facial recognition data, with Kubernetes' auto-scaling capabilities dynamically adjusting resources as needed. A continuous integration and continuous deployment (CI/CD) pipeline, implemented with Jenkins, facilitates seamless updates and enhancements, ensuring that the latest features are integrated without disrupting service. Data storage is managed with Azure Blob Storage, while Azure Monitor provides ongoing performance tracking and alerts for any anomalies. Security measures, including encryption and access controls, are enforced to protect sensitive data and ensure compliance with institutional policies. This robust architecture ensures that the Attendance Management System operates efficiently, with high availability, addressing the limitations of previous manual systems.

ATTENDANCE MANAGEMENT SYSTEM USING FACIAL RECOGNITION:

The main purpose of this project is to create a face recognition-based attending observance system for institution to reinforce and upgrade this attendance system into more efficient and effective as compared to before. The previous system encompasses a lot of ambiguity that caused inaccurate and inefficient of attendance taking. Several issues arise once the authority is unable to enforce the regulation that exist within the old system.

ONLINE VOTING SYSTEM USING FACE RECOGNITION:

The main idea of this system is to create an Online Voting System that will eliminate the deception of manual voting systems and prior attempts to use cameras for facial recognition in online voting. Voters can only access the system after they are recognized and verified with the database of enlisted voters. For this system PYQT5, OpenCV is used for creating the browser and for face recognition.