Event Scenario Validation Using Multi-Sensor Reference Readings
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing scenario detection systems face challenges in accurately validating catastrophic event scenarios due to noisy or unreliable sensors, where a single unusual reading may not reliably indicate a real event, necessitating a method to validate event scenarios using reference readings from multiple sensors.
Innovation Solution
The method involves obtaining readings from distributed sensors, comparing them to a scenario library containing reference readings for predefined scenarios, and validating scenarios by confirming that additional sensor readings match the reference readings, with an optional confidence level determination based on temporal evolution of sensor data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a single sensor reading is used to detect event scenarios, then the response speed is fast, but the reliability of detection is poor due to noisy or unreliable sensors
Solution Approach 1:
The system segments the detection process into multiple stages: initial detection using a single sensor, followed by validation using additional sensors. This segmentation allows fast initial response while ensuring reliability through progressive verification against reference readings from multiple sensors.
Solution Approach 2:
The system performs preliminary action by pre-storing reference readings for various event scenarios in a database. When a sensor reading is received, the system quickly compares it against pre-prepared reference patterns, enabling fast detection without requiring complex real-time analysis of multiple sensors simultaneously.
2Reliability
If multiple sensor readings are validated against reference readings, then the reliability of detection is improved, but the complexity of the detection system increases
Solution Approach 1:
Reference readings for multiple sensors are pre-calculated and stored in a database during system setup or normal operation. This preliminary action eliminates the need for complex real-time multi-sensor coordination, as the system only needs to compare current readings against pre-stored reference patterns, simplifying the detection logic while maintaining high reliability.
Solution Approach 2:
The system creates copies of reference readings from normal operation and stores them for comparison. Instead of implementing complex real-time analysis algorithms, the system uses simplified copying and comparison of pre-stored reference patterns, reducing computational complexity while improving detection reliability through multi-sensor validation.
3Measurement precision
If sensor readings are monitored continuously over time, then the accuracy of scenario validation is improved, but the time required for detection increases
Solution Approach 1:
The system applies partial monitoring by not requiring continuous long-term monitoring of all sensors. Instead, when an initial sensor reading matches a reference pattern, the system activates additional sensors for targeted validation. This partial action approach achieves sufficient accuracy for scenario validation without the time cost of continuous comprehensive monitoring.
Solution Approach 2:
The system uses preliminary pattern matching to identify potential scenarios quickly. When a match is found, only then does it proceed to monitor additional sensors over time for validation. This two-stage approach reduces the overall detection time by avoiding unnecessary continuous monitoring unless a potential scenario is already identified through preliminary analysis.
Data Source
AI summary
Methods and apparatus are provided for validating event scenarios using reference readings obtained from a plurality of sensors associated with one or more predefined event scenarios. If a reading from a first sensor satisfies a reference reading of the first sensor for at least one identified scenario in a scenario library, at least one additional sensor is identified from the identified scenario and a reading is obtained from the additional sensors. The identified scenario is validated when the readings of the additional sensors satisfy the reference reading for the additional sensors from the identified scenario. A confidence level is optionally determined based on the readings of the sensors in the identified scenario. The readings of the sensors are optionally monitored over time to update the confidence level of the identified scenario.