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I was awarded a $500 coupon is applicable for purchasing 2 PCBA prototypes. The coupon can be used toward PCB fabrication, components, PCBA assembly, and shipping costs. This is the second in a series, focuses on bridging the gap between working edge AI prototypes and professional, scalable deployments. As part of the Edge AI Earth Guardians series submitted to the Hackster.io Earth Guardians Challenge with EDGE AI FOUNDATION and NextPCB, this project documents the real-world process of transforming a breadboard build or DIY module into a robust, manufacturable product—by leveraging the NextPCB manufacturing voucher for custom PCB and enclosure prototyping.
Why This Project is EssentialEnables Replicability: Open-source hardware must be easy to replicate. A custom PCB design removes soldering hassles for educators, enthusiasts, and community groups who want to build and deploy these solutions at scale.
Accelerates Deployment: Professionally fabricated PCBs and enclosures enable fast, reliable field deployment—making environmental impact and data collection much more practical.
Closes the Loop Between Prototype and Product: This project delivers step-by-step instructions, technical notes, and documentation on how to go from project design, to BOM, to Gerber files, to a ready-to-assemble manufactured kit using NextPCB services.
Documenting the Journey: The section acts as both a how-to guide and a project diary, showing pitfalls, learning moments, and dialogue with NextPCB/Hackster to assist future makers.
Key Steps and Technical DeliverablesDesign Finalization
Selection of all core components (AI module, power, camera, deterrents, connectors).
Schematic capture and PCB layout using KiCad or similar EDA tools.
Considerations for outdoor housing, modularity, and future upgrades.
BOM and Gerber Preparation
Creation of a detailed Bill of Materials with part numbers, suppliers, and open references.
Export of Gerber files and assembly documentation.
Validation using NextPCB’s free Gerber viewer and online order interface.
Ordering and Manufacturing
Online submission through the NextPCB portal with manufacturing options selected (board number, color, finish, assembly, etc.).
Use of the Hackster-awarded $500 NextPCB voucher.
Documentation of payment workflow, email/invoice trails, and subsequent communications.
Receiving, Assembling, and Testing
Unboxing, quality control checks, and first assembly run.
Stepwise testing of all hardware functions (power on, AI core, camera, deterrents, logging).
Outdoor environmental checks—seal integrity, mounting, weather resistance.
Feedback to NextPCB and Iteration
Notes on the ease of use, questions raised (e.g., can NextPCB help fabricate enclosures or mounts?), and actual support received.
Lessons learned and recommendations for future users of NextPCB for open hardware.
Short “Tips for Future Builders” sub-section for community value.
Open-Source Sharing
All files, instructions, and learning notes shared on GitHub, Hackster, and linked in the project story. Clear licensing and collaboration invitation.
Relationship to the Earth Guardians SeriesThis “enabler” project is crucial for ensuring that the AI-powered wildlife guardian systems developed in the series are not just impressive one-off builds, but are truly approachable, robust, and distributable. The process and knowledge documented here pave the way for students, researchers, and citizen-scientist groups to build, adapt, improve, and deploy these solutions in their own communities.
I submitted the pcb file from this github repo to nextpcb. I have completed all the steps on NextPCB and my 5 PCB boards have been shipped. However, I am having trouble with my DHL shipment because I need to pay a duty fee. I was informed that this was my responsibility to pay the duty fee. I have chosen not to pay the fee and DHL will sent it back to NextPCB. I wanted to describe how I was able to find and open source PCB design for the Grove Vision AI V2 that I used to submit my PCB file to NextPCB.
Repository Link:
Summary of the Grove Vision AI V2 Library Repo:
This GitHub repository by Seeed-Studio provides a full hardware design package for the Grove Vision AI V2 module.
It includes PCB layout files (.kicad_pcb), schematic files (.kicad_sch), a Bill of Materials (BOM), 3D models for the module case, and images for visual reference.
The README and supporting documentation provide step-by-step guidance for using KiCad, importing symbols and footprints, and customizing the design for your own project.
The repo also features integration options like the Seeed Studio Fusion PCB/PCBA service and instructions for their Co-Create program for commercializing your prototypes.
Additional directories within the repo offer KiCad libraries for capacitors, connectors, ICs, sensors, relays, switches, and other components for broader hardware development.
To generate solution code for working with the Grove Vision AI V2 and Seeed OPL KiCad Library, follow these steps to set up your environment and access the provided files and symbols:
Step-by-step instructions:
Download and Clone the Repository
Open your terminal and run:
bash
git clone https://github.com/Seeed-Studio/OPL_Kicad_Library.git
This will give you all supporting files needed for the Grove Vision AI V2 module, including PCB, schematic, BOM, and 3D model files.github
Open and Use the KiCad Project
Open KiCad.
Go to File -> Open Project and choose the project folder for Grove Vision AI V2.
