KM

Keerthana M

ECE student · Embedded Systems Intern

Bangalore, Karnataka, India

@keerthana_m

0 followers

About

ECE student with hands-on experience in Embedded C, firmware development, microcontrollers, and real-time embedded systems. Interested in low-level firmware, debugging, and embedded systems development.

Experience

  • Embedded Systems Intern
    Emertxe Information Technologies
    Dec 2025 – Jan 2026

Education

  • B.Tech in Electronics and Communication Engineering
    Electronics and Communication Engineering · 2023 – 2027
  • Class XII (PCMB)
    MES PU College
    PCMB · 2019 – 2021

Skills

  • C <3 months
  • Python <3 months
  • Embedded C <3 months
  • ESP32 <3 months
  • Verilog <3 months
  • I2C <3 months
  • UART <3 months
  • LTSpice <3 months
  • STM32 <3 months
  • Embedded Firmware Development <3 months
  • Real-time Systems <3 months
  • SPI <3 months
  • Multimeter usage <3 months
  • Microcontrollers <3 months
  • Bare-Metal Programming <3 months
  • Fsms <3 months
  • Pwm <3 months
  • Gpio <3 months
  • CAN <3 months
  • Oscilloscope <3 months
  • ADC <3 months

Tools / apps / platforms

  • Git <3 months
  • GitHub <3 months
  • KiCad <3 months
  • The MathWorks MATLAB <3 months

Projects

  • Smart AI-Powered Connected EV Assistant
    ESP32, CAN, Embedded C

    Developed a dual-ESP32 embedded system integrating CAN, GPS, and battery/temperature/vibration sensors for real-time vehicle monitoring. Implemented battery health and remaining-range estimation with charging recommendations based on battery and charging parameters.

  • Depth Estimation using Stereo Camera
    ESP32, OpenCV, PyTorch

    Developed a real-time stereo vision pipeline using dual ESP32-CAM streams, achieving 5–10 FPS for detection, matching, and depth computation. Integrated Mask R-CNN and Hungarian algorithm-based matching for object correspondence and depth estimation up to ~3 m.

  • Smart Wheelchair
    STM32, Embedded systems, IoT

    Developed an STM32-based wheelchair with Bluetooth control and joystick-based motor actuation, achieving <100 ms response time. Implemented ultrasonic obstacle detection up to 2 m with real-time alerts, integrating GPIO, UART, timers, motor control, and sensors.

Courses & certifications

  • QNX Realtime Programming · QNX

📚 Publications

  • Noise-Aware Domino Logic Gates using Differential Domino Technique

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