Mesh Network Node Triangulation for Autonomous Location Updates
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Solution Overview
Problem
Existing mesh networks face challenges in accurately and efficiently determining the geographical location of network nodes, particularly in large networks with millions of nodes, where manual tracking is time-consuming and error-prone, and node locations can change frequently due to construction or equipment upgrades.
Innovation Solution
Nodes in the mesh network communicate with neighboring nodes to identify primary nodes with known locations, calculate distances using methods like time-of-flight or signal strength, and apply triangulation to determine their own locations, which can then be used to update or correct their geographical positions, reducing the need for human intervention and communication bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking of node locations is used, then location information can be obtained, but the process becomes time-consuming and error-prone for large networks with millions of nodes
Solution Approach 1:
The patent enables nodes to automatically determine their own locations through self-organizing triangulation processes. Nodes exchange distance information with neighbors and autonomously calculate positions without human intervention, transforming manual tracking into an automated self-service system that eliminates time consumption and human error while maintaining location accuracy
Solution Approach 2:
The patent divides the network into primary nodes (with known locations) and secondary nodes (determining locations). This segmentation allows the system to process location determination in manageable units, where each node independently calculates its position based on distances to primary nodes, enabling scalable automation across millions of nodes without overwhelming central systems
2Measurement precision
If GPS chips or Wi-Fi components are installed on all nodes to determine location, then accurate location information can be obtained, but the device complexity and cost increase significantly
Solution Approach 1:
The patent extracts the location-determining components (GPS chips, Wi-Fi components) from the majority of nodes, retaining them only in primary nodes. Secondary nodes determine locations through mathematical triangulation using distance measurements to primary nodes, eliminating the need for expensive hardware in most nodes while preserving location determination accuracy through algorithmic computation
Solution Approach 2:
The patent creates virtual location information for secondary nodes through triangulation calculations, copying the location-determination capability from primary nodes equipped with GPS/Wi-Fi. Instead of physically installing hardware in every node, the system replicates location knowledge across the network through information exchange and mathematical computation, achieving the same functional outcome with simpler devices
3Reliability
If manual tracking of node locations is used, then location data can be maintained, but the process is error-prone when node locations change due to construction or equipment upgrades
Solution Approach 1:
The patent implements a dynamic location determination system where nodes continuously recalculate positions based on current distance measurements to primary nodes. When nodes move due to construction or upgrades, the system automatically detects position changes through updated distance data and recalculates locations in real-time, maintaining reliability without manual intervention and enabling automatic adaptation to changing network conditions
Solution Approach 2:
The patent establishes a feedback mechanism where nodes continuously exchange distance information with primary nodes and adjust their recorded locations based on calculated positions. This closed-loop system automatically detects and corrects location changes, providing reliable up-to-date location data that adapts to network modifications through continuous measurement and adjustment rather than static manual records
4Loss of information
If central systems are used to collect and process location information from all nodes, then comprehensive location data can be obtained, but the communication overhead and bandwidth requirements increase significantly
Solution Approach 1:
The patent segments the location determination process into distributed calculations at individual nodes rather than centralized processing. Each node independently computes its position using local distance measurements to primary nodes, eliminating the need to transmit complete location datasets to a central system. Only essential distance information and final location results are exchanged, dramatically reducing communication overhead while maintaining complete location data across the network
Solution Approach 2:
The patent enables each node to perform local location calculations using locally available distance information from primary nodes. Instead of relying on a central system to process all location data, nodes autonomously determine their positions using local computations and minimal information exchange, reducing communication bandwidth requirements while ensuring comprehensive and accurate location information is available network-wide
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 method enhances the efficiency and accuracy of geographical location determination for nodes in mesh networks, providing up-to-date and accurate location information without relying on central systems, thereby reducing communication overhead and enabling automatic, periodic updates.
Implementation Method 1
calculates its distance to each of these primary nodes
Implementation Method 2
apply triangulation to determine their own locations
Data Source
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AI summary
Technologies for autonomously determining location information of a network node in a mesh network are provided. For example, a mesh network includes primary nodes whose locations are known and secondary nodes whose locations are to be determined. A secondary node is configured to identify in-range primary nodes among the primary nodes that are in the communication range of the secondary node, and determine whether the number of the in-range primary nodes is above a threshold. If the number of the in-range primary nodes is above the threshold, the secondary node further determines a distance between the secondary node and each of selected in-range primary nodes, and calculates a location of the secondary node based on the distances and the respective locations of the selected in-range primary nodes. The secondary node further transmits the calculated location to a headend system over the mesh network.