Use cases · Facilities & operations
Parking and space occupancy from cameras
Use existing cameras to count which spaces are free or occupied and feed the count to signage, an app or a dashboard, with people checking anything unusual.
Where it starts
The trigger.
People or staff need to know where space is available, now.
How it runs today
- Staff walk the site or guess from experience.
- Visitors circle looking for space.
- Nobody has reliable occupancy data to plan with.
The workflow
Four bounded steps.
Each step has an owner and a stop rule.
- 01 / Capture
Existing or added cameras cover the spaces to monitor.
- 02 / Detect
A vision model marks each space as free or occupied at a set interval.
- 03 / Publish
Counts feed signage, an app or a dashboard.
- 04 / Review
Low-confidence frames and camera faults are flagged to a person.
Where people stay in control
Approval points.
- Staff review flagged frames and camera outages.
- Faces and plates are not stored unless there is an approved reason.
How we would measure it
Against a baseline.
Measured before and after, on the same work.
Agreement between counts and spot checks.
Time spent checking space manually.
Occupancy data available for planning.
Related
Go deeper.
Build the missing pieceCustom tools and applications for the gaps that matter.Vision analyticsDetection models that turn camera feeds into operational signals — which spaces are occupied, what is present, and what changed.What is computer vision?Software that turns images and video into structured information a system can act on.Use your existing cameras for computer visionA four-step playbook to test whether the cameras you already have can answer a counting, occupancy or safety question before you buy any new hardware.How to measure occupancy and crowd flow with computer visionHow can a business use cameras to count people, vehicles or free spaces without tracking who anyone is?
More use cases
Other places to start.
Facilities & operations
Street asset defect reports from routine drives
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.
See the workflow Facilities & operationsFacilities work order intake and dispatch
Turn maintenance requests from email, forms and chat into complete work orders, set a priority, and route each one to the right technician or vendor for approval.
See the workflow Facilities & operationsDaily work order brief
Summarise open work orders each morning, highlighting overdue, blocked and safety-related jobs and what is waiting on parts, permits or access, so supervisors start the day with a short list of what needs a decision.
See the workflowAn illustrative workflow pattern, not a result from a specific customer.
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.
---
title: "Parking and space occupancy from cameras: AI Use Case"
description: "Use existing cameras to count which spaces are free or occupied and feed the count to signage, an app or a dashboard, with people checking anything unusual."
url: https://lidvizion.ai/use-cases/parking-and-space-occupancy/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---
[Use cases](https://lidvizion.ai/use-cases/) · Facilities & operations
# Parking and space occupancy from cameras
Use existing cameras to count which spaces are free or occupied and feed the count to signage, an app or a dashboard, with people checking anything unusual.
[Talk through this workflow](https://lidvizion.ai/contact/?need=milestone-delivery&from=%2Fuse-cases%2Fparking-and-space-occupancy%2F#write) · [Build the missing piece](https://lidvizion.ai/services/custom-software/)
Where it starts
## The trigger.
People or staff need to know where space is available, now.
How it runs today
- Staff walk the site or guess from experience.
- Visitors circle looking for space.
- Nobody has reliable occupancy data to plan with.
The workflow
## Four bounded steps.
Each step has an owner and a stop rule.
1. 01 / Capture
Existing or added cameras cover the spaces to monitor.
2. 02 / Detect
A vision model marks each space as free or occupied at a set interval.
3. 03 / Publish
Counts feed signage, an app or a dashboard.
4. 04 / Review
Low-confidence frames and camera faults are flagged to a person.
Where people stay in control
## Approval points.
- Staff review flagged frames and camera outages.
- Faces and plates are not stored unless there is an approved reason.
How we would measure it
## Against a baseline.
Measured before and after, on the same work.
### Agreement between counts and spot checks.
### Time spent checking space manually.
### Occupancy data available for planning.
Related
## Go deeper.
- [Build the missing piece](https://lidvizion.ai/services/custom-software/): Custom tools and applications for the gaps that matter.
- [Vision analytics](https://lidvizion.ai/work/#vision-analytics): Detection models that turn camera feeds into operational signals — which spaces are occupied, what is present, and what changed.
- [What is computer vision?](https://lidvizion.ai/resources/basics/what-is-computer-vision/): Software that turns images and video into structured information a system can act on.
- [Use your existing cameras for computer vision](https://lidvizion.ai/guides/use-existing-cameras-for-computer-vision/): A four-step playbook to test whether the cameras you already have can answer a counting, occupancy or safety question before you buy any new hardware.
- [How to measure occupancy and crowd flow with computer vision](https://lidvizion.ai/answers/how-to-measure-occupancy-with-computer-vision/): How can a business use cameras to count people, vehicles or free spaces without tracking who anyone is?
More use cases
## Other places to start.
[All use cases](https://lidvizion.ai/use-cases/)
- [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.
- [Facilities work order intake and dispatch](https://lidvizion.ai/use-cases/facilities-work-order-intake/): Facilities & operations Turn maintenance requests from email, forms and chat into complete work orders, set a priority, and route each one to the right technician or vendor for approval.
- [Daily work order brief](https://lidvizion.ai/use-cases/daily-work-order-brief/): Facilities & operations Summarise open work orders each morning, highlighting overdue, blocked and safety-related jobs and what is waiting on parts, permits or access, so supervisors start the day with a short list of what needs a decision.
An illustrative workflow pattern, not a result from a specific customer.
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/)