Visual-Acoustic Event Detection System
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Solution Overview
Problem
Current surveillance systems face challenges in reliably detecting and classifying events in monitoring areas without human intervention, often resulting in false alerts, missed events, and high energy consumption, while also requiring extensive storage and raising privacy concerns.
Innovation Solution
A monitoring system comprising a visual 3D capturing unit and an acoustic capturing unit, with a computation unit that uses event detectors and classifiers to automatically locate and classify events in a monitoring area, reducing false alerts and energy consumption by combining visual and acoustic data for robust event classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visual 3D capturing and acoustic capturing are combined for event detection, then reliability of event detection is improved, but device complexity increases
Solution Approach 1:
The patent combines visual 3D capturing (laser scanner) and acoustic capturing (microphone array) into a single integrated monitoring system with a shared computation unit. This merging of multiple sensing modalities improves detection reliability by cross-validating events across different sensory channels while managing complexity through unified processing architecture.
Solution Approach 2:
The computation unit serves multiple functions: it processes visual 3D data from the laser scanner, processes acoustic data from the microphone array, performs event detection across both modalities, localizes events, and classifies event types. This multi-functionality reduces overall system complexity by consolidating processing tasks into a single versatile unit.
2Productivity
If continuous monitoring of all areas is performed, then productivity is improved, but use of energy increases
Solution Approach 1:
The system performs periodic scanning with the laser scanner rather than continuous full-area monitoring. The acoustic system operates continuously for event detection, but the energy-intensive visual 3D scanning is activated periodically or triggered by acoustic events, reducing overall energy consumption while maintaining comprehensive monitoring coverage.
Solution Approach 2:
The system uses acoustic event detection to trigger visual 3D scanning only when relevant events are detected acoustically. This self-service mechanism allows the system to focus computational and sensing resources on areas and times when events are likely occurring, improving productivity without proportionally increasing energy consumption.
3Loss of information
If extensive data storage is implemented, then loss of information is reduced, but device complexity increases
Solution Approach 1:
The system extracts and stores only the most relevant information from sensor data: event detection results, event localization coordinates, event classification types, and associated timestamps. Rather than storing all raw visual and acoustic data, the system extracts essential event characteristics for storage and analysis, reducing information loss while minimizing storage infrastructure requirements.
Solution Approach 2:
The system applies different data retention strategies to different types of information: detailed 3D spatial data is stored locally for immediate event analysis, while processed event summaries and classifications are stored for long-term records. This local quality approach optimizes both information retention and storage complexity by matching storage depth to data importance.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively detects and classifies events with reduced false alerts and energy consumption, providing accurate localization and classification of events, while minimizing storage requirements and addressing privacy concerns through automated and efficient data processing.
Implementation Method 1
a visual 3D capturing unit configured for an optical 3D acquisition of the monitoring area
Implementation Method 2
A visual 3D capturing unit with an electro-optical distance meter, e.g. in form of a laser scanner
Implementation Method 3
an acoustic capturing unit with a microphone array, which has a known configuration of multiple acoustic-electric transducers
Data Source
AI summary
A monitoring system for locating and classifying an event in a monitoring area by a computation unit including a visual 3D capturing unit providing geometric 3D information and an acoustic capturing unit providing an acoustic information of the monitoring area. An event detector is configured with an acoustic channel and a visual channel to detect the event. The acoustic channel is configured to detect the event as a sound event in the acoustic information and to determine a localization of the sound. The visual channel is configured to detect the event as a visual event in the geometric 3D information and to derive a localization of the visual event. The event detector provides detected events with a region of interest for detected event, which is analyzed in order to assign the detected event a class within a plurality of event classes.