Hub and Spoke Classification for Cross-Platform App Development
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Solution Overview
Problem
Current app development platforms are limited in scope, requiring technical expertise and platform-specific design, making it costly and time-consuming to create engaging mobile apps that support features like 3D, mapping, IoT integration, AR, and VR across multiple devices and operating systems, while also facing challenges in rapid development and deployment of media-rich content applications.
Innovation Solution
A method for determining a user device's location within a building using a machine-learned location classification model trained with signal profiles, which detects network signals and transmits a signal profile to a backend server for location estimation, enabling location-based services without deep expertise in operating system behavior or device characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If platform-specific design and coding are used for each device type, then app functionality and device compatibility are improved, but development time and cost increase significantly
Solution Approach 1:
The patent applies universality by creating a single cross-platform application framework that can deploy to multiple device types and operating systems simultaneously. The system uses a unified development environment that generates platform-specific code automatically, allowing one application to serve multiple platforms without requiring separate development efforts for each device type.
Solution Approach 2:
The patent employs copying by using template-based approaches where a master application design is created once and then copied/adapted to different platforms through automated code generation. The system maintains a central template that can be replicated across multiple target platforms, reducing the need to create separate designs for each device.
2Reliability
If extensive technical expertise in operating system behavior and device characteristics is required, then app performance and optimization are improved, but development accessibility and speed decrease
Solution Approach 1:
The patent introduces an intermediary layer - a cross-platform framework and development system - that sits between the developer and the underlying operating systems/devices. This intermediary handles platform-specific complexities, device characteristics, and optimization details automatically, allowing developers to create high-performance applications without needing deep expertise in each platform's internal behavior.
Solution Approach 2:
The system applies self-service by having the development framework automatically handle platform-specific optimizations, code adaptations, and device compatibility issues without requiring manual intervention from developers. The framework self-adjusts to target platforms, generating optimized code automatically based on the desired deployment targets.
3Manufacturing precision
If separate development efforts are required for each operating system and device type, then platform-specific optimization is improved, but productivity and resource utilization decrease
Solution Approach 1:
The patent applies segmentation by separating the development process into distinct layers: a platform-agnostic application logic layer and platform-specific implementation layers. This allows the core application to be developed once while maintaining the ability to optimize for specific platforms through automated code generation and configuration, achieving both precision and productivity.
Data Source
AI summary
According to some embodiments of the present disclosure, the disclosure relates to an application system and server kit that create and serve digital twin-enabled applications. This disclosure also relates to a hub-and-spoke classification system. This disclosure also relates to a location-based services framework that leverages a generative content process to improve location prediction. This disclosure also relates to virtual reality and augmented reality applications, as well as digital agents that support various types of applications.