Seeing floor hazards before anyone falls.
FloorEye is a self-funded research and engineering project by Junaid A. Shah. It applies computer vision to cameras a business already owns, identifies spills and wet floors as they appear, and triggers a warning automatically. The goal is simple and public in nature: fewer slip-and-fall injuries in the workplaces that can least afford them.
A spill nobody sees is an injury waiting to happen.
In a busy store, kitchen or warehouse a wet floor can appear in seconds: a leaking cooler, tracked-in rain, a dropped drink. It sits there unnoticed, and somewhere inside that window a worker or a customer goes down. Today most businesses find out only after the fall.
People get hurt
Falls on the same level are among the most common and most preventable injuries suffered by American workers and customers.
Detection depends on luck
A hazard is found when a person happens to walk past it. That is minutes of exposure on a floor where seconds matter.
The cost lands on small employers
One fall can mean a workers' compensation claim, litigation and higher premiums for years, a burden a small business absorbs far less easily than a national chain.
Compliance is hard to evidence
OSHA expects floors to be kept clean, dry and hazard free. Proving that a business actually did so, minute by minute, is nearly impossible with paper checklists.
Existing technology skips the small operator
Advanced safety monitoring has largely been built for enterprise budgets and new hardware, leaving independent businesses with nothing but a mop and a cone.
Nobody can watch every aisle
A manager cannot monitor every floor, every aisle, every minute of a shift. The exposure never actually goes away.
Why this problem is worth solving at a national scale
Same-level falls are a multi-billion dollar annual cost to the U.S. economy and a leading source of lost workdays. The businesses most exposed, independent retailers, restaurants, small warehouses and service operators, are precisely the ones that cannot fund enterprise safety systems. FloorEye is built on the premise that meaningful injury prevention should not require new cameras, a capital project or a corporate safety department. It should run on the equipment a small business already has.
Turning cameras that record the past into cameras that prevent the next injury.
FloorEye connects to existing camera streams and adds a layer of machine perception that does not get distracted, does not take breaks and does not walk past a puddle. When a hazard appears, the system identifies it, warns people nearby and records the event automatically.
Observe
Frames are sampled continuously from each camera at the edge and screened for spills, standing water, freshly mopped surfaces and caution signage.
Verify
A candidate hazard passes through a multi-stage verification pipeline, including comparison against a learned dry-floor reference for that exact camera view, before anything is raised. This pipeline is the subject of the provisional patent filing.
Warn
Connected warning lights and signage switch on through IoT integration and staff are notified by app, SMS and email. No human has to notice first and no human has to press anything.
Record
Every hazard, alert and resolution is timestamped and stored, producing an objective record of how quickly the condition was found and cleared.
Reactive cleanup becomes documented, automatic prevention.
Engineering summary
Designed, built and deployed end to end by a single developer.
Not a concept. Running against live camera feeds.
The frames below were captured from live cameras in participating test stores with the FloorEye model running. No staging and no stock photography. Real cameras, real floors, hazards identified automatically.
Water spill identified at checkout
A fresh water spill on the floor near the register was segmented and flagged from the camera feed, without any person reporting it.
Caution signage and mopped floor tracked
The model distinguishes caution signage from the wet surface itself, which is what lets the system tell a marked hazard apart from an unmarked one.
Captured under signed written authorization from the participating store owners covering camera access and data use.
Validated in real stores, not only on a benchmark.
Two independent retail locations are currently running the system on their own cameras under signed authorization, deliberately configured to test the same claim from two directions.
Three live camera streams
Running on a compact ARM-based AI edge module installed on site.
Three live camera streams, different hardware
Running on a standard low-power x86 edge computer rather than an AI accelerator.
The record behind the work.
FloorEye was conceived, researched, engineered, deployed and documented by one person. The evidence of that work is itself part of the project.
U.S. Provisional Patent Application
Multi-Stage Verification System and Method for Detecting Wet-Floor and Liquid-Spill Hazards from a Fixed Camera Feed.
Self-funded research and development
Every hour and every dollar of development, from first prototype to production deployment, was funded personally with no outside capital, grant or employer support.
193 pages of original documentation
A complete written technical record covering system architecture, technology stack, installation methodology and end-user operation, authored alongside the build.
Seeing Hazards Before People Fall
A published technical paper examining how modern computer vision can identify spills and wet floors the moment they appear, why small and medium-sized businesses carry a disproportionate share of slip-and-fall risk, what federal regulation actually requires of them, and how an automated perception layer closes that gap. The paper maps the system directly to OSHA Walking-Working Surface standards and to NIST SP 800-53 security and privacy controls.
Safety you can actually evidence.
The OSHA Walking-Working Surfaces standard requires employers to keep floors clean, dry and free of hazards, and to be able to show it. Paper logs cannot demonstrate what a floor looked like at 2:14 in the afternoon. A continuous, timestamped detection record can. FloorEye was designed from the outset around that evidentiary gap.
Automatic audit trail
Every hazard, alert and response is timestamped and stored, available for an inspection or a claim without anyone having to reconstruct it later.
Documented speed of response
The record shows when a hazard appeared, when it was flagged and when it was cleared, which is exactly the standard of care regulators look for.
Objective evidence in disputes
An impartial, contemporaneous record of monitoring is stronger than recollection for every party involved in a slip-and-fall dispute.
Published safety and security standards
The full mapping of the system to OSHA and NIST requirements is set out in the published white paper above.
One researcher, one system, built end to end.
FloorEye is not a company and has no team. It is a personal research and engineering project.
JS
Junaid A. Shah
Sole Inventor, Researcher & DeveloperTechnology professional with more than seven years of experience across data engineering, business intelligence, machine learning and full-stack software development, holding an M.S. in Business Analytics. FloorEye began as an independent question about whether the cameras already hanging in ordinary businesses could be made to prevent injuries rather than merely record them, and became a working, deployed system.
Every element of the project is his own work: the research and problem framing, the perception model and its training data, the multi-stage verification method now under provisional patent, the edge software, the backend platform, the web and mobile interfaces, the field installations and the full written technical record.
Questions, answered.
What people most often ask about the project.
Questions about the research?
For technical questions, collaboration on field testing, or requests for the full documentation set and patent record, get in touch directly.
Email Junaid A. Shah