Embedded Systems Engineering Student - Intern Candidate

Truong Hoang Nam

TECHNICAL INTERN

ï linkedin.com/in/namtruong05 § github.com/namtruonghoang1909

# ***.*************@*****.*** + Thu Duc, Ho Chi Minh City +84-902****** SUMMARY

Computer Engineering student specializing in Embedded Systems and Firmware Development, with hands- on experience developing real-time distributed systems. Strong in problem-solving, self-learning and team- work. Seeking a role to apply technical skills, gain hands-on experience, and contribute to embedded systems or related fields.

EDUCATION

Ho Chi Minh University of Technology - HCMUT Aug 2023 - May 2027 Bachelor of Computer Engineering

SKILLS

Languages & Frameworks: C/C++, Python, Bash scripting. OS: FreeRTOS (Task, Mutex, Queue, Event Groups), Embedded Linux (Buildroot), POSIX Threads. Boards: ESP32, STM32, QEMU Virtualization (ARM/AArch64). Protocols & Networks: UART, I2C, SPI, CAN, MQTT, HTTP/REST. Tools & Environment: PlatformIO, STM32CubeMX, CMake, GDB, Valgrind, Git, Unity (Unit Testing). Soft Skills: Strong English skills (IELTS 7.0), Technical Writing (LaTeX), presentation. PROJECTS

Elevator Safety Monitoring Unit - ESMU Dec 2025 - March 2026 Developed a distributed IoT monitoring device for real-time elevator Individual work health monitoring and fault detection. C, CMake

• Designed a dual-node architecture with an ESP32 gateway for connectivity and STM32F103 edge node for sensor processing over CAN bus.

• Engineered a multi-tasking FreeRTOS architecture, utilizing Queues and Semaphores for thread-safe data exchange.

• Designed a fault detection system for free-fall, impact, and vibration using MPU6050 with filtering and threshold-based algorithms.

• Integrated SIM A7680C failover for emergency alerts and MQTT telemetry for health monitoring.

• Engineered custom hardware abstraction layers and drivers for all integrated sensors and modules based on technical datasheets.

AIoT Smart Home System Feb 2026 - Present

Designed an AIoT smart home platform integrating gesture-based device control C, C++, Python and environmental forecasting. Team of 6

• Developing a hand-gesture control system using MediaPipe for real-time gesture recognition, enabling remote PWM-based fan speed control.

• Designed and deployed an Edge TinyML model that forecasts environmental conditions using Ten- sorFlow Lite Micro on ESP32

• Implemented MQTT-based communication for real-time data exchange between embedded devices and backend services, supporting both telemetry and remote control.

• Integrated REST APIs for interaction with backend and AI services, enabling seamless data flow between the web application and edge devices.

1

Contact this candidate