Dear All,

It’s been four months since our tiny AI superstar, reCamera, first stepped into the spotlight among our developer community. From its humble beginnings to the milestones we’ve achieved together, reCamera has become the trusted companion, continually inspiring creativity and innovation in edge AI and robotics. Now, as we look back at the journey so far, it’s the perfect moment to revisit how it all started, celebrate the progress we’ve made, and explore the exciting possibilities that await in the next chapter!

Have you heard about reCamera? What makes it unique?

reCamera comes with its processor and camera sensor. It’s the first open-source, tiny AI camera, programmable and customized, powered by an RISC-V SoC, delivering 1TOPS AI performance with video encoding 5MP@30fps. The modular hardware design gives you freedom to change various camera sensors and diverse interfaces baseboard as requirement, offering the most versitile platform for developers tackling vision AI systems.

Hardware checking list

• Core board: CPU, RAM, 8GB/64GB eMMC, and wireless module as customized antenna on-board
• Sensor board: currently compatible with OV5647/IMX335/SC130GS camera sensor, and continuously supporting more on the list, along with other sensors: mic, speaker, actuator, LED.
• Base board: determines the communication ports at reCamera’s bottom, we have USB2.0, ethernet, and serial port by default, open to be customized as you want – PoE/CAN/RS485/Display/Gyro/Type-C/vertical Type-C, etc.
• Core board covering by metal mainframe, along with the rubber ring wrapped inside the grooves for waterproofing and excellent temperature maintainance below 50℃.

OS & Dashboard

Well, the very first and important impression you should get from reCamera is that it’s already a computer. We set up the build root system, a lightweight customized Linux system in multi-thread, running all tasks without worrying about the conflicts. It supports Python and Node.js directly from console. You can also easily deploy the compiled executive files from C/Rust, so, very programming-friendly.

Just in case you’d prefer to forget about all programming scripts and complex configurations we’ve pre-built Node-RED integration for you, to build up your whole workflow in NO-CODE. It’s completely simple to start by choosing the customized nodes for reCamera pipeline, linking each other to call the camera API, and using the NPU to load AI models directly onto the device. Finally, a web UI or mobile dashboard could show up seamlessly and help verify results effortlessly.

So far, what we’ve done

Ultralytics & reCamera

Besides the standard reCamera as a standalone device only with hardware combination and Node-RED integration, we also provide you another option that can be more seamless to build your vision AI project – reCamera pre-installed with Ultralytics YOLO11 model (YOLO11n)! It comes with the native support and licensing for Ultralytics YOLO, offering real-world solutions such as object counting, heatmap, blurring, and security systems, enhancing efficiency and accuracy in diverse industries.

Application demos

1. reCamera voice control gimbal: we used Llama3 and LLaVA deployed on reComputer Jetson Orin. The whole setup is fully local, reading live video streamed from reCamera to get the basic perception of the current situation, and delivering instructions through Jetson “brain” thinking. Now, you can ask reCamera to turn left to check how many people are there and describe what it sees!

2. reCamera with Wi-Fi HaLow: We’ve tested reCamera with Wi-Fi HaLow long-range connectivity, linear distance could be up to 1km in stable!

3. Live-check reCamera detecting results through any browser: With pre-built Node-RED for on-device workflow configuration, you can quickly build and modify your applications on it, and check out video streams with various platforms.

4. reCamera with LeRobot arm: We used reCamera to scan ArUco markers to identify specific objects and utilized the ROS architecture to control the robotic arm.

Milestone – ready to see you in the real world!

Where our reCamera has traveled

• California, US – K-Hacks0.2 humanoid robotics hackathon 12/14-15
• Shanghai, China – ROSCON China 2024 12/08
• Barcelona, France – Smart City Expo World Congress 2024 11/05-07
• California, US – MakerFaire Bay Area 10/18-20
• Madrid, Spain – YOLO Vision 2024 09/27

Wiki & GitHub resources

Seeed Wiki:

• Beginner guide – getting started
• Interfaces usage
• Model conversion from other frameworks to ONNX format
• Network connection – while a USB-connected device fails to recognize reCamera during the network configuration for reCamera

Seeed GitHub:

• reCamera hardware: all hardware design references
• reCamera OS: how to flash and build on

Appreciate community contribution on reCamera resources from our Discord group:

• chilu – get started with reCamera on Node-red: how to connect to VS code
• chilu – how the MQTT code works with reCamera
• chilu – video stream processor with reCamera

Listen to users: upon Alpha Test reviews

Based on insights from the Alpha test and feedback during the official product launch, we’ve gained invaluable input from our developer community. Many of you have voiced specific requests, such as waterproofing the entire device, integrating NIR infrared, thermal imaging, and night vision camera sensors with reCamera. These features are crucial, and we’re committed to diving deeper into their development to bring them to life. Your enthusiasm and support mean the world to us—thank you for being part of this journey.

Some adorable moments~

In addition, we’ve selected four Alpha testers to explore fresh ideas and contribute to hardware iterations by trying out the reCamera gimbal. Stay tuned for our updates, and continue to join us as we embark on this exciting path of growth and innovation!

Warm Regards,

AI Robotics Team @ Seeed Studio

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