SKANDHA G H

About

Electronics and Communication Engineering student with a CGPA of 8.43/10 and a strong interest in embedded systems, firmware development, and electronics R&D. Experienced with academic and project work involving Arduino, ESP32, MQTT, and embedded testing.

Experience

• Remote IoT Intern
  Emertxe Information Technologies
  Mar 2026 – Apr 2026

  Developed a Smart Factory IoT Monitoring System using Arduino, MQTT, and ThingsBoard. Simulated and tested the system using PICSimLab.

• Embedded Technology Trainee Engineer
  Ultismart Infotech LLP
  Feb 2026 – May 2026

  Gained experience in embedded board testing, bootloading, firmware-related tasks, and product validation. Undertook industry exposure at Syrma SGS Technology, Bengaluru, through the internship collaboration.

Education

• 2026 GE
  B.E. in Electronics and Communication Engineering

  Government Engineering College Hassan

  Electronics and Communication Engineering (ECE) · Dec 2022 – May 2026

  Electronics and Communication Engineering (ECE) · Dec 2022 – May 2026

Skills

Tools / apps / platforms

Projects

• Smart Glasses for Blind People – Project Mentor
  Arduino Nano

  Mentored junior students in developing Arduino Nano-based smart glasses to assist blind and visually impaired people with obstacle detection.

• Smart Waste Segregation Using Robotic Arm
  Arduino, moisture sensor, servo, Bluetooth, ESP32-CAM

  Built an Arduino-based waste segregation prototype using a moisture sensor, servo-driven arm, and Bluetooth control. Integrated an ESP32-CAM for image collection and motor/servo control for robotic arm movement.

• ESP32-Secured Bot Clock
  ESP32, RTC, Wi-Fi, Telegram Bot, I2C

  Developed an ESP32-based clock integrating an RTC, display, Wi-Fi, and Telegram Bot. Implemented local alarm/timer controls and remote interaction, with RTC timekeeping through I2C communication.

• ECG-Based Arrhythmia Classification
  Deep learning, ECG preprocessing, CNN-LSTM

  Developed a deep learning-based approach using ECG preprocessing and CNN-LSTM models to classify five cardiac rhythm classes. Achieved 99.53% training accuracy and 99.17% testing accuracy; evaluated sensitivity, precision, and F1-score.

Courses & certifications

• Embedded for Beginners · NIELIT Calicut · 2026

⚽ Extracurricular activities

• Project Expo

  21st Karnataka State Level ISTE Student Convention, Nov. 2025.

• Hobby Project event

  VYUHANTHIRA 2025, CIT Gubbi, Oct. 2025.

• IEEE Mini Project Symposium 2025

  ATME College of Engineering, Mysuru, Oct. 2025.