Sensor Layout Generation Using Performance Feedback
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Solution Overview
Problem
The deployment of location tracking sensors in facilities, such as retail and warehouse settings, is a time-consuming process due to the need for expert staff to determine optimal sensor placement, and existing systems lack automation for optimizing sensor layouts across multiple facilities, leading to suboptimal performance and inefficiencies.
Innovation Solution
A computing device is used to receive facility maps, generate layout data for sensor placement, and collect performance metrics to update a primary layout generator, enabling semi-automated generation of sensor layouts and improving the efficiency of location tracking systems by reducing reliance on expert staff and optimizing sensor placement based on performance data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If expert staff manually determine sensor placement, then sensor layout accuracy is improved, but deployment time and cost increase
Solution Approach 1:
The system creates a digital twin or virtual model of the facility that mirrors the physical space. This virtual model allows automated algorithms to simulate and optimize sensor placements without requiring manual expert intervention in the physical space, thereby maintaining accuracy while reducing deployment time
Solution Approach 2:
The patent replaces the manual mechanical process of expert staff physically measuring and marking sensor locations with an automated computational system that uses algorithms to determine optimal placements based on facility geometry and coverage requirements
2Productivity
If automated layout generation is implemented, then deployment efficiency is improved, but layout accuracy may deteriorate
Solution Approach 1:
The system incorporates feedback mechanisms where performance data from deployed sensors is collected and used to refine and retrain the automated layout generation algorithms. This continuous feedback loop allows the system to learn from real-world performance and improve accuracy over time while maintaining high deployment efficiency
Solution Approach 2:
The system performs preliminary simulations and optimizations in a virtual environment before actual deployment. By pre-calculating optimal sensor placements in the virtual model and validating them against coverage requirements, the system ensures high accuracy is achieved before physical installation occurs
3Manufacturing precision
If performance metrics are collected and used to update the layout generator, then future sensor placements are improved, but data processing complexity increases
Solution Approach 1:
The system uses a multi-functional data processing platform that handles various tasks including data collection, performance metric calculation, algorithm training, and validation. This universal platform consolidates multiple functions into a single system, managing complexity while enabling continuous improvement of sensor placement accuracy
Data Source
AI summary
Layout generation for location-tracking sensors is disclosed herein. An example method in a computing device includes: receiving a map defining a set of features of a facility; obtaining layout data corresponding to the facility, the layout data defining, for each of a plurality of location tracking sensors, a location in a facility coordinate system; in response to deployment of the location tracking sensors in the facility according to the layout data, obtaining a performance metric for each of the location tracking sensors; and updating a primary layout generator according to the map, the layout data, and the performance metrics.