RFID Sensor Placement via Neighborhood Graph
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Solution Overview
Problem
Existing RFID systems require a large number of expensive readers to efficiently locate objects with tags, making it economically inefficient to determine the location of an object using a small number of readers.
Innovation Solution
An object tracking apparatus and method that utilizes a neighborhood graph with black and white nodes to determine the location of an object by communicating with multiple sensors, where the graph represents the space and the sensors' coverage areas, allowing for the efficient placement of sensors to create a trackable symbolic space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large number of RFID readers are deployed to accurately determine object location, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The space is segmented into multiple subspaces, and the accessibility graph is segmented into black nodes (subspaces) and white nodes (sensor placement locations). This segmentation allows the system to track objects by determining which subspace they are in, rather than requiring continuous coverage by numerous sensors throughout the entire space.
Solution Approach 2:
The accessibility graph serves as an intermediary data structure that mediates between sensor readings and object location determination. The graph encodes spatial relationships and sensor coverage areas, allowing the system to infer object location from limited sensor data without requiring dense sensor deployment.
2Reliability
If sensors are densely deployed to ensure continuous object tracking, then reliability is improved, but loss of substance increases due to higher cost
Solution Approach 1:
The accessibility graph is constructed in advance with pre-calculated sensor coverage areas (white nodes) and subspace relationships (black nodes). This preliminary structuring of spatial information allows the system to maintain reliable tracking with fewer sensors, as the graph already encodes the optimal sensor placement and coverage relationships.
3Measurement precision
If the accessibility graph is constructed with many white nodes for complete coverage, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The accessibility graph applies local quality by associating each white node with a specific sensor and its coverage area, and each black node with a specific subspace. This localized representation allows the system to achieve accurate location determination by focusing computational effort on relevant local relationships rather than processing global sensor data from all sensors.
Data Source
AI summary
The apparatus for tracking an object and the method thereof and the method for locating a sensor are described. The subject object tracking apparatus comprises an interface receiving sensor information and object information from a sensor communicated with an object; a first storing part successively storing sensor information in chronological order; a second storing part storing a neighborhood graph displaying an object space; and a location determining part determining a location of an object using sensor information and a neighborhood graph. According to the present invention, an accessibility graph corresponding to a space is generated and a location of a sensor is determined on an accessibility graph, thereby effectively locating a sensor and tracking an object.