Adaptive Spatial Resolution for Retail Sensor Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Systems that track positions of people and products in retail stores face challenges in processing vast amounts of sensor data in real-time, leading to inefficiencies when accuracy is set too high, causing delays in location identification, and when set too low, resulting in less useful position information.
Innovation Solution
A method that dynamically adjusts spatial and temporal resolution based on system performance, reducing spatial resolution when the system falls behind in processing sensor data and increasing it when performance improves, while also reducing temporal resolution as a last resort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high spatial resolution is used to determine locations of items, then measurement precision is improved, but processing speed deteriorates causing delays in location identification
Solution Approach 1:
The system dynamically adjusts spatial resolution based on real-time performance monitoring. When the system falls behind in processing sensor data, the spatial resolution is reduced to increase processing speed. When the system keeps pace with data reception, spatial resolution is increased to improve measurement precision. This dynamic adjustment resolves the contradiction by making spatial resolution variable rather than fixed.
Solution Approach 2:
The patent changes the spatial resolution parameter adaptively based on system performance. The processor monitors whether it can keep up with the reception rate of sensor messages and adjusts the spatial resolution parameter accordingly - using higher resolution when processing capacity allows, and lower resolution when processing capacity is exceeded, thus resolving the speed-precision tradeoff.
2Measurement precision
If high spatial resolution is used to determine locations of items, then measurement precision is improved, but productivity deteriorates as the system cannot process sensor values fast enough
Solution Approach 1:
The system makes spatial resolution dynamic, adjusting it in real-time based on whether the processor can keep up with sensor data reception. When processing throughput is insufficient, spatial resolution is reduced to increase productivity. When throughput is sufficient, spatial resolution is increased to maintain measurement precision. This resolves the contradiction between precision and productivity.
Solution Approach 2:
The system implements feedback by monitoring performance metrics (whether the processor keeps up with sensor data reception) and using this feedback to adjust spatial resolution. This closed-loop control ensures that spatial resolution is optimized for both measurement precision and processing throughput based on real-time system state.
3Measurement precision
If the system processes sensor data at high resolution, then measurement precision is improved, but loss of time occurs as the identification rate cannot keep up with the reception rate
Solution Approach 1:
The system dynamically adjusts spatial resolution to prevent time loss. When the identification rate falls behind the reception rate, spatial resolution is reduced to accelerate processing and reduce the time gap. When the system keeps pace, spatial resolution is increased to maintain precision. This dynamic adjustment eliminates the tradeoff between precision and time loss.
Solution Approach 2:
The patent changes the spatial resolution parameter adaptively based on the time gap between data reception and identification. By monitoring whether sensor messages are being processed fast enough, the system adjusts spatial resolution to maintain optimal processing speed, thus preventing accumulation of unprocessed data and reducing time loss while preserving precision when possible.
Data Source
AI summary
A method includes monitoring performance of a system that determines locations of items in a retail store based on sensor values from a collection of sensors in the retail store. When the performance is insufficient to process the sensor values as the sensor values are received, a spatial resolution used to determine the locations of the items in the retail store is reduced.