Lighting Network Sound Localization via Propagation Mapping
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Solution Overview
Problem
Current noise monitoring systems face challenges in accurately localizing sound sources due to the lack of real-time scene dynamics data, such as traffic conditions and environmental factors, which affects the accuracy of noise maps and localization.
Innovation Solution
A networked lighting system with integrated sound and environmental sensors that combines real-time sound data, environmental data, and topographical information to create a propagation map, allowing for the localization of sound sources and potentially modifying lighting based on the data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional microphone sensor networks are used for noise monitoring, then the system structure is simple, but the measurement precision of sound localization is insufficient due to lack of real-time scene dynamics data
Solution Approach 1:
The patent combines multiple sensor types (microphones, cameras, environmental sensors) into an integrated monitoring system that captures both acoustic and visual data simultaneously. This merging allows the system to achieve higher localization precision by correlating sound data with visual information from cameras and contextual data from environmental sensors, while sharing a common processing infrastructure.
Solution Approach 2:
The monitoring system is designed to perform multiple functions: sound localization, noise level measurement, environmental condition monitoring, and scene dynamics detection. By making the system multi-functional, it achieves superior sound localization accuracy without requiring a separate dedicated system, thus managing complexity through consolidation rather than proliferation of specialized components.
2Measurement precision
If acoustic consultants use empirical models with direct measurements, then the noise map accuracy can be improved, but the loss of information occurs due to unmeasured real-time scene dynamics
Solution Approach 1:
The system performs preliminary data collection by continuously monitoring and storing environmental conditions, traffic patterns, and scene dynamics before noise measurement campaigns. This preliminary action ensures that when noise measurements are taken, the corresponding contextual data is already available, eliminating information loss and enabling accurate correlation between sound propagation and environmental factors.
Solution Approach 2:
The system implements feedback loops where measured noise data is continuously compared with environmental conditions and scene dynamics. This feedback mechanism allows the system to refine its noise maps by correlating acoustic measurements with real-time contextual data, ensuring that no relevant information is lost and that the noise maps accurately reflect actual propagation conditions.
3Measurement precision
If more sensor types are integrated to capture real-time scene dynamics, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The monitoring system is segmented into modular functional units: acoustic sensing modules, visual sensing modules, environmental sensing modules, and a central processing unit. Each module independently performs its specific function, and the segmentation allows for easier deployment, maintenance, and scaling. This modular approach manages complexity by breaking down the integrated system into manageable, interchangeable components.
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
Enhances the accuracy of noise mapping and localization by incorporating real-time scene dynamics, improving the understanding of noise pollution and enabling more effective noise reduction measures.
Implementation Method 1
obtain, by at least one of the plurality of sound sensors, real-time sound data from within the environment
Implementation Method 2
obtain, by at least one of the plurality of environmental sensors, real-time environmental data from within the environment
Implementation Method 3
combining real-time sound data, real-time environmental data, and topographical information about the environment to create a propagation map of the sound data
Data Source
AI summary
A method (500) for monitoring sound within an environment (100) using a lighting network (300, 400) comprising a processor (26, 220), a plurality of sound sensors (32), a plurality of environmental sensors (36), and a plurality of lighting units (10), includes the steps of: obtaining (520), by at least one of the plurality of sound sensors, real-time sound data from within the environment; obtaining (530), by at least one of the plurality of environmental sensors, real-time environmental data from within the environment; combining (560) the real-time sound data, the real-time environmental data, and topographical information about the environment to create a propagation map of the sound data; and localizing (570), from the propagation map of the sound data, a source of the sound data.