Projects

Resume projects with practical AI, vision, and embedded systems depth.

Each project keeps the resume source content at the center: description, stack, learning, future scope, architecture placeholder, and repository.

Disaster Insight Hub Assistant

Flask-based Retrieval-Augmented Generation experience that classifies crisis-related text, fetches safety playbooks, and drafts natural responses through Ollama Cloud.

Repository

Tech Stack

PythonReactTailwind CSSFastAPIMongoDBOllamaLangChain

Features

  • Multi-output Random Forest crisis detection
  • TF-IDF retrieval over a curated Excel knowledge base
  • Safety playbook retrieval and natural response drafting
  • Full-stack assistant experience for disaster management

Learning & Scope

Enhanced full-stack development, AI integration, and cloud deployment skills.

Predictive AI, IoT, GIS mapping, and smarter real-time disaster management.

Architecture placeholder for RAG flow, classifier, retrieval layer, and response engine.

Pothole Detection Assistant

AI-powered pothole detection system that identifies potholes from road images or video streams using computer vision and deep learning techniques.

Repository

Tech Stack

PythonYOLOOpenCVNumPy

Features

  • Road image and video stream detection
  • Real-time pothole identification
  • Intuitive monitoring interface
  • Maintenance prioritization support for road safety

Learning & Scope

Strengthened computer vision, deep learning, and real-time object detection skills.

GPS mapping, severity analysis, and smart road maintenance integration.

Architecture placeholder for camera input, YOLO inference, analysis, and reporting flow.

Smart Weather Monitoring System

Offline smart weather monitoring system using Arduino ESP8266 and environmental sensors to provide real-time temperature, humidity, and rainfall data for rural farmers without internet connectivity.

Repository

Tech Stack

Arduino ESP8266Embedded CDHT11 SensorRain SensorLDRLCD Display (I2C)

Features

  • Offline rural weather monitoring
  • Temperature, humidity, and rainfall sensing
  • Arduino ESP8266 sensor processing
  • LCD-based local data display

Learning & Scope

Learned embedded systems and real-time sensor data processing using Arduino ESP8266.

AI/ML model integration for predictive weather forecasting.

Architecture placeholder for sensors, ESP8266 processing, display, and forecasting extension.