AI-generated code is nothing new. But how can AI coding tools contribute when a product must address national standards, flight controller protocols, embedded hardware, and testing on real devices?

In this livestream, we will use the open-source AmovRemoteID project as a case study to demonstrate how developers can use Claude Code and Codex to turn the remote identification requirements of GB 46750-2025 into a practical software solution, step by step, and validate it on ESP32-S3 hardware. The session covers the complete development process, from understanding requirements to hardware validation.

Through this livestream, we aim to answer a practical engineering question: How should AI coding tools be integrated into the development workflow for an embedded product?

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Livestream Time: Wednesday, September 23, 19:00–21:00

Livestream Topic:

Open-Source UAV RID Module Project—AI-Assisted Product Development with Claude Code/Codex

01

Where Does This Livestream Begin?

Understanding Real-World Challenges Through National Standards

RID plays an important role in communicating UAV identification information during operation. Built on the ESP32-S3, the case-study project encodes remote identification data packets according to GB 46750-2025 and transmits the information via WiFi broadcasts. It also integrates data from a PX4 flight controller and a web-based configuration interface.

The challenges in this type of project are not confined to any single block of code. Developers first need to establish where fields 001 through 021 come from, which data is supplied by the flight controller, which data requires user configuration, how the data is encapsulated, and how it is ultimately transmitted over WiFi. The livestream will begin with these specific questions, helping the AI tools and developers build a shared understanding of the project goals, existing code, and features still to be implemented.

Four Stages of Development, Explained Step by Step

Stage 1: Understand the Project

We will first ask the AI to read the project documentation and existing code, then have the developer correct key information. The goal is to clarify the features to be implemented, the capabilities already available in the repository, and the gaps that still need to be filled, establishing a reliable foundation for the design work that follows.

Stage 2: Design the Solution

Once the requirements are clear, the livestream will demonstrate how to translate national standard requirements into a software architecture and module boundaries. This stage will also explain which tasks can benefit from AI-assisted analysis and which interfaces, data sources, and hardware constraints must be confirmed by the developer.

Stage 3: Implement the Solution

Next, we will work with the actual code. AI will help read the code, break down requirements, support design, modify the implementation, diagnose issues, and organize tests, while the developer continuously checks the direction and results. Viewers will see how a vague request such as “help me write code” can be turned into actionable, verifiable engineering tasks.

Stage 4: Validate and Test

Once the code is complete, the project must return to real devices and real data. The livestream will focus on whether tests are repeatable, the process is observable, and the results meet acceptance criteria. It will also include a live demonstration of RID operation and functionality.

02

Livestream Highlights

A Real Open-Source Project from Start to Finish

The livestream uses the open-source AmovRemoteID project as its case study, focusing on the ESP32-S3, GB 46750-2025, the PX4 flight controller, and WiFi broadcasting.

Rather than sample code detached from an engineering environment, viewers will see a real project with an existing codebase, hardware interfaces, and testing requirements. The AI must understand the existing repository and carry out analysis and development within the project’s constraints.

From National Standards to a Software Solution 

Starting with the remote identification requirements of GB 46750-2025, the livestream will examine the sources, configuration methods, and encoding process for fields 001 through 021.

The session will explain, step by step, how the standard’s field requirements become software requirements, how flight controller data and user configuration are combined, and how the resulting data is encapsulated and broadcast over WiFi.

The Complete AI-Assisted Development Workflow

This livestream will go beyond showing the final code. It will demonstrate how Claude Code and Codex contribute to understanding the project, breaking down requirements, designing the solution, modifying code, diagnosing issues, and organizing tests.

The hands-on process will also show how developers provide effective context to AI, review generated results, and retain control over key decisions that require their judgment.

Key Technologies Behind the RID Module

Focusing on the practical implementation of the RID module, the livestream will cover:

Encoding remote identification data packets for GB 46750-2025;

Organizing and encapsulating fields 001 through 021;

Dual-path WiFi Vendor IE broadcasting;

Handling OUI FA:0B:BC and types 0xF0 and 0x0D;

Integrating PX4 flight controller and MAVLink data;

The web-based configuration interface and on-site debugging.

Validation on Real Hardware

Completing the code is only one part of the development process. During the livestream, we will also run the software on ESP32-S3 hardware, check whether the data is correct and the broadcasts work as expected, verify that the tests can be reproduced, and demonstrate the RID module’s operation and functionality live.

Viewers will see the full journey from a requirement, through standards analysis, software implementation, and hardware testing, to a verifiable engineering result.

03

Build Your Own RID Module After the Livestream

After the livestream, you can try building an open-source ESP32-based RID module from scratch to meet the remote identification broadcasting needs of a self-built UAV.

Following the development workflow demonstrated in the livestream, developers can use their own hardware and flight controller setups to build the module, configure parameters, integrate flight controller data, implement WiFi broadcasting, and validate its functionality.

To help you apply what you learn to real projects, we will also provide supporting open-source code, a build guide, and a technical discussion group.

Resources at a Glance

Open-Source Code

The AmovRemoteID project has made its RID module code and related materials publicly available. Developers can build on the existing project to adapt it to their hardware, validate functionality, and carry out further development.

Open-Source Repository:

https://gitee.com/amovlab1/AmovRemoteID

Build Guide

Star the open-source project and join the technical discussion group to receive the Open-Source RID Module Build Guide.

Technical Discussion Group

After the livestream, developers can also join the project’s technical discussion group to continue discussing RID, PX4, MAVLink, ESP32, and GB 46750-2025.

The group is a place to continue discussing issues encountered during the build, share experience adapting the project to different hardware, and suggest improvements to the open-source project.