Automated Solution to Validate Shelf Layouts in Stores
Description:
ShopView leverages computer-vision technology for retailers that want to gain a competitive edge in product placement auditing. The solution relies in a drivable platform equipped with a high speed flash synced with multiple digital cameras, aided by a light softener, a laptop and a couple of sensors to:
> Photograph shelves – controlling reflections and minimizing blur in high-resolution;
> Recognize the positioning of real products – via information and image processing algorithms;
> Evaluate product placement – validating against target planograms;
> Reporting errors to store manager in aisles covered by the Buggy’s imaging system.
Other features include:
> Layout management of multiple stores;
> Map of aisles in floorplan;
> Panoramic full-length views;
> Label detection;
> European Article Number (EAN) decoding;
> Multiple-camera matching.
The former ShopView project has finished having its R&D objectives accomplished. Although it is capable of doing the job with a considerable degree of reliability, some challenges and limitations were identified through the execution of the project: Automatic Integration, Usability, Auditing features should be completed with Correction features – to be able to act upon the information created by ShopView, e.g. for restocking, rearranging and optimizing shelf product placement.
FhP-AICOS proposed to address the identified issues in ShopView, and complete the validation of the solution throughout a long-term pilot, with demonstrators all over the world: the ShopView2Market.
Partners:
WeDo Consulting - Sistemas de Informação (coordinator); Sonae Modelo Continente.
Outcome:
ShopView2Market solution validated with high (7) Technology Readiness Level, with enough maturity for product roadmap and commercial use, which means:
> Demonstrations without critical failures in operational environment;
> Easy installation and configuration;
> Fully integration with retailer business model;
> Functionalities adapted to user expectations.
Consult the project's Spec Sheet here:
Co-funded by:
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