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AI / Image Recognition

Crowdsourced Road Damage Collection Service

A public service where anyone can submit photos of road damage without registration; YOLO automatically judges them and plots the results on a map. A memory-efficient design that separates submission intake from detection.

Duration

Short-term development

Team

1-2 people

Engineered With PythonFastAPIRedisYOLOLeaflet

01 // OVERVIEW

Project Overview

A public service that lets an unrestricted number of people submit photos of road damage for free, with no registration required; YOLO automatically judges the images and plots the damaged locations on a map. Submission intake and image detection are separated into an asynchronous flow, and the detection model is not kept running continuously, which keeps server resource usage low.

02 // KEY FEATURES

Key Features

add_a_photo

One-Screen Submission With No Authentication

Just send a photo - no registration required. Location is obtained from the browser's geolocation or the photo's EXIF data. Per-IP rate limiting prevents abuse.

sync

Asynchronous Separation of Intake and Detection

FastAPI accepts submissions instantly, and a worker performs detection via a Redis queue. The model is launched per job rather than kept running, achieving low memory usage.

map

Map Visualization With Privacy Consideration

Only the detection results and coordinates are retained; the original image is deleted after judgment. Leaflet plots the damaged locations on a map.

03 // TECHNICAL DEEP-DIVE

Technical Highlights

Solution

Resource-Efficient Operation as a Public Service

Rather than keeping the detection model running continuously, the queue-and-worker design smooths out load, and storage is limited to detection results plus coordinates only, keeping the public-facing path lightweight.

04 // IMPACT & RESULTS

Results

No Sign-Up

Anyone can submit

Asynchronous

Intake and detection separated

Low-Memory

Model not kept resident

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