Developed Homie, an IoT-based home automation system that monitors and controls utilities including water pump automation, gas leak detection, temperature monitoring, and security alerts. Features custom PCB design in Proteus with mobile app integration for remote monitoring and control of smart home devices.
STM32 embedded systems project covering firmware, UART, GPIO, sensor integration, PCB layout, enclosure design, power analysis, and prototype cost evaluation.
Especialização em Robótica
Synthetic CAN/J1939 parser lab for 29-bit identifier decomposition, PGN logic and bench examples.
Developed an IoT smart mailbox system combining TM4C123 firmware, Raspberry Pi-based computer vision, and a web dashboard for real-time monitoring, remote lock control, and event detection.
Personal portfolio website showcasing my engineering projects, technical experience, leadership, and interests in embedded systems, machine learning, hardware–software integration, and healthcare technology.
Cyber-physical Romi autonomous vehicle integrating manual control, PID line following, ArUco road-sign detection, Raspberry Pi camera streaming, Redis/OpenCV drive-by-video, and real-time operator feedback.
An integrated IoT medication management system. Comprises a web app interface and an Arduino-powered smart pillbox that provides physical light and sound reminders, showcasing full-stack development.
Interactive RP2040 business-card PCB with NFC, a dual-colour LED grid, MicroPython gameplay, and minimax AI.
Sistema de inspeção visual de molas (DUAL) com Streamlit, OpenCV e TensorFlow.
MicroBlaze FPGA embedded system on Nexys DDR using Vivado/Vitis, AXI GPIO peripherals, UART, and C firmware for memory-mapped switch-to-LED hardware control.
Embedded C firmware for STM32 B-L475E-IOT01A that reads onboard temperature/humidity sensors and serves live environmental data through a lightweight Wi-Fi HTTP server.
Embedded systems and FPGA projects using Raspberry Pi, sensors, MQTT, SystemVerilog, Vivado, and Basys3 hardware.
Multi-product computer vision system for automated USB-A and USB-C connector inspection using Deep Learning, industrial traceability, and production-line integration.
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