Load Cell Weight Data Validation Using Door Sensor Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing inventory management systems in materials handling facilities face challenges in accurately determining item interactions due to erroneous weight data caused by air movement and thermal effects, leading to incorrect interaction data and resource wastage.
Innovation Solution
The implementation of load cells with door sensors and advanced data analysis techniques, such as correlation analysis and trajectory validation, to distinguish between valid and invalid weight data, ensuring accurate interaction data is derived.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If load cells are used to monitor inventory weight, then inventory tracking capability is improved, but measurement precision deteriorates due to air movement and thermal effects causing erroneous weight data
Solution Approach 1:
The patent introduces door sensors as intermediary devices that detect door opening/closing events and use these events to validate or filter weight data from load cells. The door sensor acts as a mediator between the physical environment (door state) and the measurement system (load cell data), allowing the system to distinguish between legitimate weight changes and those caused by air movement during door operations.
Solution Approach 2:
The system implements feedback by continuously monitoring door sensor states and using this information to validate weight data in real-time. When the door sensor detects an opening or closing event, the system flags corresponding weight data as potentially erroneous and excludes it from interaction detection, creating a closed-loop validation mechanism that improves reliability.
2Measurement precision
If advanced data analysis techniques are implemented to filter erroneous data, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the data validation process into distinct components: door sensor event detection, weight data timestamp correlation, and validity determination. By dividing the complex validation task into separate, manageable segments that can be independently processed, the system achieves high measurement precision without proportionally increasing overall device complexity.
Solution Approach 2:
The system performs preliminary action by pre-establishing correlation rules between door sensor events and weight data timestamps. Instead of implementing complex real-time analysis, the system pre-defines validation logic that simply checks whether weight data falls within a predetermined time window around door events, significantly reducing processing complexity while maintaining accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces processing of erroneous data, improves resource utilization, and maintains accurate inventory tracking by filtering out noise from weight data, enhancing the overall efficiency of inventory management systems.
Implementation Method 1
A plurality of load cells at the shelf are configured to generate weight data
Implementation Method 2
A door sensor in the fixture is configured to generate door sensor data indicative of a configuration of the door
Data Source
AI summary
Shelves or other fixtures may be used to hold items at a facility. Load cells at the shelf may be used to acquire weight data indicative of changes as items are added or removed from the shelf. The shelves may be part of a fixture that includes a door that results in air movement with respect to the shelves when opened or closed. This air movement may produce weight data that is erroneously indicative of an event, such as a pick or place, even when no actual event has taken place. Weight data from load cells of a shelf may be analyzed to determine a trajectory associated with changes in the weight data over time. A portion of the space may be designated as being associated with invalid weight data. If the trajectory avoids this portion of the space, the weight data may be deemed valid.