Projects
Selected work in disaster guidance, applied machine learning, and offline IoT monitoring.
Disaster Insight Hub Assistant
An AI-powered disaster guidance application that turns crisis reports into location-aware, context-driven responses.
Selected Technologies
PythonFlaskRandom ForestTF-IDFspaCyDocker
Project Highlights
- Classifies crisis reports across seven categories with a Random Forest model trained on 2,345 labelled records.
- Uses TF-IDF retrieval over a curated knowledge base to surface relevant guidance.
- Extracts locations with spaCy and combines them with cloud LLM responses through REST APIs.
- Publicly deployed as a Flask application.
Smart Weather Monitoring System
An offline IoT weather monitor for rural farming environments where dependable internet access is not guaranteed.
Selected Technologies
ESP8266DHT11Embedded CLCD
Project Highlights
- Measures real-time temperature and humidity with an ESP8266 and DHT11 sensor.
- Refreshes readings every two seconds on a local LCD interface.
- Works without an internet dependency for practical field use.