- TOP
- Download ◯◯ Materials
Raspberry Pi × Edge AI Utilization Guide
Tips for Implementing Inference and Sensor Integration in Embedded Systems
Important
Once the Edge firmware is updated to the Console REST API V2-compatible version, it cannot be reverted to the Console REST API V1-compatible version.
Overview
This document introduces use cases of edge AI on compact devices such as Raspberry Pi and Jetson Nano.
It explains the workflow from control using Python/C++, implementation with OpenCV and TensorFlow Lite, to sensor data acquisition and cloud transmission, accompanied by architecture diagrams and code samples.
For those with the following technical challenges and needs
- Want to perform object detection and classification on edge devices with low latency
- Want to collect data from cameras and various sensors on Raspberry Pi and process it in real time
- Want to combine hardware control using Python or Shell scripts with AI processing
What you will get by downloading
- Implementation examples of image processing and real-time inference using OpenCV and TensorFlow Lite
- Architecture diagrams and code snippets for sensor → device → cloud integration