Open Grove - Vision AI Module V2.kicad_pcb for PCB design and Grove - Vision AI Module V2.kicad_sch for the schematic.
Add OPL Footprint and Symbol Libraries
In KiCad, go to Preferences -> Manage Footprint Libraries and add the OPL_Kicad_Library directory if not already added.
Similarly, go to Preferences -> Manage Symbol Libraries and add the symbol library from your cloned repo.
Use the library's components in your design by searching for "seeed" or "OPL" in the component browser.
Customize the PCB or Schematic
You can change components and footprints as needed to match your design requirements, add additional sensors, or modify connectivity.
Example Usage Snippet for Adding a Component (Symbol) in KiCad:
In the schematic editor, click "Add Symbol."
Search for "Grove Vision AI V2" or "Sensor-Transducer" (if available in the library).
Place it in the schematic and connect as needed.
Example KiCad Symbol/Footprint Usage (Pseudocode):
AddSymbol("Grove Vision AI V2")
ConnectPin("VCC", "3.3V Power Supply")
ConnectPin("GND", "Ground")
ConnectPin("SCL", "MCU_I2C_SCL")
ConnectPin("SDA", "MCU_I2C_SDA")
Modify this logic as needed based on your application and schematic.github
Note: All supporting solution code—for PCB, schematic, BOM, and models—is already provided in the repo. Use KiCad to open, view, and edit the files as necessary. For programming or integrating with an MCU, consult Seeed's documentation for Grove Vision AI V2 firmware APIs, and use standard I2C/SPI communication code for your microcontroller platform.
Here are the other solution options available for the Grove Vision AI V2 Library within the Seeed OPL KiCad Library repo. This will help you tailor your workflow and utilize all included assets:
Main Solution Code & Options in the Directory:
KiCad Project & Design Files:
Grove - Vision AI Module V2.kicad_pcb — PCB layout for Grove Vision AI V2
Grove - Vision AI Module V2.kicad_pro — KiCad project file
Grove - Vision AI Module V2.kicad_sch — Complete schematic for the module
Bill of Materials (BOM) & Documentation:
Grove_Vision_AI_V2_BOM.xlsx — Component list (BOM) for sourcing, assembly, and ordering
README.md — Full setup, usage instructions, highlights, and customization guidelines
3D Model & Case Files:
himax.3mf — 3D model file for case/visualization
himax.stp — 3D STEP file for enclosure or mechanical integration
Images for Reference:
1.png, 2.png — Likely reference visuals of board, schematic, or case
Other Noteworthy Options and Resources:
Symbol and Footprint Libraries:
The repo also includes comprehensive directories for capacitors, connectors, ICs, sensors, relays, etc., all with custom KiCad .lib and .pretty files.
These can be found under “Seeed Fusion Component Libraries for KiCad,” e.g.,
OPL_Capacitor.pretty
OPL_Connector.pretty
OPL_Sensor-Transducer.pretty
OPL_Integrated_Circuit.pretty, and many more
Fusion & Commercialization Services:
Direct integration with Seeed Studio Fusion for PCB manufacturing and assembly
“Co-Create with Seeed Studio” program to commercialize advanced prototypes
Getting Started/How-To:
Step-by-step examples for adding and using OPL symbol/footprint libraries (covers both Grove Vision AI V2 and XIAO series)
Customization options for adapting the baseline board to your own project
Bulk and Related Libraries:
The OPL_Kicad_Library repo includes other Seeed modules such as Wio LR1121, Wio SX1262, XIAO ESP32S3, etc. If you need multi-board or cross-module design, these are prebuilt and ready.
Seeed OPL Parts List:
There’s a downloadable Excel Open Parts List, covering all available, vetted Seeed Fusion components for design and assembly.
Summary Table:
Category
Options/Files Included
PCB & Schematic
.kicad_pcb, .kicad_sch, .kicad_pro
Documentation
README.md, BOM.xlsx
3D/CAD
.3mf, .stp files
Visual Aids
.png images
Symbol/Footprint
OPL_.lib, OPL_.pretty for IC, sensors, connectors, relays, etc.
Manufacturing Help
Seeed Studio Fusion, Co-Create program, commercial support
How-to Guides
Step-by-step library integration and customization docs
Related Modules
Wio LR1121, Wio SX1262, XIAO series hardware libraries for broader Seeed hardware design
This robust set of files and resources means you can:
Design, customize, and prototype Grove Vision AI V2-based applications
Source directly from the BOM
Prepare documentation and visuals for project submission/commercialization
Expand to other Seeed hardware design projects effortlessly.github+1
On to the next project in this series which demonstrates how to design, train, and deploy a custom squirrel detection AI model using edge hardware to protect bird feeders and support biodiversity, with a fully open-source workflow for future improvement and adaptation.
Project3 -Squirrel Detection Model Design and Implementation
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