Number plate recognition (ANPR / LPR), joined to everything else.
DataGlue marries Number plate recognition (ANPR / LPR) data with your other systems in one living model. Every number shows its formula and its records.
Number plate recognition (ANPR / LPR): Plate readers that record a vehicle plate, location and time of detection.
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- NO NATIVE CONNECTOR · WEBHOOK
Bring Number plate recognition (ANPR / LPR) and one decision to the call. Tool names are enough; no access needed.
Trusted by
- WebhookIN
- Your warehouse or databaseIN
- REST APIIN
- File exportIN
What comes in from Number plate recognition (ANPR / LPR). Plate reads, reader ids and timestamps come in. Plates stay on vehicle records unless your systems already hold an authorised person link.
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Webhook
Where Number plate recognition (ANPR / LPR) supports event webhooks, your system sends recorded counts, presence or plate events to a DataGlue inbound URL. The fields and identifiers are agreed in the build. No footage or face images are imported.
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Your warehouse or database
Recorded events from Number plate recognition (ANPR / LPR) join through tables you already sync to your warehouse. Postgres connects today; other databases need a sync you run or our REST API. No footage or face images are imported.
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REST API
A sync you run reads the recorded events available from Number plate recognition (ANPR / LPR) and sends them to our REST API. The fields, identifiers and schedule are agreed in the build. No footage or face images are imported.
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File export
Recorded count, presence or plate exports from Number plate recognition (ANPR / LPR) are imported as files, with their source ids and timestamps. The available fields are checked in the build. No footage or face images are imported.
There is no native Number plate recognition (ANPR / LPR) connector today; the routes above are how it joins. Connections are agreed in the build. We check the source data, consent and identifiers before promising a linked journey. Number plate recognition (ANPR / LPR) is a trademark of its owner; this page implies no partnership or endorsement.
Describe the outcome. DataGlue works it out and shows you the formula.
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Describe the outcome you want in plain words, such as "Plate seen three times in 24 hours".
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DataGlue works it out from the definitions of your data sources, Number plate recognition (ANPR / LPR) included, and shows the formula in concise English.
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Send it on: to reports, BI tools, any destination, or the AI tools your team already uses.
- EXAMPLE OUTCOME 01
Plate seen three times in 24 hours
THE FORMULACount recorded reads of the same plate within a rolling 24-hour window, excluding duplicate reads of one visit.
- EXAMPLE OUTCOME 02
Perimeter visits with no access record
THE FORMULARepeated plate sightings near the perimeter with no matching access record in the same period. Flag for review; a sighting alone does not establish a threat.
- EXAMPLE OUTCOME 03
Repeat mall vehicle visit
THE FORMULADistinct car park visits for the same recorded plate, kept as a vehicle tag rather than assumed shopper identity.
Tags about people come only from signals your systems already record, under your privacy policy and local law. Sensitive tags, such as gender or income estimates, are marked as estimates and can be switched off. Records link only where recorded identifiers support the match. People are never identified from faces.
Want one of these from your Number plate recognition (ANPR / LPR) data? We map the route and the first outcome on the call.
Book a CallBring Number plate recognition (ANPR / LPR) and one decision. We'll map the route and the first outcome on the call.
The call scopes fit. The build is a separate engagement, priced before work begins.