šŸŒ Internet of Things

āœ… Internet of Things (IoT) and Edge Computing

Throughout my professional experience, I have undertaken various projects involving the setup and integration of miniature computing boards and the deployment of lightweight Computer Vision and Deep Learning models for efficient and real-time data processing. I have listed some of them below.

Key Explorations:

  1. Raspberry Pi + Arduino Uno + DHT11 Temperature Sensor Setup:

    • Configured a Raspberry Pi and Arduino Uno combination with a DHT11 temperature sensor to collect temperature and humidity data.

    • Developed a Python wrapper using ctypes for the WiringPi library to ensure seamless integration with the Python project.

  2. Raspberry Pi + Intel Neural Compute Stick 2 (NCS2) for Lightweight Computer Vision:

    • Integrated the Intel Neural Compute Stick 2 (NCS2)* with a Raspberry Pi to enable efficient and accelerated execution of lightweight Computer Vision models.

    • Utilized the NCS2 for running Single Shot Detection (SSD) models, enabling real-time object detection capabilities.

      *Please note that Intel has discontinued this product line.

  3. Setting up NVIDIA Jetson NX for Deep Learning Inference:

    • Learned to set up the Jetson board.

    • Explored and implemented various Deep Learning models for tasks like object detection, image classification, and semantic segmentation on Jetson.

  4. MLPerf Benchmarking on Jetson:

    • Configured MLPerf, a widely used benchmark suite for Deep Learning performance, on the Jetson platform.

    • Benchmarked custom Deep Learning models on Jetson to evaluate their efficiency and power consumption as part of hardware benchmarking.

These projects have provided invaluable hands-on experience in building and optimizing IoT and Edge Computing systems, empowering me with the knowledge and skills to design innovative solutions for real-world applications.