Wireless Sensor Node Localization via Dynamic Mesh-Tree Switching
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Solution Overview
Problem
Existing wireless sensor network localization systems face challenges in low-power environments, accuracy in indoor settings, and tree-like network architectures, where triangulation is not feasible due to limited path lengths and precision issues in determining node locations, especially in the presence of indoor obstructions like walls.
Innovation Solution
A system that configures a wireless network architecture to switch between tree and mesh structures for communication, using RF circuitry with multiple antennas for bi-directional communications, employing frequency channel overlapping, stepping, multi-channel wide band, and ultra-wide band communications for time of flight and signal strength techniques to accurately determine node locations, and periodically re-triangulate when changes are detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If triangulation is used for localization in tree-like networks, then location estimation can be performed, but sufficient path lengths between node pairs cannot be established
Solution Approach 1:
The network dynamically switches between tree architecture for communications and mesh architecture for localization. The system adapts its topology based on the operational mode: using tree structure during normal communications and temporarily forming mesh structures when localization is needed to enable sufficient path lengths for triangulation
Solution Approach 2:
The localization process is segmented into discrete phases where specific node pairs are selected to establish measurement paths. The system divides the network into active measurement paths and inactive communication paths, allowing triangulation to be performed on selected subsets of nodes without disrupting overall network communications
2Measurement precision
If repetitive transmission bursts are used for fast and accurate localization, then localization speed and accuracy improve, but power consumption increases
Solution Approach 1:
Localization is performed periodically rather than continuously. The system schedules localization events at intervals and uses the mesh architecture to establish measurement paths only when needed. This periodic operation allows nodes to enter low-power states between localization events while still maintaining accurate location information
Solution Approach 2:
The system discards the tree architecture's power efficiency during localization events and recovers it by switching back to tree architecture for communications. The temporary mesh configuration is discarded after localization is complete, allowing nodes to return to low-power operation modes
3Use of energy by moving object
If narrow-band communications are used for all operations, then power consumption is reduced, but localization accuracy and detection of indoor obstructions deteriorate
Solution Approach 1:
Different communication bandwidths are applied to different functional requirements. Narrow-band communications are used for routine data transmission to conserve power, while wide-band communications are locally applied during localization events to achieve high measurement precision. Each communication mode is optimized for its specific purpose
Solution Approach 2:
The system changes the bandwidth parameter of communications based on operational mode. During normal operation, narrow-band parameters are used for power efficiency. During localization, the system switches to wide-band or ultra-wide-band parameters to enable accurate time of flight and signal strength measurements for determining node locations and detecting walls
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables accurate, low-power, and context-aware localization in indoor environments by combining signal strength and time of flight measurements, improving detection of walls and room context while conserving energy through selective use of high and low frequencies, and reducing spurious estimates from reflected signals.
Implementation Method 1
radio frequency (RF) circuitry including multiple antennas to transmit and receive communications
Implementation Method 2
measuring time of flight for wireless transmission between nodes to estimate distance
Implementation Method 3
measuring incident signal strength and using this information to estimate distance between transmitting and receiving nodes
Data Source
AI summary
Systems and methods for determining locations of wireless sensor nodes in a network architecture having mesh-based features are disclosed herein. In one example, a computer-implemented method for localization of nodes in a wireless network includes causing, with processing logic of a hub, the wireless network having nodes to be configured as a first network architecture for a first time period for localization. The method further includes determining, with the processing logic of the hub, localization of at least two nodes using at least one of frequency channel overlapping communications, frequency channel stepping communications, multi-channel wide band communications, and ultra-wide band communications for at least one of time of flight and signal strength techniques. The method further includes causing the wireless network to be configured in a second network architecture having narrow-band communications upon completion of localization.