C++

Project Overview A smart security framework designed to perform object detection at the edge and centralize analytics. This system minimizes storage overhead by alerting the user only when actionable items (such as persons) are detected. Key Implementation Details Edge Capture: Programmed ESP32-Cam microcontrollers in C++ to capture and stream low-latency MJPEG video streams over a local Wi-Fi connection. Machine Learning Inference: Developed a Python processing backend using a quantized YOLOv5 neural network to analyze incoming video feeds frame-by-frame. Instant Notifications: Integrated the system with the Telegram Bot API to dispatch instant photo captures and telemetry alerts directly to the user’s mobile device. 🔗 GitHub Repository

Project Overview A unified driver interface engineered to handle complex audio operations on microcontrollers. This project simplifies digital-to-analog audio conversion pipelines on the VS1053 codec. Key Implementation Details Streaming & File Playback: Unified web radio network streaming (HTTP protocols) with physical SD card storage media streams (over SPI). Asynchronous Processing: Designed an asynchronous non-blocking scheduling pipeline in C++ to prevent audio stuttering during parallel processor tasks. Hardware Integration: Implemented APIs to interact directly with internal registers, permitting control over custom equalizers, physical treble/bass, and volume. 🔗 GitHub Repository