Computer vision & field operations
Turn equipment photos into structured records.
Connected equipment-label recognition with registration logic and 360-degree reporting context.
Team experience / 309 Technology. Implementation led by Mathyu Cardozo
Project
309 Technology / HVAC
Industry
HVAC / field services
Development
3.5 months
Stack
Google Cloud Vision, Equipment-registration logic, 360-degree reporting
Evidence
Photo to fields
Mathyu Cardozo · AI Engineer Lead
The challenge
Equipment label photographs still needed to become structured registration data.
What we built
OCR and application logic connected photographs to equipment fields; 360-degree reporting remained separate.
What changed
A photo-to-record handoff, with no quantified accuracy or time savings.
Context and problem
Field equipment photos needed a route from label recognition to usable registration information.
What we built
Implementation at a glance
Read equipment labels from field photos.
Connect recognized text with equipment-registration logic.
Add reporting context using 360-degree images.
Implementation details
Manufacturer, model and serial information lived on physical HVAC labels. Field technicians could photograph the equipment, but the next operational step needed structured information rather than an image or a block of recognized text. Error reports also needed visual context that helped explain an issue beyond the label itself.
Connect capture to recognition
Technician photographs supplied the label images. Google Cloud Vision extracted the text visible in those images and returned it to the application.
Give the text equipment meaning
Application logic structured the extracted information into equipment fields, including manufacturer, model and serial information, for the registration workflow.
Add reporting context
A companion capability used 360-degree imagery in error reports. The source describes it separately and does not establish an automatic OCR-failure trigger.
Results and evidence
The delivered capability connected field photography, managed OCR and equipment-registration logic. The useful handoff was structured equipment information. A successful OCR response and a correct destination record are distinct checkpoints; this case does not provide a measured accuracy rate, processing volume or time-saving result.
Relevance and PDF contents
Where this pattern applies
This pattern applies when a service team already collects photographs but still copies information into another system. Start by defining the destination fields, deciding how uncertain or incomplete data should be handled and identifying the person who owns an exception. The full PDF explains the responsibilities within that handoff.
Inside the full PDF
See how field photography, text recognition and application logic connect to equipment registration.
Photo-to-record workflow and responsibilities
OCR output versus equipment-field structuring
Separate role of 360-degree reporting
Field-data readiness worksheet
Free PDF · 7 pages · Includes a readiness worksheet.
On this page
Follow the handoff from photo capture to OCR, application logic and equipment registration. Use the worksheet to assess a similar field-data workflow.
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