Embedded Files
Door Projection Security System.pptxThis slideshow presents the current milestone progress for the Sure Sight Door Projection Security System. The project has pivoted away from extra features and secondary add-ons to focus on proving the core innovation claim: using an exterior door camera feed to create a large, real-time projection on the inside of the door. The presentation highlights the problem, the focused proof-of-concept approach, current progress, remaining challenges, and the path toward demonstrating a working door-scale security display.
Current prototype demonstration showing the Sure Sight system projecting an exterior door camera view onto the inside of the door. These shots document the real-world test environment, the viewer’s perspective from inside the home, and the working projection alignment used to validate the core innovation claim.
current_Setup_Measurments.docxThis document records the current known-good prototype setup for the Sure Sight demo, including door dimensions, projection coverage, projector placement, Ring camera position, image quality notes, and Jetson/display settings. It documents the physical alignment and system conditions used to achieve a working door-scale projection
ForgeMind was born from a simple challenge: spending too much time moving designs from CAD to manufacturing. As a CNC and 3D printing enthusiast, I wanted a faster way to go from idea to production. By combining AI with manufacturing workflows, ForgeMind helps transform engineering concepts into manufacturing-ready outputs with less manual effort and greater efficiency.
Untitled design.pdfForgeMind is an AI-assisted parametric CAD/CAM regeneration platform focused on deterministic geometry intelligence, associative manufacturing workflows, and regeneration reliability.
The platform is designed to bridge the gap between:
engineering intent
CAD geometry
CAM planning
manufacturing synchronization
workflow regeneration
reliability verification
Unlike traditional CAD/CAM systems that treat geometry and manufacturing as loosely connected processes, ForgeMind is being developed as an integrated associative engineering platform where geometry changes intelligently propagate throughout the manufacturing workflow.
I spent a significant amount of time creating designs in AutoCAD, and I wanted a way to speed up the design-to-manufacturing process. That idea led to the creation of ForgeMind—an AI-assisted manufacturing platform designed to help engineers, makers, and inventors move from concept to production more efficiently.
As the owner of a small CNC machine and a 3D printer, I found that 3D printing was relatively straightforward, but creating CNC toolpaths and setting up machining operations was often more complex and time-consuming. ForgeMind was developed to simplify and accelerate that workflow by using AI to help generate manufacturing-ready designs, planning information, and production artifacts from natural-language engineering requirements.
ForgeMindDev1.docxPrompt:
Prompt:
Create a CNC rectangular base plate 300 x 170 x 5 mm.
Add four 5 mm through holes at the corners with 15 mm margin.
Add four 3.4 mm through holes in a rectangular pattern 58 x 49 mm centered at x=240 y=85.
Use 6061 aluminum.
Export STEP, STL, and 3MF.
AI Assistance and References
AI Assistance and References
OpenAI ChatGPT (architecture planning, workflow design, documentation, CAD/CAM strategy, deployment guidance)
GitHub Copilot (code generation and software development assistance where used)
Render documentation (deployment architecture)
Vercel documentation (frontend deployment)
FastAPI documentation (backend framework)
FreeCAD documentation (CAD interoperability and manufacturing workflows)
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