Forest Ranger: A Distributed Edge-AI Acoustic Sensor Network Architecture for Real-Time Detection of Illegal Deforestation Activity
Open project manuscript / April 2026 / Vellore Institute of Technology
computer science / software engineering / applied ML
Integrated M.Tech CSE (Data Science) at VIT Vellore. I build backend systems, data products and applied ML tools, with a bias toward software that survives real workflows.
Recent work includes Delhivery, video intelligence, edge AI, API security and personal knowledge tooling. I work comfortably across Python, FastAPI, TypeScript, SQL and Docker.
Video intelligence: detection, tracking, event rules and evidence workflows.
Agricultural price analysis using weather, geography and market structure.
Software development internship across rider-facing UI, backend/data flows and testing.
ESP32 acoustic sensing node that runs a quantised CNN locally to detect chainsaw activity and send compact alerts.
Bookmark and content-preservation system with search, annotations, link-health checks and archived copies.
Identity-verification middleware combining ECDSA challenge-response with Isolation Forest behavioural anomaly detection.
Video-security software that connects detection and tracking with rules, evidence capture, camera health and operator response.
FastAPI, REST, PostgreSQL, Redis, Docker and testing.
Anomaly detection, detection/tracking and edge inference.
Python, R, pandas, geospatial analysis and visualisation.
Git, CI, Playwright, documentation and small automation.
Open project manuscript / April 2026 / Vellore Institute of Technology
Inputs, state, constraints and failure cases first.
Small utilities where manual handling keeps recurring.
Commands, tests and notes that make work easy to resume.
Use the stack that keeps the problem clear.