IoT Device Twin Mapping for Cloud Service Coordination
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Solution Overview
Problem
Current IoT communication systems lack efficient methods for mapping and coordinating IoT devices with third-party cloud services, limiting their ability to invoke methods and synchronize properties across devices and cloud services.
Innovation Solution
Establishing a mapping between IoT devices and third-party cloud services through an IoT support service, where device twins are stored with properties of both the device and cloud service, enabling method invocation and property synchronization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If IoT devices communicate directly with multiple third-party cloud services, then communication flexibility is improved, but system complexity increases
Solution Approach 1:
The patent introduces an IoT support service as an intermediary between IoT devices and third-party cloud services. This mediator establishes mappings between devices and cloud services, manages device twins, and coordinates method invocations, thereby enabling flexible communication without requiring devices to directly manage complex connections with multiple cloud services.
Solution Approach 2:
The IoT support service provides universal functionality by serving as a centralized platform that handles multiple cloud service integrations, device registrations, and communication protocols. This multi-functional service reduces the need for each device to implement specialized connection logic for different cloud services.
2Reliability
If device twins store properties from multiple cloud services, then data synchronization is improved, but information management complexity increases
Solution Approach 1:
The patent merges properties from multiple cloud services into a unified device twin structure. The device twin consolidates device properties, cloud service properties, and metadata into a single standardized format, enabling comprehensive data synchronization while abstracting away the complexity of managing heterogeneous information sources.
Solution Approach 2:
The device twin structure implements local quality by organizing different types of properties (device properties, cloud service properties, metadata) into distinct sections within the same data structure. This allows targeted access and management of specific property types while maintaining overall data coherence.
3Adaptability or versatility
If the system supports non-traditional devices, then device compatibility is improved, but communication protocol complexity increases
Solution Approach 1:
The system accommodates non-traditional devices by dynamically adjusting communication parameters through metadata stored in device twins. The IoT support service modifies communication behaviors, data formats, and interaction patterns based on device-specific metadata, enabling broad compatibility without requiring complex protocol implementations in each device.
Data Source
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AI summary
In one example of the technology, a mapping is established between: IoT devices that are tenants of an IoT support service, and tenants of a first third-party cloud service. On the IoT support service, device twins are stored, such that each device twin corresponds to a corresponding IoT device, and such that each device twins includes at least a first section that includes properties of the corresponding IoT device, and a second section that includes properties associated with the first third-party cloud service. The IoT support service is used to invoke a first method associated with at least one IoT device based on metadata in at least one corresponding device twin. The first method is associated with the first third-party cloud service.