Timestamped Sensor Data Association for Event Detection
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Solution Overview
Problem
Existing surveillance and maintenance systems are inadequate for large and complex infrastructures and vehicles, as they lack the ability to efficiently collect, analyze, and associate sensor data from diverse sources to detect and respond to events in real-time, leading to potential inefficiencies and false alarms.
Innovation Solution
A modular surveillance and maintenance system comprising sensor modules that collect and timestamp data from various sensors, an analysis module that detects events and associates relevant data based on timestamps and spatial constraints, and an output module that provides targeted information to supervisors, utilizing neural networks for enhanced event detection and classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor data from multiple sources is collected and analyzed in real-time for event detection, then event detection capability is improved, but computational effort and system complexity increase
Solution Approach 1:
The system segments sensor data processing by creating modular sensor modules that can be independently configured and analyzed. Each sensor module handles specific sensor types (acoustic, optical, mechanical, etc.), allowing the system to process data from multiple sources without requiring a monolithic complex architecture. This modular approach enables event detection across distributed sensors while managing system complexity through standardized interfaces and independent processing units.
2Measurement precision
If all sensor data is processed and stored for comprehensive event analysis, then measurement precision is improved, but data processing time and computational resources increase
Solution Approach 1:
The system applies preliminary actions by timestamping sensor data at the point of collection and pre-filtering data based on spatial constraints before full analysis. The analysis module uses these pre-applied timestamps and spatial relationships to quickly identify relevant data subsets for event analysis, avoiding the need to process all stored sensor data. This preliminary organization of data enables precise event detection while significantly reducing processing time by focusing computational resources on relevant data only.
3Area of stationary object
If multiple sensor modules are integrated into a unified system, then surveillance coverage is improved, but system complexity and integration difficulty increase
Solution Approach 1:
The system implements universality by designing sensor modules with standardized interfaces and a common analysis module that can handle multiple sensor types (acoustic, optical, mechanical, electromagnetic, chemical, biological). This multi-functional architecture allows different sensor modules to be integrated into a unified surveillance system without requiring type-specific processing logic, thereby expanding coverage while managing integration complexity through standardized data formats and processing protocols.
4Productivity
If real-time event detection is implemented across large infrastructures, then operational efficiency is improved, but computational resources and energy consumption increase
Solution Approach 1:
The system applies partial action by focusing computational resources on detecting specific event types rather than analyzing all sensor data comprehensively. The analysis module uses spatial constraints and timestamps to identify only the subset of sensor data relevant to potential events, processing only that partial set in real-time. This approach maintains operational efficiency for event detection while reducing computational energy consumption by avoiding unnecessary processing of irrelevant data.
Data Source
Figure 1
AI summary
The invention relates to a surveillance system (1) for an infrastructure and/or for a vehicle, comprising at least two sensor modules (2a-2d) configured to collect respective sensor data (I, F1, F2, V) from a respective associated sensor (3a-3d); an analysis module (5) configured to access the sensor data (I, F1, F2, V); wherein the sensor modules (2a-2d) are configured to provide the sensor data (I, F1, F2, V) with a time stamp; and the analysis module (5) is configured to detect a given event based on sensor data (I, F1, F2, V) of at least one first sensor module (2a-2d) and to associate sensor data (I, F1, F2, V) of at least one other second sensor module (2a-2d) with the event based on the time stamps of the sensor data (I, F1, F2, V) to provide an enhanced surveillance and/or maintenance system, in particular a system suitable for large and/or complex infrastructures, vehicles, and combinations thereof.