Indoor Sensor Data Tagging Using SLAM-Based Path Estimation
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Solution Overview
Problem
Existing methods for providing location-based services indoors, such as those using GPS signals, face challenges in areas where signals are weak or unavailable, like between high buildings or inside buildings, requiring pre-existing indoor map information for effective indoor wireless positioning.
Innovation Solution
A method and system utilizing a data collecting apparatus with first and second sensors that perform timestamping, simultaneous localization and mapping (SLAM) to generate indoor map data, detect loop closures, and tag sensing locations to sensor data, allowing for the creation of indoor maps and accurate location estimation without pre-existing map information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS signal is used for location-based service, then location information can be obtained in open areas, but it becomes very difficult to measure location in GPS signal gray areas such as between high buildings or inside buildings
Solution Approach 1:
The patent introduces an intermediary system consisting of access points and mobile terminals that mediate location measurement in indoor environments where GPS signals are unavailable. The access points serve as intermediary nodes to establish wireless connections and enable positioning through alternative methods such as triangulation or time-of-flight measurements, thus resolving the contradiction between GPS reliability and indoor adaptability
Solution Approach 2:
The patent changes the measurement parameters from GPS satellite-based signals to indoor wireless signal parameters such as signal strength, time of arrival, or angle of arrival. By transforming the location measurement approach from external satellite signals to internal wireless infrastructure signals, the system achieves both reliable location measurement and adaptability to indoor environments
2Measurement precision
If indoor map information is pre-existing, then indoor wireless positioning can be performed accurately, but the system requires prior preparation and infrastructure setup
Solution Approach 1:
The patent performs preliminary actions by having mobile terminals collect access point information and generate indoor map data before actual positioning operations. This pre-collection of reference information enables subsequent accurate positioning without requiring complex manual setup, thus achieving both precision and reduced setup complexity
Solution Approach 2:
The system enables self-service by allowing mobile terminals to automatically collect access point information, generate indoor maps, and perform positioning without requiring external intervention or pre-existing detailed maps. The system serves itself by using the mobile terminal's own sensors and processors to create and utilize location data, reducing overall system complexity
3Measurement precision
If sensor data is collected with timestamping and location tagging, then accurate location-based services can be provided, but time and cost for data collection increase
Solution Approach 1:
The patent merges multiple operations into a single integrated process where mobile terminals simultaneously perform sensing, timestamping, and location tagging in real-time. By combining these functions into unified operations rather than sequential steps, the system achieves accurate location data while minimizing data collection time
Solution Approach 2:
The system maintains continuous useful action by performing location data collection, timestamping, and tagging operations continuously as mobile terminals move through the environment. This continuous real-time processing eliminates idle time between operations and ensures accurate location information is captured without interruption, thus achieving precision without excessive time loss
Data Source
AI summary
The data collecting method includes: collecting first and second sensor data respectively through a first and a second sensors while a data collecting apparatus moves within a target area, and tagging a first and a second timestamp values respectively to the first and the second sensor data; generating map data of the target area and location data at a point of time corresponding to the first timestamp value, based on the first sensor data; generating map information of the target area based on the map data, and generating moving path information on the map based on the location data; and estimating a sensing location at a point of time corresponding to the second timestamp value based on the moving path information, and tagging the sensing location to the second sensor data.