AI-Powered Floor Plan Lighting Design Canvas by Muhammad UsmanAI-Powered Floor Plan Lighting Design Canvas by Muhammad Usman

AI-Powered Floor Plan Lighting Design Canvas

Muhammad Usman

Muhammad Usman

My Role: Senior Full-Stack Developer
Tech Stack: Next.js, React, TypeScript, Fabric.js, AI, PostgreSQL, Tailwind CSS, Vercel

Project Description

An AI-powered web application for designing, visualizing, and managing lighting layouts directly on architectural floor plans.
I developed an interactive canvas workspace where users can upload floor plans, place and customize lighting fixtures, use AI-assisted design suggestions, manage projects, and share layouts with clients and teams.

Problem

Manual lighting design is time-consuming and repetitive
Precise fixture placement across floor plans can be challenging
General-purpose tools require significant manual editing
Managing revisions and project versions can become disorganized
Client feedback and design sharing can be inefficient

Solution

AI-assisted lighting layout and fixture recommendations
Interactive Fabric.js canvas for floor plan editing
Drag-and-drop fixture placement and customization
Project management with auto-save and version history
AI-assisted workflows to reduce repetitive design work
Export and sharing functionality for client collaboration
Responsive UI focused on a fast and intuitive design experience

Key Features

AI-powered lighting design assistance
Interactive Fabric.js canvas
Floor plan upload and visualization
AI-based fixture placement suggestions
Drag-and-drop lighting fixtures
Fixture positioning, resizing, and editing
Project management
Auto-save
Recent projects
Design export and sharing
Client collaboration workflows
Responsive UI/UX Web and Tablet

Development

Built with Next.js, React, TypeScript, Fabric.js, AI, PostgreSQL, and Tailwind CSS.
I developed the interactive canvas engine using Fabric.js, including floor plan rendering, fixture placement, object manipulation, editing, and layout interactions. I also integrated AI-assisted lighting workflows that allow users to generate design suggestions and refine them directly on the canvas.
A key challenge was combining AI-generated suggestions with a flexible canvas editor, giving users full control to review, modify, and fine-tune AI-assisted lighting layouts.

Results & Outcome

Streamlined lighting design directly on architectural floor plans
Reduced repetitive manual design work through AI assistance
Enabled precise fixture placement through an interactive canvas
Simplified project and revision management
Improved the design review and collaboration workflow
Created a scalable foundation for AI-powered architectural design tools
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Posted Sep 8, 2025

Developed a web app for efficient lighting design on architectural floor plans. Floor Plan Lighting Design App Development