Thing Machine Graph Model for IoT Service Adaptability
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The current definition and implementation of the Internet of Things (IoT) are limited by focusing primarily on devices and sensors connected to the Internet, rather than services offered, leading to inefficiencies and costs in algorithmic procedures and modeling.
Innovation Solution
A Thing Machine that represents actions and the things they act upon using a multi-dimensional graph model, allowing for the management and interpretation of requests through a booting vocabulary that adapts with interaction, enabling increased interpretation and action capability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a traditional client-server model with web browsers is used to access services, then compatibility and ease of operation are maintained, but mobile friendliness and adaptability to different devices are poor
Solution Approach 1:
The patent implements a universal Thing Machine platform that can operate across multiple devices and operating systems. By using a standardized thing:graph data model and vocabulary that is device-agnostic, the system provides consistent service access whether through mobile devices, desktop computers, or other platforms, eliminating the need for device-specific optimizations while maintaining universal compatibility
2Adaptability or versatility
If multiple dedicated mobile apps are downloaded for different services, then service functionality is improved, but device clutter and complexity increase
Solution Approach 1:
The patent merges multiple service-specific functionalities into a single unified Thing Machine platform. Instead of requiring separate apps for different services, the system uses a common interface that can access any service through standardized protocols and data models, consolidating what would otherwise require multiple applications into one universal access point
Solution Approach 2:
The Thing Machine serves as a universal platform that can access diverse services through a standardized interface. The thing:graph data model and vocabulary enable the same platform to handle different service types without requiring service-specific applications, providing multi-functionality through a single unified system
3Adaptability or versatility
If the Internet of Things is defined as devices and sensors connected to the Internet, then device connectivity is improved, but service modeling and interpretation become ambiguous
Solution Approach 1:
The patent segments the Internet of Things concept into two distinct layers: the physical layer (devices and sensors) and the service layer (virtual services and actions). By introducing the thing:graph data model that separately represents physical Things and virtual Services with clear distinctions in their vocabularies and data structures, the system maintains device connectivity while eliminating ambiguity in service definition through structured separation of concerns
4Adaptability or versatility
If a standardized Thing Machine platform is implemented, then adaptability and service access are improved, but algorithmic procedure complexity increases
Solution Approach 1:
The patent applies homogeneity by standardizing service access through a unified Thing Machine interface and common data model. All services are accessed through the same standardized protocols, vocabulary, and thing:graph structure, creating uniform interaction patterns that simplify algorithmic procedures despite the diversity of underlying services. The consistent structure across all service accesses reduces complexity through predictability and standardization
Data Source
AI summary
A computer-implemented method is disclosed for a first (P(TM)) to gain knowledge. The method includes: performing a first P(TM(i)) to interact with a P(TM(thing)) to set a first Thing that is representative of content, performing a second P(TM(i)) to interact with the P(TM(thing)) to parse the content of the first Thing as a second Thing that is representative of a statement, performing a third P(TM(i)) to interact with the P(TM(thing)) to evaluate the statement of the second Thing to compute a third Thing that is representative of a performable statement, and performing a fourth P(TM(i)) to interact with the P(TM(thing)) to perform the performable statement of the third Thing, The fourth P(TM(i)), in performing the performable statement, interacts with P(TM(thing)) to set one or more Things that are representative of posterior knowledge.