Intelligent Fusion Middleware for Spatial Data Integration
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Solution Overview
Problem
Current systems lack a unified middleware solution to effectively integrate disparate spatially-aware and spatially-dependent devices and systems, limiting their utility and usability by not leveraging AI to create a holistic platform for complex interactions.
Innovation Solution
The development of intelligent fusion middleware that interprets spatial data from various systems, allowing for natural user inputs such as gestures, speech, and brain activity to control and interact with 3D modeling applications, enhancing user experience and system functionality by simulating real-time physical reactions and invoking native functions of participating systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple disparate spatially-aware systems are integrated without unified middleware, then each system maintains its independence and simplicity, but the overall system complexity increases and utility is limited
Solution Approach 1:
The patent introduces a fusion middleware layer that acts as an intermediary between disparate spatially-aware systems. This middleware receives spatial data from multiple independent systems, processes and fuses the data using AI algorithms, and generates unified contextual information. The intermediary layer enables system integration without requiring direct complex connections between individual systems, thereby improving adaptability while managing integration complexity.
Solution Approach 2:
The fusion middleware is designed as a universal platform that can interface with multiple different types of spatially-aware systems simultaneously. It provides multi-functional capabilities including data aggregation, spatial analysis, gesture recognition, and context generation that can serve various downstream applications. This universal approach allows diverse systems to be integrated through a common interface, enhancing versatility without proportionally increasing complexity.
2Productivity
If AI algorithms are added to create gestalt of connected systems, then system capabilities and intelligence are dramatically increased, but computational requirements and processing time increase
Solution Approach 1:
The fusion middleware performs preliminary spatial data processing and fusion before the data reaches the application layer. By pre-computing spatial relationships, generating environment contexts, and fusing sensor data in advance, the system reduces the computational burden on downstream applications. This preliminary action enables AI-driven gestalt creation while managing energy consumption by doing heavy lifting upfront rather than on-demand.
Solution Approach 2:
The patent segments the computational workload into distinct modules within the fusion middleware: spatial data reception, data fusion processing, gesture recognition, context generation, and function invocation. This segmentation allows each module to be optimized independently for energy efficiency while collectively delivering high system capability. The modular architecture enables selective activation of computational functions based on current needs.
3Speed
If real-time processing of spatial data is implemented, then user interaction responsiveness is improved, but processing accuracy and depth of analysis may be compromised
Solution Approach 1:
The fusion middleware implements partial processing of spatial data in real-time, focusing on critical aspects such as gesture recognition and immediate spatial relationships. Not all spatial data is processed to the same depth - urgent interactions receive full real-time processing while less time-sensitive data undergoes more thorough but delayed analysis. This selective approach maintains responsiveness while preserving analytical accuracy where needed.
Solution Approach 2:
The system maintains continuous spatial data processing through the fusion middleware, which constantly receives, fuses, and analyzes spatial inputs. This continuous action ensures that the system remains responsive to user interactions without interruption. The uninterrupted processing pipeline allows the system to maintain both speed and accuracy by never stopping the analysis flow, even if the depth of analysis varies based on current context.
Data Source
AI summary
Methods, including computer programs encoded on a computer storage medium, for controlling a 3D modeling application based on natural user input received at middleware. In one aspect, a method includes: receiving data indicating that an application operating at the application layer is interpreted as spatial data about one or entities at one or more corresponding locations within an environment context from one or more participating systems; receiving, through an interface in communication with the one or more systems that provide spatial data, multiple sets of spatial data provided by or derived from the one or more participating systems that are generated while the application manages one or more interactions in the environment context; determining adjustment to apply to the environment context.