Divyank Kushwaha

I've built real-time machine learning and IoT systems for safety, accessibility, and human activity monitoring.

During my NPTEL internship at SWAN Lab, IIT Kharagpur, I processed WiFi CSI data to achieve 95%+ recognition accuracy and built Python dashboards tracking 5+ performance KPIs. I also applied clean, modular coding practices while collaborating across research and engineering teams.

At MMMUT, I developed an Arduino and ESP32-based manhole monitoring system that improved response time to unsafe conditions by 15%, integrated REST APIs, and enabled real-time cloud alerts. I also integrated seven sensors and GSM-based anomaly reporting.

My projects include an eye-gaze controlled wheelchair using deep learning, computer vision, and IoT for hands-free mobility, plus a human activity recognition system with 95%+ accuracy and real-time WebSocket streaming. I'm pursuing a B.Tech in Electronics and Communication with a minor in Data Science.