Prabir Rout
@prabirrout
Embedded firmware developer building production IoT and edge-vision systems with ESP32.
What I'm looking for
I’m a CS undergraduate focused on AI & ML, and I build production-ready IoT firmware for ESP32/Arduino. In my part-time role at the IoT Lab (KIIT), I integrated sensor drivers (I2C/SPI/UART) with Wi‑Fi and MQTT back-ends to cut manual testing time by ~30%.
I’ve designed BLE GATT profiles for mobile-to-device communication and optimised MTU payloads to improve low-latency, reliable transfers in resource-constrained environments. I also build maintainable firmware by documenting hardware interfaces and firmware APIs and working effectively with Git in cross-functional teams.
On the edge AI side, I deployed YOLOv8 + OpenCV inference on ESP32-CAM to deliver real-time classification (~5 FPS) with no cloud dependency for inference. I enjoy turning ML pipelines into robust embedded execution, including low-latency event handling and efficient data flows.
My projects reflect that same focus: BikeNav uses a custom MTU-optimised BLE packet protocol to drive a distraction-minimised OLED HUD, while SmartWaste runs on-device YOLOv8 and relays results over MQTT to actuate servo-controlled bin lids <200 ms after classification. I’ve also been a top hackathon finalist (including Smart India Hackathon) and a multi-year science representative, which strengthened how I ship under real constraints.
Experience
Work history, roles, and key accomplishments
Embedded Software Developer
IoT Lab, Kiit Bhubaneswar
Jan 2025 - Present (1 year 5 months)
Built production-ready firmware for ESP32/Arduino by integrating I2C/SPI/UART sensor drivers with Wi-Fi back-ends over MQTT, reducing manual testing cycle time by ~30%. Designed BLE GATT profiles optimized with MTU payloads for low-latency transfer and deployed an on-device YOLOv8 + OpenCV pipeline on ESP32-CAM for real-time classification at ~5 FPS without cloud inference.
Education
Degrees, certifications, and relevant coursework
KIIT University
Bachelor of Technology (B.Tech), Computer Science & Engineering (AI & ML)
2024 -
Grade: CGPA 9.05 / 10.0
Activities and societies: Relevant coursework: Embedded Systems, Data Structures & Algorithms, Operating Systems, OOP.
B.Tech in Computer Science & Engineering (AI & ML) at KIIT University, Bhubaneswar (2024–2028), with CGPA 9.05/10.0. Coursework includes Embedded Systems, Data Structures & Algorithms, Operating Systems, and OOP.
Availability
Location
Authorized to work in
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Skills
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