Vehicle Command Routing Across Disparate Smart Home Ecosystems
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Solution Overview
Problem
Existing smart home and IoT ecosystems often restrict interoperability, requiring devices from the same manufacturer or using the same communication protocol and operating system, limiting user choice and flexibility.
Innovation Solution
A cloud-based artificial intelligence system in vehicles analyzes user commands and routes them to the appropriate smart home or IoT ecosystem using natural language understanding and speech recognition, modifying commands as necessary to ensure compatibility across disparate systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a user interacts with multiple separate electronic ecosystems (e.g., Apple and Android devices), then the user can access diverse device functionalities and services, but the user must manually manage and switch between different ecosystems, increasing operational complexity and time consumption
Solution Approach 1:
The patent introduces a message router as an intermediary component that automatically routes user commands between different electronic ecosystems. The router intercepts commands from a first ecosystem, determines the target device in the second ecosystem, and forwards the command appropriately, eliminating the need for manual ecosystem switching while maintaining seamless interoperability between devices
2Ease of operation
If user commands are routed automatically across ecosystems, then operational ease is improved, but the routing system complexity increases
Solution Approach 1:
The routing system is segmented into distinct functional components: a message router for command interception and forwarding, a device graph for structured device relationship representation, and a command interpreter for determining routing logic. This modular segmentation manages complexity by organizing the routing functionality into manageable, independent modules that can be developed and maintained separately
3Measurement precision
If device relationships are represented using a device graph, then command routing precision is improved, but the data structure complexity increases
Solution Approach 1:
The device graph uses universal node and edge structures that can represent multiple types of device relationships (ownership, proximity, pairing, etc.) through a unified data model. Each node represents a device with standardized attributes, and each edge represents a relationship type, allowing the same graph structure to handle diverse routing scenarios without requiring separate data structures for each relationship type
Data Source
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AI summary
A system for routing commands issued by a passenger of a vehicle to a Smart Home and/or an Internet of Things (IoT) ecosystem via a connection manager. Issued commands are obtained from utterances using speech recognition and analyzed using natural language understanding and natural language processing. Using the output of the natural understanding analysis, the connection manager determines where to send the command by identifying a target Smart Home and/or IoT ecosystem.