AI on Embedded Platforms using Raspberry Pi
Duration – 5 days-Workshop
Objectives
AI & Embedded Systems Workshop Outcomes
- Understand AI concepts tailored for embedded systems
- Interface sensors and cameras with Raspberry Pi
- Train and deploy ML models using TensorFlow Lite
- Build real-time AI applications for automation and computer vision
Tools & Platforms
AI & Embedded Systems Tools and Platforms
- Hardware: Raspberry Pi 4, DHT11, LDR, MCP3008, Pi Camera, LEDs
- Software: Raspberry Pi OS, Python, TensorFlow Lite, OpenCV, Matplotlib
- Languages: Python (with libraries for ML, vision, and GPIO control)
Pre-requisites
Prerequisites for AI & Embedded Systems Workshop
- Basic Python programming
- Fundamentals of machine learning
- Familiarity with electronic components (GPIO, sensors)
Take away
AI & Embedded Systems Workshop Outcomes
- Complete knowledge of deploying AI on Raspberry Pi
- Build end-to-end sensor-based and vision-based AI systems
- Hands-on experience in real-time AI inference and automation
- Final project integrating sensors and computer vision
Day 2: Sensor Interfacing and Data Acquisition
Theory:
- Interfacing digital and analog sensors
- Working with ADC (MCP3008) on Raspberry Pi
- Structured data logging and file formats
- Fundamentals of Exploratory Data Analysis (EDA)
- Preprocessing techniques for AI readiness
Hands-On:
- Connect and read data from DHT11 (temperature & humidity)
- Use MCP3008 with LDR to capture analog light data
- Automate sensor data logging with timestamps
- Save sensor readings to CSV and visualize using matplotlib
