Context Server for User-Defined Automation Tasks
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Solution Overview
Problem
Current approaches for end user programming of context-adaptive systems, such as rule-based and process-oriented programming, are inadequate for defining complex automation tasks as they require technical knowledge and understanding of graphical notation, limiting user flexibility and creativity in combining different sensors for context-aware automation.
Innovation Solution
A method and system that utilize an input unit, sensor system, and computing unit to create a context subspace describing all possible states and relationships of context entities, allowing end users to refine predefined situation descriptions using a query language, enabling the execution of user-defined context-aware automation tasks without programming knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If rule-based or process-oriented programming is used for end user programming, then automation tasks can be defined, but the system requires technical knowledge and understanding of graphical notation which limits ease of operation
Solution Approach 1:
The patent introduces a context server as an intermediary between the user and the complex programming systems. The context server provides predefined situation descriptions that users can select and refine without needing to understand underlying rule-based or process-oriented programming logic. This mediator translates user-friendly situation selection into automated context-adaptive behavior, resolving the contradiction between automation capability and ease of operation.
Solution Approach 2:
The patent creates simplified copies of complex programming concepts through predefined situation descriptions. Instead of requiring users to create automation rules from scratch using graphical notation, the system provides pre-crafted situation templates that replicate common automation scenarios. Users can select and customize these templates without needing programming expertise, thus maintaining automation functionality while improving accessibility.
2Adaptability or versatility
If rule-based programming is used, then simple automation tasks can be defined, but the approach is too restricted for complex automation tasks
Solution Approach 1:
The patent segments the complex task of defining context-adaptive behavior into two distinct parts: situation description (what conditions to monitor) and reaction definition (what actions to take). The context server handles the complex situation description using semantic models and ontologies, while users focus only on selecting and refining situation descriptions. This segmentation allows the system to handle complex automation tasks while keeping the user interface simple and intuitive.
Solution Approach 2:
The patent adds a new dimension to traditional rule-based programming by introducing semantic models and ontologies that provide meaning and context to situations. Instead of simple if-then rules, the system uses rich semantic representations that capture complex relationships between context entities. This dimensional enhancement enables the system to handle complex automation tasks while maintaining ease of operation through natural language situation descriptions.
3Ease of operation
If process-oriented programming is used, then chronological sequences can be defined, but most participants found the notation intuitive yet only one found tasks to be structured
Solution Approach 1:
The context server acts as an intermediary that enforces structured task composition while presenting an intuitive interface to users. When users select and refine situation descriptions, the context server automatically structures these selections into consistent, well-formed automation tasks using predefined semantic models. This mediator ensures task structure consistency without requiring users to manually organize their automation logic, resolving the contradiction between intuitive notation and structured task composition.
Data Source
AI summary
A method for assisting with the specification of a context-adaptive behavior of a system by an end user using an input unit includes: provision of an input unit, a sensor system and a computing unit; capture of at least one item of context information in the surroundings of the end user by means of a sensor system; creation of a context subspace; refinement of a predefined situation description by the end user; termination of the refinement by the end user; combination of private and public components of the definition of the context subspace, together with the extension resulting from the refinement by the end user, into a query in the query language; compilation of the query by the computing unit using a context server; and execution of the query by means of the computing unit.