Object-Model Event Detection for Real-Time Sensor Stream Analysis
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Solution Overview
Problem
Existing event data recorder (EDR) systems lack real-time event detection and monitoring capabilities, as well as effective interfaces for managing and viewing recorded data.
Innovation Solution
An event detection system comprising multiple sensor devices that generate and access sensor data to detect events or precursors, utilizing object models to define procedures for data processing and visualization, and streaming data to a server system for further analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional EDR systems continuously record all sensor data, then complete event data is captured, but real-time event detection and monitoring capabilities are lacking
Solution Approach 1:
The system performs preliminary analysis of sensor data streams using object models to identify potential events before they occur or as they occur. The event detection system continuously monitors sensor data against predefined object models that represent expected event patterns, enabling real-time detection without waiting for complete data accumulation.
Solution Approach 2:
The system extracts only the relevant portions of sensor data that match event patterns defined by object models. Instead of processing all continuous sensor data equally, the system identifies and extracts specific data segments that indicate events or precursors, enabling focused real-time analysis of critical information.
2Measurement precision
If multiple sensor devices are deployed for comprehensive event detection, then event recognition accuracy improves, but system complexity and data management burden increase
Solution Approach 1:
The system segments the complex task of event detection into manageable components by defining object models for different event types. Each object model represents a specific event pattern with its own detection criteria, allowing the system to handle multiple sensor devices and event types through modular, independent detection rules rather than a monolithic complex system.
Solution Approach 2:
The object model framework provides a universal detection mechanism that can handle multiple sensor types and event categories through a single unified system. The same object model-based architecture processes data from various sensor devices regardless of the specific event type being detected, reducing overall system complexity through standardized multi-functional processing.
3Reliability
If all sensor data is streamed to server system for analysis, then comprehensive event monitoring is achieved, but data transmission bandwidth and processing resources are consumed
Solution Approach 1:
The system extracts and transmits only the relevant event-related data portions to the server system. By using object models to identify which sensor data segments represent actual events or precursors, the system sends only these extracted portions rather than continuously streaming all sensor data, significantly reducing bandwidth consumption while maintaining complete event monitoring capability.
Data Source
AI summary
Example embodiments described herein therefore relate to an object-model based event detection system that comprises a plurality of sensor devices, to perform operations that include: generating sensor data at the plurality of sensor devices; accessing the sensor data generated by the plurality of sensor devices; detecting an event, or precursor to an event, based on the sensor data, wherein the detected event corresponds to an event category; accessing an object model associated with the event type in response to detecting the event, wherein the object model defines a procedure to be applied by the event detection system to the sensor data; and streaming at least a portion of a plurality of data streams generated by the plurality of sensor devices to a server system based on the procedure, wherein the server system may perform further analysis or visualization based on the portion of the plurality of data streams.