Indoor Navigation via Crowdsourced Sensor Data
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Solution Overview
Problem
Existing smartphone navigation systems face challenges in indoor locations with weak GPS signals, requiring costly and time-consuming processes to create databases and indexes for alternative navigation methods like WiFi and Bluetooth signals.
Innovation Solution
Crowdsourced data collection using client devices to record accelerometer readings, wireless network access location information, and timestamps to generate walkable paths within indoor spaces, which are then processed to provide navigation assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional database creation methods are used for indoor navigation, then navigation accuracy can be improved, but the time and cost required for surveying and data collection increases significantly
Solution Approach 1:
The system enables users to automatically collect and contribute navigation data during their normal movements through the building. Each user's device self-records GPS coordinates, accelerometer data, and wireless signal information, eliminating the need for professional surveyors to manually collect data. This transforms the data collection process from a labor-intensive professional service to an automated user-driven process.
Solution Approach 2:
Instead of creating original survey data through manual measurement, the system collects copies of navigation data from multiple users' devices. These copies include GPS coordinates, accelerometer readings, and wireless signal fingerprints that are automatically recorded during normal device usage. The aggregated copies form a comprehensive navigation database without requiring direct measurement by professionals.
2Reliability
If professional surveying is conducted to create navigation databases, then the quality of navigation data improves, but the cost and complexity of the process increases
Solution Approach 1:
The system makes mobile devices perform multiple functions: they serve as both consumer navigation tools and data collection instruments. The same GPS receiver, accelerometer, and wireless interface used for normal device operation are also utilized to collect navigation survey data, eliminating the need for specialized surveying equipment and reducing overall system complexity.
Solution Approach 2:
The navigation database is built through automated data collection from users' own devices during their normal activities. The system self-organizes and processes the collected data to create reliable navigation information, reducing the need for complex professional surveying procedures while maintaining data quality through aggregation and validation of multiple sources.
3Measurement precision
If extensive database creation is performed for indoor navigation, then navigation coverage and accuracy improve, but the time and resources required for database generation increase
Solution Approach 1:
Data collection occurs continuously as users move through the building during their normal activities, rather than requiring scheduled surveying operations. The system continuously records GPS coordinates, accelerometer data, and wireless signal information in the background, accumulating navigation data over time without interrupting users or requiring dedicated surveying periods.
Solution Approach 2:
The system rapidly accumulates navigation data by collecting copies from numerous users simultaneously. Each user's device generates multiple data points during normal movement, and these copies are aggregated to quickly build comprehensive coverage of the indoor space, dramatically increasing the productivity of database creation compared to sequential professional surveying.
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
Enables efficient and cost-effective indoor navigation by leveraging user-generated data to identify walkable paths and provide navigation assistance without the need for extensive database creation.
Implementation Method 1
recording a set of route data including a timestamp, accelerometer data
Implementation Method 2
a wireless network signal fingerprint comprising one or more wireless network signal beacon identifiers and associated signal strengths
Data Source
AI summary
Aspects of the disclosure relate generally to using crowd sourced information to generate walkable paths through indoor spaces. More specifically, aspects relate to recording data such as accelerometer readings, wireless network or other beacon signal information, and timestamps while a client device moves within an indoor space. If the user reaches a destination within the indoor space, the client device may prompt the user for information about the destination. The information received and recorded by the client device may be sent to a server computer for further processing. The server may use the information to identify walkable paths within the indoor space. This information in turn may be used in various ways, such as to provide navigation assistance to users though the indoor space.