Baseline Event Detection Using Stored Sensor Data References
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Solution Overview
Problem
Existing event data recorder systems lack the capability to efficiently detect and monitor events and precursors in real-time, and provide interfaces for users to manage and view recorded data effectively.
Innovation Solution
An event detection system comprising multiple sensor devices that generate and process data streams, using object models to define procedures for event detection, and streaming data to a server system for further analysis and visualization, incorporating features like neural networks and stereoscopic inference models for real-time event recognition and notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If event detection systems continuously monitor all sensor data in real-time, then detection reliability is improved, but energy consumption and processing load increase significantly
Solution Approach 1:
The system performs preliminary action by generating baseline data during normal operation and storing it for later comparison. When an event is detected, the system retrieves and compares against pre-generated baseline data, avoiding the need for continuous real-time analysis of all sensor data streams. This preliminary preparation of reference data enables reliable event detection while significantly reducing ongoing processing requirements and energy consumption.
2Measurement precision
If the system streams all sensor data to the server for analysis, then measurement precision is improved, but data transmission bandwidth and processing time increase
Solution Approach 1:
The system extracts only the essential comparison function from the server, using it to generate baseline data and define event criteria. Local devices then perform the actual event detection by comparing sensor data against stored baseline data, extracting only necessary decisions locally rather than transmitting all raw sensor data to the server. This extraction of core functionality enables precise event detection while minimizing data transmission and processing time.
3Measurement precision
If the system stores and analyzes complete sensor data streams, then event detection accuracy is improved, but device complexity and storage requirements increase
Solution Approach 1:
The system creates simplified copies of sensor data in the form of baseline data that captures the essential characteristics of normal operation. Instead of storing and managing complete raw sensor data streams, the system generates condensed baseline representations that can be easily stored, retrieved, and compared. This copying approach maintains event detection accuracy while significantly reducing storage requirements and data management complexity.
Data Source
AI summary
A baseline event detection system to detect events by performing operations that include: generating a baseline data set; accessing a data stream; performing a comparison of the baseline data set and the data stream; and detecting an event based on the comparison.