---
title: "Find street defects from routine drives"
description: "A four-step playbook to choose the defects worth finding, capture images on routes your vehicles already drive, have an inspector confirm every flag and turn confirmed defects into work orders."
url: https://lidvizion.ai/guides/find-street-defects-from-routine-drives/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---

[Field guides](https://lidvizion.ai/guides/) 4 steps

# Find street defects from routine drives

A four-step playbook to choose the defects worth finding, capture images on routes your vehicles already drive, have an inspector confirm every flag and turn confirmed defects into work orders.

For: Public works, transport and facilities teams that learn about potholes, damaged signs and obstructions mostly from complaints.

Vehicles already drive most streets every week, but the defects they pass are only reported when someone complains. Cameras on those routes can flag likely defects with a photo and location, while inspectors keep the final say. These four steps keep the scope narrow, protect privacy and tie every confirmed defect to a work order.

## Step 1 — Choose the defects that matter

**Goal:** Agree a short list of defects worth detecting.

1. List the defects that cause the most complaints, claims or safety risk.
2. Pick two or three to start, such as potholes, damaged signs or blocked paths.
3. Write a plain definition and example photos for each.
4. Agree who confirms each defect type and how work orders are prioritised.

**You finish with:** A short defect list with definitions, examples and owners.

## Step 2 — Capture on existing routes

**Goal:** Collect usable images without extra drives.

1. Choose vehicles that already cover the target streets regularly.
2. Mount cameras and record location with every image.
3. Decide what is processed on the vehicle and what is sent for review.
4. Blur faces and number plates before images are stored or reviewed.

**You finish with:** Located, privacy-protected images from routine routes.

## Step 3 — Flag and confirm

**Goal:** Put likely defects in front of an inspector.

1. Flag likely defects with a photo, location and defect type.
2. Group repeat flags at the same location.
3. Have an inspector confirm, reject or reclassify each flag.
4. Create a work order only for confirmed defects.

**You finish with:** Inspector-confirmed defects with work orders.

## Step 4 — Measure and refine

**Goal:** Show earlier detection and a lower review load.

1. Track the share of flags confirmed by inspectors.
2. Track time from capture to work order.
3. Compare defects found by drives with those found by complaints.
4. Use rejected flags to tighten definitions and the model.

**You finish with:** Measured results and a list of improvements.

## Common pitfalls

- Trying to detect every defect type at once.
- Creating work orders without an inspector confirming them.
- Storing images with visible faces or number plates.
- Adding dedicated drives instead of using routes vehicles already cover.

Want a hand getting started?

## Start with a workflow audit

We pick the workflow with you, set the baseline and write the bounded design.

[See the audit](https://lidvizion.ai/workflow-audit/) [Talk this playbook through](https://lidvizion.ai/contact/?need=milestone-delivery&from=%2Fguides%2Ffind-street-defects-from-routine-drives%2F#write)

## See it as a workflow

- [Street asset defect reports from routine drives](https://lidvizion.ai/use-cases/street-asset-defect-reports/): Facilities & operations Use images captured on routine drives to flag likely road, sign and street-furniture defects with a location, so an inspector confirms each one and real defects become work orders.

## More guides like this

- [Make your footage searchable](https://lidvizion.ai/guides/make-your-footage-searchable/)
- [Start tracking players from your own footage](https://lidvizion.ai/guides/start-tracking-players-from-your-own-footage/)

## Related answers

- [When should a company build custom AI software instead of using existing tools?](https://lidvizion.ai/answers/when-should-a-company-build-custom-ai-software/)
- [What can computer vision do for a business?](https://lidvizion.ai/answers/what-can-computer-vision-do-for-a-business/)

Bring the messy version

## One workflow. A better way to run it.

Show us the tools, the handoffs, and the part that keeps slowing your team down.

[Let’s map your workflow](https://lidvizion.ai/contact/) · [Read our approach](https://lidvizion.ai/approach/)