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What’s the difference between scanning one barcode and 20? I’m not talking about 20 unique scans; I’m talking about scanning all 20 at the same time.
Scanning multiple barcodes at once requires more than running the same algorithm repeatedly. It needs contextual awareness, spatial understanding of the environment, and pinpoint positioning of visual feedback on users screens.
Ideally, it’s also customized to the exact workflow it’s intended to accelerate. Otherwise, the software won’t know whether to return 20 barcodes for cycle counting versus one barcode out of many for order picking.
Here’s how we built the Scandit AI Engine to make multiple barcode scanning smarter.
Why is multiple barcode scanning difficult?
It’s no surprise that our recent Frontline Retail Revealed report found that scanning one barcode at a time is the top scanning pain point for store associates.
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Building technology to automate all of this requires a different approach than single barcode scanning.
The technology must quickly identify all visible barcodes, determine which ones matter, track them as the device moves around, and present clear, stable visual feedback to the user. And it has to do all of this without draining the battery — because it runs not on a laptop, but on frontline workers’ mobile devices, where usage is heavy and battery life precious.
The Scandit AI Engine integrates three strategies into one cohesive process to solve this:
- AI-powered scene analysis: Computer vision (CV) techniques continuously evaluate the scene — barcode positions, angles, distance, focus, and device motion sensor data — to determine which barcodes to capture and track over time.
- Aligning digital and physical worlds: The barcodes’ dataset is mapped onto augmented reality (AR) overlays that help users relate on-screen content to real-world objects, reducing guesswork and errors.
- User-centered workflows: The overall user experience (UX), from UI elements to task-specific workflows, is optimized for specific use cases such as counting, picking, and task tracking.
Our challenge was to design a system where these strategies cooperate across various mobile devices and operating systems without excessive computational overhead.
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Accelerate finding, picking, or counting workflows
Making multiple barcode scanning smarter
To batch scan barcodes reliably in real-world enterprise environments, the Scandit AI Engine addresses five challenges:
- Speed and resource balance: Every additional barcode in the camera’s field of view multiplies computational load. The Scandit AI Engine’s CV models use algorithmic optimization to interpret millions of pixels in milliseconds. This allows them to decode multiple barcodes in parallel, without increasing latency or draining battery life.
- Avoiding duplicates and false positives: Meeting business goals requires extremely high accuracy. The engine’s CV models identify barcodes uniquely, and track each one across frames. It works even if a barcode is tiny, printed on a curved surface, or looks identical to others nearby. This is crucial for workflows where many items share the same SKU and each one must be counted, not dropped.
- Tracking through motion: As the camera moves, the Scandit AI Engine remembers each barcode’s spatial position, even if it goes outside the field of view. This avoids forcing the user to recapture the same barcode and allows the software to count duplicates.
- Handling imperfect conditions: Low-light environments, curved, damaged, or tiny labels, and low-resolution cameras require adaptive decoding. All Scandit barcode scanning products include CV models that dynamically compensate for blur, glare, camera quality, and other degradations.
- Stabilizing AR overlays: The AR layer runs in sync with upstream algorithms, ensuring visual cues remain anchored to physical objects and do not flicker — a subtle yet critical factor in maintaining user confidence.
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Our overarching goal is to create a system that neither the developer nor the user has to worry about. The engine provides clear, easy-to-use APIs and UX-optimized workflows that act as a targeted intelligence layer between environment and users — without anyone having to worry about them.
“With Scandit’s bulk scanning capabilities, we have been able to reduce the time required to check selling prices by half.”
From AI to action: MatrixScan options
Scandit’s MatrixScan products package the Scandit AI engine’s capabilities into configurable workflows ready to deploy. Each one builds on the same foundation, providing developers and product managers with scalable options, ranging from fully packaged components to flexible APIs that allow fully customized integrations.
- MatrixScan Count: Lightning-fast, intuitive, and error-free scan and count solution for receiving goods, inventory, and cycle counting.
- MatrixScan Find: Scan multiple items and instantly highlight the right one using augmented reality (AR)
- MatrixScan Pick: Turn any scan into a visual, interactive checklist that makes following complex workflows consistent and efficient.
- MatrixScan Batch: Batch process barcodes and handle multi-code labels with unparalleled speed and accuracy.
- MatrixScan AR: Capture multiple barcodes and display information with customizable augmented reality (AR) overlays.
“The ability to batch scan from Scandit MatrixScan Count was huge... I had boxes set up vertically, some horizontal, some at an angle, and you could still just take your phone and it just picked everything up.”
Multiple barcode scanning needs collaborative technologies
The Scandit AI Engine brings intelligent perception, adaptive decision-making, and responsive UI to users’ fingertips.
To learn more about Scandit AI Engine-enabled products, explore our MatrixScan family of multiple barcode scanning solutions.
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