Semantic IoT Device Matching for Automatic Task Execution
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Solution Overview
Problem
Current IoT technologies do not provide a method to determine if an electronic device is suitable for performing a task or to select a suitable device without user intervention, assuming a pre-existing connection between devices.
Innovation Solution
The solution involves an electronic device that uses semantic information-based task and product ontologies to select a suitable device for a task by comparing device capabilities with required functions, allowing automatic selection and task execution without user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If IoT technologies assume pre-existing device connections, then device communication is simplified, but the system cannot automatically determine device suitability or select appropriate devices for tasks
Solution Approach 1:
The system performs preliminary actions by pre-defining task ontologies and device ontologies with semantic information before actual task execution. This allows the system to automatically match devices to tasks based on pre-established semantic relationships, eliminating the need for user intervention in device selection while maintaining simplified communication protocols.
Solution Approach 2:
The patent introduces an intermediary matching mechanism that uses semantic information from task ontologies and device ontologies to bridge the gap between simple device connections and intelligent device selection. This intermediary layer automatically determines device suitability by comparing semantic attributes without complicating the underlying communication infrastructure.
2Reliability
If the system requires user intervention for device selection, then device compatibility can be verified, but task execution efficiency is reduced
Solution Approach 1:
The system implements self-service by enabling automatic device selection through ontology-based matching. The task execution module autonomously queries device information, compares semantic attributes against task requirements, and selects appropriate devices without user intervention. This maintains reliability through systematic compatibility verification while dramatically improving task execution efficiency.
Solution Approach 2:
The system incorporates feedback mechanisms where the task execution module continuously queries device information and ontology databases to verify compatibility during automatic device selection. This feedback loop ensures reliable device matching while maintaining automated operation, as the system adjusts its selections based on real-time device availability and capability information.
3Extent of automation
If semantic information-based ontologies are implemented, then automatic device selection is enabled, but system complexity increases
Solution Approach 1:
The patent segments the ontology system into distinct, manageable components: task ontologies that define task requirements and device ontologies that define device capabilities. Each ontology is further divided into structured attributes and semantic relationships. This segmentation reduces overall system complexity by allowing independent development, maintenance, and querying of separate ontology modules.
Solution Approach 2:
The ontology structure is designed with universal, standardized attributes and relationships that can be applied across different device types and task scenarios. This multi-functional ontology framework reduces complexity by providing a unified approach to device-task matching rather than requiring custom matching logic for each device type, enabling automatic device selection through consistent semantic comparison rules.
Data Source
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AI summary
A method for operating an electronic device is provided. The method includes identifying a task among a plurality of tasks configured in a semantic information-based task ontology; identifying functions for each piece of device information corresponding to the identified task based on the semantic information-based task ontology; and identifying functions corresponding to a plurality of devices based on a semantic information-based product information ontology. The method then includes comparing the functions corresponding to the plurality of devices with the functions for each piece of device information based on semantic information; identifying one or more devices to perform the identified task from among the plurality of devices based on the comparing; and displaying, on a touch screen display of the electronic device, information on the identified task and information on the identified one or more devices.