Automated Sensor Alerting System for Off-Hours Monitoring
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Solution Overview
Problem
Users in various industries face challenges in monitoring and alerting for unusual operating conditions of machines outside regular working hours, as existing systems require manual monitoring and processing of large volumes of sensor data, which can lead to undetected issues and potential damage.
Innovation Solution
A system that automatically monitors sensor data and provides real-time alerts based on user-defined alert ranges, allowing for continuous monitoring and instantaneous notification of suboptimal or dangerous conditions, even when the user is not present, using a server that processes and combines data from multiple sensors with operations like zScore and interpolation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual monitoring of sensor data is used, then device complexity is reduced, but reliability deteriorates due to undetected issues during off-hours
Solution Approach 1:
The system enables self-service monitoring where the automated alerting system independently processes sensor data, evaluates conditions against thresholds, and sends notifications without requiring continuous human intervention. This resolves the contradiction by allowing the system to monitor itself reliably during off-hours while maintaining operational simplicity for the user.
Solution Approach 2:
The patent replaces manual mechanical monitoring processes with an automated electronic system that continuously processes sensor data through computational algorithms. This substitution eliminates the need for human operators to manually check data during off-hours, improving reliability while the automated nature of the system manages complexity through standardized processing logic.
2Reliability
If continuous automated monitoring is implemented, then reliability improves, but device complexity increases
Solution Approach 1:
The system segments the monitoring function into distinct modular components: data collection from sensors, data processing and analysis, threshold evaluation, and alert notification. This segmentation allows each component to be independently optimized and maintained, managing overall system complexity while enabling reliable continuous monitoring through specialized functions.
Solution Approach 2:
The system uses configurable threshold parameters and alert conditions that can be adjusted based on specific operational requirements. By changing parameters such as alert thresholds, notification frequencies, and monitoring intervals, the system adapts to different reliability needs without fundamentally changing the core monitoring architecture, thus managing complexity through parameterization.
3Measurement precision
If large volumes of sensor data are processed manually, then productivity is reduced, but measurement precision may be compromised due to time constraints
Solution Approach 1:
The patent replaces manual data processing with automated computational algorithms that continuously analyze sensor data streams. This substitution enables high-speed processing of large volumes of data with consistent precision, as the automated system can process millions of data points without the time constraints or human error limitations that affect manual processing productivity and accuracy.
Solution Approach 2:
The system implements continuous automated data processing that operates without interruption during off-hours and peak periods. This continuity ensures that measurement precision is maintained through consistent processing standards while productivity is enhanced by eliminating idle time between manual checks and maintaining constant monitoring of sensor data streams.
Data Source
AI summary
Aspects of the present disclosure relate to alerting. A server accesses a user-provided specification, the user-provided specification indicating an initial alert range for a measured value and a subsequent alert schedule for the measured value. The server monitors a physical measurement of the measured value. The server determines that the physical measurement falls within the initial alert range. The server provides an initial alert in response to the physical measurement falling within the initial alert range. The server provides a subsequent alert according to the subsequent alert schedule in the user-provided specification.