Telecom Engineer

A comprehensive mobile health solution that integrates wearable sensors with cloud analytics for real-time patient monitoring and predictive healthcare.

• Flutter mobile app with real-time vital sign visualization
• AWS backend with Lambda, SageMaker, and DynamoDB
• Edge-cloud switching algorithm for optimal processing
• ML prediction models for early health anomaly detection
• MQTT protocol for efficient IoT communication

• Flutter
• AWS
• Python
• TensorFlow
• MQTT
• Edge Computing

An innovative presentation control system that combines hand gesture recognition with voice commands for seamless slide navigation.

• MediaPipe hand tracking for precise gesture recognition
• Python-based voice command processing
• Integration with PowerPoint and Keynote
• Customizable gesture mapping
• Low-latency performance for real-time control

• Python
• OpenCV
• MediaPipe
• SpeechRecognition
• PyAutoGUI

Draw in the air with your index finger using a standard webcam. The app includes a left-side thickness slider, RGB color buttons, an eraser, a background toggle (black/white), a configurable grid, and one-key saving.

• Real-time index-finger tracking (MediaPipe Hands)
• Left-side thickness slider (hover with index to adjust)
• RGB color buttons (Red / Green / Blue) + Eraser mode
• Background toggle (black/white) without destroying strokes
• Grid overlay with adjustable spacing (G- / G+)
• Open-palm clear gesture + “Clear All” button
• Motion-based drawing guard (background subtraction)
• On-screen color indicator with current HEX
• Quick save with s (drawing + preview) and quit with q

• Python
• OpenCV
• NumPy
• MediaPipe

A real-time facial emotion recognition system designed for smart museums. It uses a CNN model deployed on Raspberry Pi to detect visitor emotions, helping curators understand emotional engagement with exhibits.

• Real-time facial emotion detection using CNN
• Raspberry Pi 5 for on-device image processing
• Flutter app with integrated TFLite model for local inference
• Node-RED flow for emotion data transmission
• Laravel dashboard for emotion trends and reports

• Python
• TensorFlow/TFLite
• Raspberry Pi
• Flutter
• Node-RED
• Laravel

Mini wireless sensing project using Libelium/Waspmote + XBee 802.15.4 and Cities PRO (BME/BME280). Sender/Receiver exchange ASCII payloads (TEMP/HUM/PRES), and the receiver computes medians/averages over batches of 10 packets.

• IEEE 802.15.4 link (PAN 0x1234, CH 0x0F), optional AES
• ASCII payload with tags: TEMP/HUM/PRES
• Medians & averages computed per 10 received frames
• Waspmote + Cities PRO (BME/BME280) on socket A

• IEEE 802.15.4
• XBee
• Waspmote
• BME280
• C/C++