IIITDM Kurnool CSE'27 | Ex-ISRO Intern | Ex-SDE Intern @ Ninternet | Contributor Hacktoberfest, GSSoC'24

leetcode

github

Kousthub J V  • Peerlist

This project, Automated Security Surveillance System, revolutionizes traditional security gate management by leveraging modern technologies such as face recognition and number plate scanning to decrease the manual work at the security gates of institutions. Face Recognition: This employs facial recognition algorithms to accurately identify individuals approaching the gate. Number Plate Scanning: The system captures images of vehicle number plates as they approach the gate. It records and stores vehicle information, enabling efficient monitoring and management of vehicles entering the security gate. Automated Data Logging: It automatically logs details of recognized individuals and vehicle plates along with the date, time, owner details and vehicle model into an organized Excel sheet automatically, eliminating the need for manual data entry. This feature ensures accurate record-keeping and facilitates easy retrieval of access history for security analysis and auditing purposes.

Computer Vision-Based Security Automation Sys

Architected and deployed a distributed full-stack collaborative ecosystem engineered for community-driven task orchestration and granular contribution provenance. Key technical implementations include: Role based access control(RBAC): Engineered a robust Role-Based Access Control (RBAC) framework to enforce the principle of least privilege across diverse user segments. Real-time Event Architecture: Leveraged WebSocket protocols and asynchronous message queuing to power low-latency in-app notifications and automated SMTP-based triggers. Workflow Engine: Developed a multi-tenant task execution layer supporting atomic group assignments, peer-review validation pipelines, and state-machine transitions. Data Analytics & Observability: Synthesized raw telemetry into comprehensive OLAP dashboards, featuring high-cardinality performance metrics and platform-wide monitoring for system health. Gamification Logic: Integrated a scalable scoring engine utilizing persistent leaderboards and performance-tracking algorithms to optimize user engagement and retention.

Loomio - Community task management platform

Built a machine learning–driven system to analyze and track users' emotional states from text-based inputs (e.g., journal entries or social media–like posts). Used Natural Language Processing (NLP) for multi-label emotion classification to detect emotions like joy, sadness, anger, and anxiety. Applied clustering algorithms to group users by emotional patterns and trends over time.

Mental Health Monitoring & Emotion Tracking S

A productivity-focused web extension designed to enhance user experience on YouTube by filtering out unwanted content based on customizable preferences. The tool helps users stay focused by hiding distracting elements like shorts, trending tabs, comments, and suggested videos, allowing for a cleaner and more intentional viewing experience. Built with JavaScript, HTML, and CSS, and available on the Mozilla Add-ons