The use of iOS and Android devices has exploded in the enterprise space. Forward looking developers and IT departments are creating new revenue-generating and cost-saving services to track, validate, authenticate and collect data using these amazing devices.
For asset tracking applications the use of iOS and Android devices can be particularly convenient and cost-saving.
Because deploying purpose-built mobile computers to every field service worker is a logistic nightmare and prohibitively expensive, especially for independent contractors.
Instead, these workers can freely download the codeREADr app to their own smartphones, enter their authorized app credentials and then scan on behalf of their employer or client. Every day we have over 10,000 app-users doing that – mostly using their own devices, though some use provisioned devices where it makes financial and logistic sense.
The roadblock for using these devices for data capture had been the barcode scanning performance using just the device’s built-in camera. We’ve solved that problem with our SD PRO camera scan engine. Its opened up new applications to capture, collect, analyze and act upon field data that were previously not viable.
Let’s look at UID tags printed with standard or inverted DataMatrix barcodes (examples). The typical smartphone app reads these codes quite slowly and inaccurately (if at all). However, with SD PRO our app instantly reads theses codes.
To demonstrate, we scanned sample UID tags manufactured by a leading suppler of durable tags for asset tracking – Camcode. Watch the 45-second video at the beginning of this post.
As an added benefit, codeREADr’s integrated cloud-based Web service offers the ability to alter scan values and scan responses in-app and also alter how the data is exported in a template. In this way the scanned data from a UID tag can be formatted however a client needs it formatted.
That data can be merged with timestamps, GPS coordinates, photos, and textual data collected at the time of the scan. Those scan records can then be filtered, shared, exported and inserted into local or cloud-based databases hosted by third parties or the client.