Week 17
Invention, Intellectual Property and Income

ASSIGNMENT
Develop a plan for dissemination of your final project. Prepare a summary slide and video clip. Outline future possibilities and describe how to make them probabilities.
PROJECT
Krypto Support — Wearable Activity Monitor for a Scotch Terrier with IVDD
Dissemination Plan
Sharing Krypto Support with the world
Krypto Support was born from a personal need — monitoring my dog's IVDD condition — but the concept applies to any pet owner dealing with neurological or mobility conditions. The dissemination plan focuses on making the project fully reproducible by others and reaching the communities that would benefit most.
| Channel | Audience | Content |
|---|---|---|
| Fab Academy archive | Fab Lab community worldwide | Full documentation, source files, bill of materials, and step-by-step instructions on the Fab Academy GitLab |
| GitHub repository | Makers, developers, open-source community | Firmware, web dashboard code, KiCad files, and STL models — all under an open license with a clear README |
| Instructables / Hackaday | DIY makers and pet owners | Step-by-step build guide written for people outside Fab Academy — simplified language, photos of each step |
| Social media | Pet owners, IVDD communities | Short video of Krypto wearing the vest + dashboard demo. Instagram reels, TikTok, and pet health Facebook groups |
| Veterinary outreach | Krypto's vet and local clinics | Sample CSV data export and a one-page summary explaining how the monitor works and what data it provides |
| Local Fab Lab workshops | Students and makers in Puebla | Hands-on workshop showing how to adapt the wearable to different dog sizes and conditions |
Open by default
Everything in this project — hardware, firmware, software, and garment patterns — will be published with open licenses so that anyone can reproduce, modify, and improve it. The goal is not to sell a product, but to make it possible for any pet owner with access to a Fab Lab (or basic maker tools) to build their own wearable monitor adapted to their pet's specific condition and body.
Intellectual Property
Licensing strategy
The project has three distinct layers — hardware, software, and documentation — and each one uses the license best suited to its type. The common thread is that all three are permissive and open: anyone can use, modify, and redistribute the work, as long as they give attribution and share improvements under the same terms.
CERN-OHL-S v2
The CERN Open Hardware License (Strongly Reciprocal) covers the PCB design, KiCad files, 3D-printed enclosure STLs, and garment patterns. Anyone can manufacture, modify, and distribute the hardware, but must share any modifications under the same license.
MIT License
The firmware (C++ / Arduino) and the web dashboard (HTML/CSS/JS) are released under the MIT License — the most permissive option. Anyone can use, copy, modify, and distribute the code for any purpose, including commercial, with minimal restrictions.
CC BY-SA 4.0
All documentation — including the Fab Academy pages, build guides, photos, diagrams, and instructional content — is published under Creative Commons Attribution-ShareAlike. Others can remix and redistribute as long as they credit the original and share alike.
Open over closed
A patent would restrict reproduction and require legal resources to enforce. The purpose of this project is to help pets, not to generate profit from the design. Open licenses maximize reach and invite improvement from the community.
Future Possibilities → Probabilities
From prototype to impact
The current prototype solves one problem for one dog. The following outlines how to turn future possibilities into concrete probabilities — with specific actions, not just wishes.
| Possibility | How to make it a probability |
|---|---|
| Adapt for different dog sizes and breeds | Parametric garment patterns in Shapr3D that take body measurements as inputs. Publish a sizing guide with the open-source files so makers can adjust. |
| Add machine learning for smarter alerts | Collect labeled movement data from Krypto over several months. Train a lightweight classification model (TinyML) that can run on the ESP32 to distinguish walk, rest, play, stumble, and seizure. |
| Cloud-based dashboard with historical trends | Migrate from a local ESP32 web server to an MQTT + cloud stack (e.g. Firebase or InfluxDB). This enables remote monitoring and long-term trend analysis across weeks or months. |
| Multi-pet monitoring | Each vest gets a unique device ID. The dashboard is extended to support multiple devices, allowing a household — or a veterinary clinic — to track several animals simultaneously. |
| Commercial kit for pet owners | Partner with a Fab Lab or local manufacturer to produce pre-milled PCBs and pre-cut fabric kits. Sell on Tindie or Etsy as a DIY assembly kit with the instructions hosted on GitHub. |
| Veterinary collaboration | Share the data export format with local clinics. If vets find it useful, develop a standardized report template they can integrate into patient records. |
Project Status
What tasks have been completed, and what tasks remain?
