Built-Environment Localization Using Differential Motion
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Solution Overview
Problem
Existing localization systems struggle to provide accurate positioning in built environments due to signal interference and require continuous communication with multiple fixed devices, failing when obstacles are present, and existing wireless technologies like GPS, GSM, and AGPS are inadequate in indoor settings.
Innovation Solution
A system utilizing differential motion sensors and machine-learning algorithms, such as neural networks, to recognize voluntary movement patterns without external references, enabling topological localization by analyzing differential movement data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wireless communication technologies (GPS, GSM, AGPS) are used for localization, then localization can be achieved in outdoor environments, but accuracy and reliability deteriorate in built environments due to signal interference and obstacles
Solution Approach 1:
The patent replaces wireless communication-based localization systems with an inertial measurement system using accelerometers and gyroscopes. This mechanical/sensor-based approach substitutes the electromagnetic signal-based system, eliminating the harmful effect of signal interference while maintaining localization capability in built environments.
Solution Approach 2:
The patent introduces an intermediary processing system that collects data from multiple sensors (accelerometers, gyroscopes, magnetometers) and processes it through algorithms to determine position. This intermediary layer mediates between the raw sensor data and the final localization output, filtering out the effects of signal interference and providing reliable localization in challenging environments.
2Measurement precision
If multiple fixed devices are deployed for localization, then localization accuracy improves, but device complexity and installation costs increase
Solution Approach 1:
The patent implements self-service localization where the mobile device itself carries the sensing components (accelerometers, gyroscopes, magnetometers) needed for localization. This eliminates the need for external fixed devices and infrastructure, reducing system complexity and installation costs while maintaining localization accuracy through on-device processing.
Solution Approach 2:
The patent makes the mobile device universal by integrating multiple functions (localization, orientation, movement detection) into a single portable unit. The device performs both sensing and processing functions, eliminating the need for separate fixed infrastructure and reducing overall system complexity while maintaining high measurement precision.
3Reliability
If continuous communication with fixed devices is required for localization, then localization reliability improves, but energy consumption increases
Solution Approach 1:
The patent employs periodic action by using inertial sensors to capture movement data at discrete time intervals rather than requiring continuous communication. The system processes sensor data periodically to update position estimates, maintaining localization reliability while significantly reducing energy consumption compared to continuous wireless communication.
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 accurate localization in complex environments by recognizing voluntary movements and reducing installation complexity and costs, particularly beneficial in areas like hospitals and construction sites.
Implementation Method 1
at least one accelerometer (S1, S1') for detecting a differential movement of the person or of the object moved by one or more people
Implementation Method 2
at least one gyroscope (S1, S1') for detecting a differential movement of the person or of the object moved by one or more people
Implementation Method 3
at least one magnetometer (S1, S1') for detecting a differential movement of the person or of the object moved by one or more people
Data Source
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AI summary
System and method of topological localization of a person or an object that is moved by one or more people in a built environment comprising at least one sensor for detecting the movement of the person or object in said environment capable of providing differential data over time and presenting: - at least one transmission unit of differential movement information detected by the sensor mechanically coupled to that person or object; - at least one unit for receiving the differential movement information transmitted by this transmission unit; - at least one processing unit configured to perform a differential movement information evaluation procedure which: a) recognizes the presence of a voluntary movement activity as opposed to an involuntary movement; b) if there is a voluntary movement activity, it recognizes a path within said environment by comparing differential movement parameters, such as for example the speed of variation of the position and / or the duration of this variation and / or the speed of variation of the direction and / or the duration of such variation, with models of execution of voluntary movement activities in a plurality of predefined paths in the same built environment.