Ontology-Based Geolocation Determination From Heterogeneous Data
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Solution Overview
Problem
Conventional systems fail to accurately associate geolocation data with real-world entities such as persons or organizations, and struggle to determine the geolocation of objects at specific points in time based on information from heterogeneous data sources.
Innovation Solution
The system employs an ontology-based object model to represent real-world entities, allowing it to identify and associate geolocation data sources with objects through ontology-defined relationships. It retrieves and processes geolocation information from multiple heterogeneous data sources, such as GPS units and video streams, to determine the geolocation of elementary and composite objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional systems process geolocation data from heterogeneous sources, then data coverage is improved, but association accuracy with real-world entities deteriorates
Solution Approach 1:
The patent introduces an intermediary processing layer that receives geolocation data from multiple heterogeneous sources and systematically associates it with real-world entities using predefined association rules. This intermediary layer acts as a mediator between raw data and final geolocation determination, improving both data coverage and association accuracy by structured processing rather than direct conventional methods.
Solution Approach 2:
The system segments the geolocation determination process into distinct stages: data collection from heterogeneous sources, association rule application, entity matching, and final geolocation determination. This segmentation allows each stage to be optimized independently, maintaining high data coverage while improving association accuracy through systematic processing at each segment.
2Adaptability or versatility
If multiple heterogeneous data sources are integrated, then geolocation determination capability is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal processing framework that handles multiple heterogeneous data sources through a single integrated system. The association rules and entity matching mechanisms serve multiple functions across different data sources, reducing overall system complexity while maintaining enhanced geolocation determination capability. The system processes GPS data, video stream data, and other heterogeneous sources through the same universal processing logic.
3Loss of information
If geolocation data is retrieved from multiple data sources, then data completeness is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing association rules and entity relationships before actual geolocation determination is needed. Data from multiple sources is pre-processed and associated with entities in advance, so that when geolocation determination is required, the system can quickly retrieve and use pre-established associations, maintaining data completeness while reducing processing time.
Data Source
AI summary
An example method of determining geolocations of objects based on information retrieved from heterogeneous data sources comprises: receiving, from a first data source associated with an object by an ontology-defined relationship, a first dataset including a first data item specifying a first time identifier and a first geolocation associated with the object; receiving, from a second data source associated with an object by an ontology-defined relationship, a second dataset including a second data item specifying a second time identifier and a second geolocation associated with the object; and determining, by applying a rule set associated with the ontology to the first dataset and the second dataset, a geolocation of the object and a corresponding time identifier.