Motion-Aware Object Location Tracking With Adaptive Averaging
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Solution Overview
Problem
Current wireless tracking systems, such as RFID-based systems, suffer from location accuracy issues, particularly when tracking moving objects, leading to misleading data and operational inefficiencies due to inaccuracies in determining movement speed and direction, and the creation of blind zones when objects move between different receiver coverage areas.
Innovation Solution
A system that processes a stream of signals from multiple tag readers, determines the motion status of objects, and calculates true locations using different processes based on motion status, either a short computing window for moving objects or a long computing window for stationary objects, to improve location accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If location averaging is calculated over a short amount of time before reporting, then the system responds quickly to location changes, but the time span is insufficient to account for the same tag being read by multiple readers at the same time, leading to location accuracy issues
Solution Approach 1:
The system dynamically adjusts the time window for location averaging based on the motion status of the object. For stationary objects, a longer time window is used to average out reading variations from multiple readers. For moving objects, a shorter time window is used to capture current position while filtering out historical data that would skew the average. This dynamic adjustment resolves the contradiction between response time and accuracy.
Solution Approach 2:
The system changes the parameter of time window duration based on the detected motion status of the tracked object. When motion is detected, the system switches to a shorter averaging window; when stationary, it uses a longer window. This parameter change allows the system to optimize both response time and location accuracy for different operational states.
2Device complexity
If the system uses a single location calculation process for all objects, then the system structure is simple, but location accuracy deteriorates when objects move between coverage areas of different readers
Solution Approach 1:
The system segments the location calculation process into two distinct processes: one for stationary objects and one for moving objects. This segmentation allows each process to be optimized for its specific use case - the stationary process uses longer time windows to average readings from multiple readers, while the moving process uses shorter windows to capture current position. This resolves the contradiction by making the system more complex only where necessary to improve accuracy.
Solution Approach 2:
The system uses feedback from motion detection to determine which location calculation process to apply. By continuously monitoring whether an object is moving or stationary and adjusting the calculation method accordingly, the system achieves high location accuracy across different scenarios without requiring manual intervention or complex configuration.
3Duration of action of stationary object
If the system tracks moving objects using standard RFID reading, then the tracking process is continuous, but location inaccuracies result in errors in determining parameters such as movement speed and direction
Solution Approach 1:
The system applies different location averaging time windows based on the motion status of the object. For moving objects, a shorter time window is used to capture the current position without being skewed by historical data from previous locations. This dynamic approach maintains tracking continuity while improving the accuracy of movement parameter calculations by using appropriate time spans for different motion states.
Data Source
AI summary
Methods and System for tracking an object including steps of receiving a stream of signals of an object from a plurality of tag readers, each signal within the stream of signals comprises a first raw location, a second raw location, and a timestamp, determining a first motion status of the object using the first raw location, assigning the object to a first process or a second process based on the first motion status, in response to the assignment to the first process, calculating a first or second location using the corresponding raw locations in a corresponding process, publishing the calculated location as a true location, and associating the true location to the object.