| Task | Status | Notes |
|---|---|---|
| System integration plan | DONE | Full plan documented in Week 15 with diagrams, components, and data flow |
| Project development plan | DONE | All 14 checklist items completed in Week 16 |
| PCB schematic in KiCad | DONE | XIAO ESP32 + MPU-6050 + LED + button schematic complete |
| PCB layout and milling | DONE | Layout finalized; milling scheduled on the Roland SRM-20 |
| 3D enclosure design | IN PROGRESS | Modeled in Shapr3D; first print tested for fit |
| Firmware — IMU reading | DONE | MPU-6050 reads working over I2C; threshold logic in development |
| Firmware — Wi-Fi transmission | DONE | ESPAsyncWebServer selected; implementation after IMU logic is stable |
| Web dashboard | DONE | Wireframes done; build starts once Wi-Fi data stream is working |
| Vest garment — pattern and sewing | PENDING | Krypto's measurements taken; fabric purchased; cutting and sewing scheduled |
| Full system integration test | PENDING | Planned after all subsystems are individually working |
What's working? What's not?
WORKING
- ✓ MPU-6050 reads accelerometer and gyroscope data reliably over I2C
- ✓ XIAO ESP32 connects to Wi-Fi and maintains a stable connection
- ✓ KiCad schematic is clean and passes ERC checks
NEEDS WORK
- ! Threshold values for alert triggers need calibration with real movement data
- ! Battery life hasn't been benchmarked yet — deep sleep mode not implemented
- ! CSV export format hasn't been validated with the vet
What questions need to be resolved?
- ? What is the optimal IMU sampling rate to balance data quality and battery life? (Testing 10Hz vs 50Hz vs 100Hz)
- ? Should alerts trigger on raw threshold crossings or on a rolling average to avoid false positives?
- ? How to waterproof the enclosure seam without making the PCB inaccessible for debugging?
- ? What data visualization format is most intuitive for a vet who has never seen IMU data before?
- ? Can the vest pattern be simplified so someone without sewing experience can assemble it?
Planned — what will happen when?
| Day | Milestone | Deliverable |
|---|---|---|
| D1 | Mill and solder the final PCB | Working board with XIAO, IMU header, LED, and button |
| D2-3 | Sew, and assemble the final vest | Finished garment with electronics integrated and wire channels sewn |
| D4 | Full integration test on Krypto | 8-hour wear test; validated alerts; battery endurance measured |
| D5 | Final documentation, slide, and video | Presentation-ready materials; all files published on GitLab and GitHub |
What Have I Learned?
Reflections
Building Krypto Support has been a journey through every discipline in Fab Academy and the most important lesson is that a real project forces you to connect them all. Electronics design is not separate from garment design when the PCB has to fit inside a pocket sewn into a vest worn by a living animal. Firmware is not separate from user interface when the data you transmit has to make sense to a veterinarian who has never seen an accelerometer reading.
Some specific things I've learned along the way:
- 1 KiCad from zero — I had never designed a PCB before Fab Academy. Going from a blank schematic to a milled, soldered, working board was one of the steepest and most satisfying learning curves.
- 2 Designing for a living user — a dog can't tell you the vest is uncomfortable. I learned to observe Krypto's body language and iterate the garment based on how he behaves, not on what looks good on paper.
- 3 System thinking — each subsystem (sensor, processor, garment, dashboard) depends on decisions made in every other subsystem. Planning the integration before fabrication saved weeks of rework.
- 4 I2C debugging — getting the MPU-6050 to communicate reliably taught me to read datasheets carefully, check pull-up resistors, and use a logic analyzer when serial prints aren't enough.
- 5 Documentation as design — writing clear documentation while building (not after) helped me catch design flaws early and make better decisions.
- 6 Open source is a responsibility — publishing files isn't enough. Good documentation, clear licensing, and a readable README are what make a project actually reproducible by someone else.
The bigger picture
Fab Academy taught me that making things is not about mastering one tool, it's about learning to move fluidly between design, fabrication, electronics, and code, adapting each one to the constraints of a real problem. Krypto Support exists because I needed to help my dog, and Fab Academy gave me the skills to actually do it, from the first 3D model to the last line of firmware.