Modular Bin Inventory System with Single-Row Sensor Configuration
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Solution Overview
Problem
Existing inventory management systems require a dense and costly array of sensors to accurately monitor objects of varying shapes and sizes on shelves, leading to inefficiencies in resource allocation and increased complexity, with a tradeoff between accuracy and cost.
Innovation Solution
The implementation of adjustable bin modules with a single row of sensors along a center axis, allowing for optimal positioning and adjustable dividers to accommodate different object sizes, coupled with a support plate for modular integration, reduces the number of sensors needed and simplifies the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a dense array of sensors is used to monitor objects of varying shapes and sizes, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The system divides the shelf into multiple zones with sensor arrays, where each zone has its own sensors mounted on the shelf surface. This segmentation allows localized monitoring with fewer sensors per zone while maintaining overall detection accuracy across the entire shelf area.
Solution Approach 2:
The sensors are designed to perform multiple functions: detecting object presence, determining object location, and identifying object removal or addition. This multi-functionality eliminates the need for separate sensor types for different detection purposes, reducing overall system complexity.
2Measurement precision
If more sensors are deployed to cover various object shapes and sizes, then measurement precision is improved, but loss of substance increases
Solution Approach 1:
The system implements varying sensor densities in different shelf zones based on local requirements. High-value or frequently monitored areas have denser sensor arrays, while less critical areas have sparser arrays. This local optimization reduces total sensor quantity while maintaining necessary detection precision where it matters most.
Solution Approach 2:
The sensors are positioned to detect a broader range of object characteristics than strictly necessary, using partial overlap in detection coverage. This allows fewer sensors to effectively monitor multiple object types and sizes by capturing sufficient data for accurate status determination without requiring complete coverage of every possible object dimension.
3Device complexity
If a fixed sensor array is used, then device complexity is reduced, but adaptability decreases
Solution Approach 1:
The system uses adjustable sensor positions and reconfigurable detection zones that can be dynamically modified to match different shelf layouts and product arrangements. Sensors can be repositioned along the shelf surface, and detection parameters can be adjusted to accommodate varying object sizes and shapes, providing adaptability without requiring complete system redesign.
Data Source
AI summary
A modular inventory management system is disclosed herein that includes a bin module. The bin module may include a module base, a sensor configuration, and a divider. The module base may have a first lateral edge, a second lateral edge, and a top surface that connects the first lateral edge to the second lateral edge. The sensor configuration may be arranged on the module base between the first lateral edge and the second lateral edge. The sensor configuration may include a plurality of sensor elements that are arranged in a single row on a center axis of the module base and configured to sense whether one or more objects are positioned on the top surface of the module base. The divider may be situated at the first lateral edge and may be configured to slide laterally with respect to the module base to adjust a width of the bin module.