Beacon RSSI Motion Detection for Reliable Location Updates
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Solution Overview
Problem
Existing systems struggle to accurately determine the location and motion of low-cost beacon transmitters due to environmental changes and lack of motion information, leading to unreliable location estimates.
Innovation Solution
A method and apparatus that process received signal strength information to estimate the motion and location of beacon transmitters, adjusting processing windows based on motion state, using adaptive RSSI averaging windows and machine learning to enhance location determination accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If location determination is performed continuously without considering motion state, then location updates are provided at all times, but location accuracy deteriorates when device is moving due to signal strength variations
Solution Approach 1:
The system dynamically adjusts location determination behavior based on detected motion state. When motion is detected, the system suspends location updates to avoid inaccurate readings. When the device becomes stationary, location updates are resumed. This dynamic adaptation resolves the contradiction by making the system responsive to actual operational conditions rather than providing continuous updates regardless of device state.
Solution Approach 2:
The system uses motion detection feedback to control location determination operations. The motion detection module provides feedback about device movement status, which then modulates the location determination module's activity. This feedback mechanism ensures that location updates are only performed when reliable, eliminating the trade-off between continuous updates and accuracy.
2Measurement precision
If motion detection is added to the system, then location accuracy improves by filtering out motion-related errors, but device complexity increases
Solution Approach 1:
A motion detection module is introduced as an intermediary component between the signal strength measurement and location determination processes. This intermediate layer filters out motion-related signal variations before location calculation, preventing inaccurate location data from being generated. The intermediary approach adds precision without requiring fundamental redesign of the core location determination algorithm.
3Measurement precision
If processing window is extended to average signal strength measurements, then location accuracy improves, but response time deteriorates when device is moving
Solution Approach 1:
The processing window duration is dynamically adjusted based on motion state detection. When the device is detected to be moving, the processing window is shortened or suspended to reduce response time. When the device is stationary, the processing window is extended to provide accurate averaged measurements. This dynamic adjustment eliminates the trade-off between measurement accuracy and response time.
Data Source
AI summary
Methods and apparatus for processing and using signals transmitted by a device, e.g., a low cost beacon transmitter device, to facilitate making location determinations with regard to the transmitting device and/or making a decision of when or how to use location information generated based on received signals are described. In accordance with some features the processing performed on the received signal strength measurements is based on whether or not the device from which the signals are received is in motion. The size of a sample period used as a processing window when determining device location is based, in some embodiments, on the rate of motion. When and/or how to use location determinations are performed is also based on motion in some embodiments. Machine learning updates of location determination parameters, based on received signals, are disabled when the signals are from devices determined to be in motion.