3D Mesh Updates in Extended Reality Environments
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Solution Overview
Problem
Current IT environments face challenges in efficiently curating, searching, and analyzing massive quantities of diverse data, particularly in remote collaboration for extended reality environments, where users struggle to interact with real-world environments due to limited views and restricted analysis capabilities.
Innovation Solution
The implementation of an event-based data intake and query system, such as the SPLUNK® ENTERPRISE system, which uses a flexible schema to extract information from machine data, allowing for late-binding schema application at search time, enabling users to search all machine data and derive insights from various data sources, including real-time operational intelligence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a flexible schema with late-binding is used to extract information from machine data, then data analysis flexibility is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by ingesting and storing all machine data in raw form without pre-specifying data sets or schemas. This allows the data to be available for any future analysis need while avoiding the complexity of pre-defining all possible data structures and relationships.
Solution Approach 2:
The system implements dynamic schema application where the schema is not fixed in advance but is applied at search time based on the specific analysis needs. This dynamic approach allows the same data to be analyzed in multiple ways without requiring pre-defined structures for each possible analysis scenario.
2Loss of information
If all machine data is retained and made searchable, then information completeness is improved, but data processing time increases
Solution Approach 1:
The system performs preliminary data ingestion and storage in a standardized format, making all data immediately available for search without requiring later data collection or transformation steps. This eliminates delays associated with data gathering while maintaining complete information availability.
Solution Approach 2:
The system replaces traditional mechanical data processing approaches with an event-based architecture that enables parallel processing and efficient data retrieval. This substitution allows the system to handle large volumes of data without proportionally increasing processing time.
3Ease of operation
If remote users are provided with host's video stream, then remote collaboration is enabled, but remote user's independent analysis capability is limited
Solution Approach 1:
The system creates digital copies of physical environments through 3D spatial mapping and mesh generation. These digital replicas can be viewed and analyzed independently by remote users without being constrained by the host's perspective, enabling both collaboration and independent analysis simultaneously.
Solution Approach 2:
The system transitions from 2D video streams to 3D spatial representations, adding a dimensional layer that enables users to navigate and analyze environments from multiple perspectives. This dimensional enhancement provides independent analysis capability while maintaining collaborative functionality.
Data Source
AI summary
Various implementations or examples set forth a method for scanning a three-dimensional (3D) environment. The method includes generating a 3D representation of the 3D environment that includes one or more 3D meshes. The method also includes determining at least a portion of the 3D environment that falls within a current frame captured by the image sensor. The method further includes generating one or more additional 3D meshes representing the at least a portion of the 3D environment and combining the one or more additional 3D meshes with the one or more 3D meshes into an update to the 3D representation of the 3D environment.