Automatic Device Testing for Set-Top Box Installation
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Solution Overview
Problem
Device testing often fails to accurately evaluate performance under high demand network conditions, leading to operational errors and inefficient installations, as technicians typically install devices during low demand times, preventing evaluation of normal operating conditions.
Innovation Solution
A device, such as a set-top box, can perform a self-test by tuning to a channel with a threshold data rate, simulating high demand scenarios, allowing it to monitor performance metrics and identify errors, thereby ensuring proper operation during normal conditions without requiring a technician's return for fixes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If device testing is performed during low demand periods, then installation time is reduced and technicians can work efficiently, but the device performance cannot be accurately evaluated under normal high demand operating conditions
Solution Approach 1:
The patent applies preliminary action by implementing automatic device testing that simulates high demand network conditions during the installation phase. The system proactively creates artificial traffic loads and monitors device performance metrics before the device is fully deployed into actual high demand operating conditions, thereby predicting potential performance issues in advance without requiring a technician return visit
Solution Approach 2:
The patent applies copying by creating a simulated environment that replicates normal high demand operating conditions in the laboratory or during installation. Instead of waiting for actual high demand conditions to occur, the system generates copy representations of typical user traffic patterns, network loads, and operating scenarios to test device performance accurately during low demand installation periods
2Reliability
If technicians return to fix operational errors after installation, then device reliability is improved, but loss of time and installation efficiency deteriorate
Solution Approach 1:
The patent applies self-service by implementing automatic device testing and monitoring systems that autonomously evaluate device performance under simulated high demand conditions without requiring technician intervention. The system automatically detects performance degradation, identifies operational errors, and generates diagnostic information, enabling the device to essentially test and monitor itself rather than requiring external technician assessment during high demand periods
Solution Approach 2:
The patent applies feedback by implementing continuous monitoring of device performance metrics during simulated high demand conditions. The system collects data on device responsiveness, error rates, and operational stability, then feeds this information back to technicians or system administrators to predict potential failures before they occur in actual deployment, allowing proactive rather than reactive maintenance
3Measurement precision
If device testing simulates high demand conditions, then performance evaluation accuracy is improved, but processing resource consumption increases
Solution Approach 1:
The patent applies partial or excessive action by implementing targeted device testing that focuses specifically on the most critical performance metrics and operational scenarios under high demand conditions. Rather than exhaustively testing every possible function and condition, the system identifies and monitors key performance indicators that are most predictive of actual device reliability in deployment, achieving sufficient measurement precision with reduced processing overhead
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting the intensity and complexity of simulated high demand conditions based on device type, installation context, and observed performance. The system can scale the level of simulation fidelity and resource consumption up or down depending on what is necessary to achieve adequate performance evaluation accuracy for that specific device and scenario, rather than always applying maximum resource intensity
Data Source
AI summary
A device can receive an indication to perform a test of a capability of the device to receive data. The data can have a threshold data rate. The device can perform an action to cause the device to receive the data from a source of the data at the threshold data rate. The device can monitor a set of metrics related to the data or a performance of the device. The device can perform an analysis of the set of metrics after monitoring the set of metrics. The device can identify a source of an error based on a result of performing the analysis of the set of metrics. The source of the error can be related to the data or the performance of the device. The device can perform another action related to fixing the source of the error.