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Imagine a warehouse worker instantly capturing the single barcode they want from a shelf cluttered with packages. Or a customer scanning shelf labels in-store and getting exactly the product information they’re looking for, rather than unwanted information from products nearby.
In the real world, barcodes don’t appear neatly one by one. In places such as grocery aisles or warehouses, they’re clustered together. And when there are multiple codes in your field of view, scanning just the one you need, the first time, isn’t always easy.
New AI-powered barcode scanning in the SDK 7.0 now gives any app the power to automatically detect the barcode a user wants to scan. Rather than frustrating your users with unwanted scans, it helps them get it right every time.
The result? Fewer errors and drastically improved efficiency. Compared to apps without this feature, businesses see up to a 100% reduction in unwanted scans. This can double order picking speed for grocers, as an example.
The era of context-based scanning is here
Building on 10 billion scans annually and a decade of designing scanning experiences, we know that solving the challenges of complex enterprise environments means going beyond traditional measures of scanning performance — such as decoding speed and accuracy.
Real-world factors such as label distance, suboptimal user behavior, and barcodes clustered in close proximity cause challenges for barcode scanning software. How does it know which barcode the user wants to scan? And if the software doesn’t know, how can it help users scan more accurately?
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The answers lie in connecting the digital world to the broader physical environment through context-based scanning. In the SDK 7.0, we've applied advanced AI algorithms to the device’s camera feed to analyze multiple signals beyond just detecting and decoding barcodes:
- Environment: Understanding the number and position of all barcodes in the camera’s field of view, as the user moves.
- Target: Analyzing the characteristics of all barcodes in the field of view to extract the one the user wants.
By combining these signals, Scandit's barcode scanning can now consistently detect and capture the barcodes users want to scan, even when aiming is imperfect or multiple barcodes are in the field of view.
A shipping and receiving clerk can scan the right barcode from several boxes on a pallet and move on. Retail workers spend less time thinking and moving their devices around a shelf, when their scanning tools instantly extract the one barcode they need for accurate restock counts.
As a consumer-facing app with a community of over 60 million users, an optimal, intuitive, and friction-free scanning app is essential for Yuka. That frictionless UX is often threatened by unintentional scans, a result of the environments Yuka users scan products in, such as the store, pantry, or fridge, where barcodes are heavily prevalent. With its advanced algorithms, Scandit ... helps eliminate this friction by understanding which barcode the user intends to scan, leading to fewer errors and more accurate scanning.
François Martin, Co-Founder and CTO of Yuka
How you can try AI-powered barcode scanning
AI-powered barcode scanning is enabled by default in SparkScan, our pre-built component that gives you top performance and optimized scanning UX in just a few lines of code. Deployable in minutes, you spend less time customizing scanning behavior, and your users get fast, accurate scanning at their fingertips.
It's also available across our other single barcode scanning products, including Barcode Capture for building fully customized barcode scanning.
Rewiring barcode scanning for today’s businesses
The race to capture value from barcode scanning must include all the variables. Accounting for the scanning environment and user intent on top of barcode detection and decoding creates a faster, more effective experience. This holistic approach makes compensating for unwanted scans a thing of the past.
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