Wireless Sensor Network Diagnostics via Nested Variable Monitoring
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Solution Overview
Problem
Troubleshooting wireless control and sensor networks (WCSN) is challenging due to complexity and the difficulty in determining the root cause of issues without built-in diagnostics, especially when problems can arise in various components like radio hardware, firmware, processors, and communication channels, and are often located in inaccessible areas.
Innovation Solution
A method and device for wireless diagnostics that include a diagnostic module integrated into the application code to monitor internal variables, collect diagnostic data, perform layered analysis, and identify problems, allowing for efficient problem resolution and customer experience enhancement by providing a fourth level of internal variable diagnostics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If built-in diagnostics are added to monitor internal variables, then diagnostic capability is improved, but device complexity increases
Solution Approach 1:
The diagnostic module is nested within the application code structure, with internal variables embedded in code sections. The system uses a hierarchical diagnostic approach where device-level diagnostics contain application-level diagnostics, which in turn contain internal variable monitoring, creating a nested diagnostic structure that provides comprehensive monitoring without proportionally increasing overall system complexity
Solution Approach 2:
The diagnostic system is segmented into multiple hierarchical levels: device-level diagnostics and application-level diagnostics. Each level monitors specific subsets of variables appropriate to its scope, allowing complex diagnostic functionality to be broken down into manageable segments that can be implemented and maintained independently
2Measurement precision
If comprehensive diagnostic data is collected and uploaded, then problem identification accuracy is improved, but communication bandwidth consumption increases
Solution Approach 1:
The system extracts and monitors only the most relevant internal variables at each diagnostic level rather than collecting all possible data. At the device level, key hardware and communication variables are monitored, while at the application level, specific application-specific variables are tracked. This selective extraction provides sufficient diagnostic accuracy while minimizing the volume of data that needs to be uploaded and transmitted
Solution Approach 2:
The diagnostic system implements partial monitoring by focusing on critical variables that provide the most value for problem identification. Rather than attempting to monitor every possible variable comprehensively, the system monitors a strategic subset of variables that enable effective diagnostics with minimal communication overhead
Data Source
AI summary
A method of performing diagnostics on a first hierarchical device operable within a building automation system is disclosed. The method includes compiling application code configured to control the first hierarchical device such that the application code includes a plurality of internal variables, providing a diagnostic module configured to monitor the plurality of internal variables, collecting internal variable diagnostic data related to the monitored plurality of internal variables, uploading the collected internal variable diagnostic data to a second hierarchical device, performing, at the second first hierarchical device, a layered diagnostic analysis on the internal variable diagnostic data, and identifying a first hierarchical device problem based on the analyzed internal variable diagnostic data.