IoT Logic Database for Device Data Interoperability
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Solution Overview
Problem
The lack of a universal IoT data protocol leads to interoperability issues between different IoT devices, as each manufacturer uses unique data formats, making it difficult for third-party applications to interpret and manage device data across various platforms.
Innovation Solution
A method and apparatus for processing identification data by acquiring device data from interactions between controlling and controlled devices, extracting logic information and attribute information, and establishing a logic database that maps device-specific data to standard formats, enabling data interpretation and interoperability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a data standard is formulated in advance to standardize data names and formats, then data interoperability between different devices is improved, but the complexity of device compatibility increases due to constant correction and difficulty in covering all device types
Solution Approach 1:
The patent introduces a cloud platform as an intermediary that automatically translates between device private data formats and standard data formats. The cloud platform receives device data in various private formats, processes and translates it to standard formats, and then provides it to applications. This mediator approach eliminates the need for applications to directly handle complex device-specific formats, resolving the contradiction between interoperability and standard complexity.
Solution Approach 2:
The system enables devices to automatically register their own data formats with the cloud platform. Each device autonomously provides its data format definition, and the cloud platform automatically generates the corresponding translation mechanisms. This self-service approach allows the system to adapt to new device types without manual standard updates, maintaining interoperability while reducing standard complexity.
2Adaptability or versatility
If no data standard is formulated and applications adapt to device private data protocols, then data interoperability between applications and specified devices is achieved, but third parties cannot understand private data outside the specified scope
Solution Approach 1:
The cloud platform serves as an information bridge that translates device private data into universally understandable standard formats. Applications interact with standardized data through the cloud platform, while the platform automatically translates between standard formats and various device private formats. This ensures both device-specific compatibility and third-party accessibility without information loss.
Solution Approach 2:
The patent creates a universal data interface through standard data formats that can work across all device types. The cloud platform maintains multiple translation layers that enable a single standardized interface to accommodate diverse device protocols. This universality allows any application to access any device data through the standard interface, eliminating the isolation of private data scopes.
3Adaptability or versatility
If device manufacturers use different data formats to reflect differentiated forms and functions, then device diversity and functionality are enhanced, but the difficulty of interpreting and managing device data across platforms increases
Solution Approach 1:
Each device manufacturer autonomously registers their data format with the cloud platform, allowing the system to automatically learn and adapt to new formats without centralized standard-setting. This self-service registration mechanism preserves device diversity while automatically handling the complexity of data translation through the cloud platform's built-in processing capabilities.
Solution Approach 2:
The cloud platform acts as an automated intermediary that handles the complexity of data translation between diverse device formats and standard formats. Rather than requiring applications to manually manage multiple data formats, the platform centralizes this complexity and provides simplified standard interfaces to applications, effectively isolating data management complexity from the application layer.
Data Source
AI summary
Methods and apparatuses for processing identification data are provided. The method includes acquiring device data based on an interaction between a controlling device and a controlled device, wherein the device data is related to a state of the controlled device; extracting logic information and attribute information according to the device data; and establishing a logic database of the controlled device, wherein the logic database includes a correspondence between the attribute information and the logic information. By establishing a logic database, data meanings may be interpreted from device private data to complete identification of the device private data, thus implementing interoperation of Internet of Things data, and improving the use value of the IoT.