Firmware Engineer | ECE Graduate

SUCHETA KRISHNA NAIK

0
Sensors Tested
8.55
CGPA
0
Protocols Mastered
2+
Years Building
Get In Touch View Projects
ESP32-S3 UART TX LIVE ●
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01

About

ECE graduate who turns circuit-level ideas into working firmware. Currently developing real-time embedded systems at SmartBuild Automation using ESP32-S3, FreeRTOS, and a full suite of wireless protocols.

I don't just write code — I debug UART traces at 3AM, calibrate industrial sensors to µA precision, and chase down RF interference with an oscilloscope. From MQTT device control to multimodal medical imaging with MATLAB — I build things that work in the real world.

@suchetanaik00@gmail.com
📞+91 7338176152
🌐suchetanaik.online
inin/sucheta-k-naik
📍Bengaluru, Karnataka, India
Live — FreeRTOS Task Scheduler Simulation

FreeRTOS uses a preemptive scheduler where higher-priority tasks preempt lower ones. Each colored bar represents a concurrent task (UART_TX, WIFI_HANDLER, BLE_SCAN, SENSOR_READ) running on the ESP32-S3's dual cores.

02

Experience

SmartBuild Automation Pvt Ltd
Firmware Developer Intern
Oct 2025 — Present
  • Developed embedded firmware for ESP32-S3-WROOM-1 using C and FreeRTOS, implementing UART, TCP/IP, UDP, Wi-Fi, and BLE communication protocols.
  • Integrated and configured RF communication modules, optimizing real-time performance, latency, reliability, and fault tolerance.
  • Performed UART and RF protocol debugging using Docklight, including RF module configuration, command validation, and communication issue resolution.
  • Designed and validated TCP/IP and MQTT-based device control communication and used tools for protocol debugging, packet verification, and issue diagnosis.
ESP32-S3 FreeRTOS UART TCP/IP MQTT BLE UDP Docklight
Pepperl+Fuchs India Pvt Ltd
Quality Assurance & Automation Testing Intern
Feb — May 2025
  • Performed QA testing on 50+ sensor batches weekly using multimeters, encoder kits, and other tools, ensuring compliance with standards.
  • Collaborated with engineering teams across India to improve sensor testing workflows, applying insights from technical workshops.
  • Configured and calibrated sensors using PACTware and Sonpro; verified IP settings with Docklight for client-specific requirements.
  • Documented test results for 200+ sensors monthly, reducing quality issues by 20% and improving data-driven validation.
PACTware Sonpro Docklight Sensor Cal. 200+ Sensors/mo
03

Skills

▸ TCP/IP Stack — Hover Each Layer
L7
Application MQTT · HTTP · CoAP
MQTT broker/client for IoT device control. Publish/subscribe model over TCP for lightweight telemetry. Used in SmartBuild for remote device management.
L6
Presentation JSON · TLS
Data serialization and encryption. JSON payloads for sensor data; TLS for secure OTA updates over Wi-Fi on ESP32-S3.
L5
Session TCP Sessions
Managing persistent TCP connections between ESP32 and server. Handles reconnection logic under FreeRTOS task supervision.
L4
Transport TCP · UDP
TCP for reliable device command delivery; UDP for low-latency real-time sensor streaming. Debugged using Hercules and Docklight.
L3
Network IPv4 · Wi-Fi
IP routing over ESP32 Wi-Fi stack. Configured static/dynamic IP for sensor modules per client specifications at Pepperl+Fuchs.
L2
Data Link BLE · RF · 802.11
BLE 5.0 on ESP32-S3 for proximity control. RF module configuration via AT commands. Docklight for frame-level debugging.
L1
Physical UART · SPI · I2C
Dual-UART firmware on ESP32-S3 for RGB lighting + touch boards. SPI/I2C for sensor interfacing. Logic analyzer verification.
Embedded & Firmware
ESP32 / FreeRTOS95%
C Programming90%
UART / SPI / I2C92%
MQTT / TCP/IP / BLE88%
Testing & Diagnostics
Docklight / PACTware90%
Sensor Calibration85%
Data Science & Tools
Python / NumPy / Pandas78%
MATLAB80%
04

Projects

P — 02
MedWatch System
Real-time health monitoring tracking SpO₂ and heart rate using Arduino Uno + MAX30100. ESP8266 for wireless data transmission. Embedded IoT design with live LCD display.
Arduino MAX30100 ESP8266 IoT
P — 03
Multimodal Brain
Tumor Detection
MATLAB-based image fusion combining MRI, CT, PET, and SPECT scans for Glioblastoma & Meningioma diagnosis. Advanced image processing pipeline improving diagnostic accuracy by 25%.
MATLAB Image Fusion MRI+CT+PET +25% Accuracy
05

Education & Certs

BE
Electronics & Communication Engineering
Shree Devi Institute of Technology · Mangaluru
2021 — 2025
8.55 CGPA
12
Class XII — PCMB
Siddartha Pre University College · Bhatkal
2021
82.83%
Certifications
2025
Embedded Systems for Beginners
NIELIT Calicut · Online
2024
CS50 — Introduction to Programming with Python
Harvard University
2022
Internet of Things and Its Applications
IQMETRICS Solutions Pvt Ltd