IoT Device Self-Diagnosis via Input-Output Association Tables
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Solution Overview
Problem
Current IoT devices lack effective internal diagnostic capabilities to detect faults in inputs and outputs, making it difficult for users to identify and address issues until the devices are in use, and even then, it's challenging to isolate whether the fault is due to a hardware, software, or peripheral component.
Innovation Solution
A computer-implemented method and system that generates a device table and association table to represent the relations between inputs and outputs of IoT devices, allowing for automated testing and fault detection using external signals and sources within a network, enabling devices to test their own inputs and outputs in isolation and detect internal failures or performance degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated testing systems are implemented for IoT devices, then fault detection capability is improved, but device complexity increases
Solution Approach 1:
The patent enables IoT devices to perform self-diagnosis by automatically generating test signals and detecting faults in their own inputs and outputs. The device creates device tables and association tables that map inputs to outputs, allowing the device to autonomously test its components without external intervention, thereby improving reliability while avoiding the complexity of external testing infrastructure.
Solution Approach 2:
The patent divides the testing process into discrete, manageable components: device tables that catalog inputs and outputs, association tables that map relationships between them, and modular test signal generation. This segmentation allows the complex testing functionality to be implemented through simple, standardized data structures and processes that can be integrated into existing devices without overwhelming complexity.
2Ease of operation
If internal diagnostic capabilities are added to IoT devices, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The device automatically generates and executes diagnostic tests, creating device tables that inventory its inputs and outputs and association tables that map their relationships. This self-service approach allows users to simply initiate a diagnostic routine and receive clear fault identification without needing to understand the underlying complexity of the testing mechanisms.
Solution Approach 2:
The patent introduces intermediate data structures (device tables and association tables) that act as mediators between the complex internal diagnostics and the user. These tables organize diagnostic information in a standardized, easily interpretable format, allowing users to identify faults through simple table lookups without directly interacting with the complex testing logic.
3Measurement precision
If comprehensive input-output testing is performed, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent pre-generates device tables that inventory all inputs and outputs and association tables that map their relationships before actual testing occurs. This preliminary organization of testing data allows the diagnostic process to proceed efficiently by simply following the pre-established mappings, rather than discovering relationships during the test itself, thereby reducing testing time while maintaining comprehensive coverage.
Solution Approach 2:
The testing system dynamically adapts its scope based on the association tables. If a fault is detected in one component, the system can use the pre-established relationships to infer the status of connected components, reducing the need to test every single input-output pair individually. This dynamic adjustment maintains measurement precision by focusing on critical paths while reducing overall testing time.
Data Source
AI summary
A method, system, and computer program product for automated testing of Internet of Things devices are provided. The method generates a device table for a set of devices. The device table includes a set of inputs and a set of controllable outputs for each device. A set of input signals are detected for a device for a subset of inputs associated with the device. The set of input signals are detected from one or more controllable outputs of a subset of devices. The device table is modified based on the set of input signals and the one or more controllable outputs to generate an association table representing a relation of the subset of inputs with the one or more controllable outputs. The method detects a fault in one or more device of the set of devices based on a test input signal and the association table.