Automated Planogram Generation Using Distributed ESL Radio Signals
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Solution Overview
Problem
Brick-and-mortar shopping stores face challenges in efficiently generating and updating planograms due to manual processes, which are time-consuming and quickly become outdated, and in tracking shopper behavior on a large scale.
Innovation Solution
A large-scale distributed radio system using electronic sign labels (ESLs) with multi-protocol radio capabilities that transmit and receive radio signals to collect and provide information about products and customer locations, enabling automated planogram generation and shopper behavior tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual processes are used to generate and update planograms, then implementation flexibility is maintained, but time consumption increases and planogram currency deteriorates
Solution Approach 1:
The patent replaces manual mechanical processes with an automated radio-based system. ESLs with radio transceivers automatically transmit product location data to a central server, which generates and updates planograms without manual intervention. This substitution eliminates time-consuming manual data collection and processing while maintaining implementation flexibility through programmable system configuration.
Solution Approach 2:
The system enables self-service automation where ESLs autonomously collect and transmit their own product location information. The central server automatically processes this data to generate and distribute updated planograms to relevant devices, eliminating the need for manual data entry and processing while keeping the system adaptable through configurable parameters.
2Measurement precision
If manual tracking of shopper behavior is implemented, then system complexity is minimized, but measurement precision and scalability deteriorate
Solution Approach 1:
The patent implements multi-functional ESLs that serve both their traditional pricing/information display function and act as radio transceivers for collecting shopper behavior data. This universal approach allows the same infrastructure to support both product information delivery and customer analytics, improving measurement precision without proportionally increasing system complexity.
Solution Approach 2:
The central server acts as an intermediary that receives radio signals from ESLs and customer devices, processes the data to extract shopper behavior patterns, and generates heatmaps and analytics. This intermediary layer enables precise tracking and scalable analysis while managing system complexity by centralizing data processing logic.
3Reliability
If frequent planogram updates are performed manually, then planogram currency is improved, but labor requirements and error probability increase
Solution Approach 1:
The system enables continuous automatic updating of planograms through persistent radio communication between ESLs and the central server. As product locations change, ESLs continuously transmit updated data, triggering automatic planogram regeneration and distribution. This continuous action maintains high planogram currency without manual intervention, reducing operational complexity and error rates.
Solution Approach 2:
The system implements feedback loops where the central server receives real-time location data from ESLs, compares it against the current planogram, and automatically triggers updates when discrepancies are detected. This feedback mechanism ensures planogram currency is maintained reliably while automating the update process, thereby simplifying operations and reducing human error.
Data Source
AI summary
A method may include obtaining, by a radio receiver, radio signals from electronic sign labels (ESLs) in which each ESL of the plurality of ESLs is associated with a respective product in a shopping store and is configured to operate in a transmission modality on one or more radio frequency protocols. The method may include determining a location of each ESL based on the radio signals obtained from the plurality of ESLs and determining locations of one or more products based on the location of each of the ESLs and an association between each of the ESLs with the respective product. The method may include generating a planogram indicating the locations of the products.