IoT Aerial Sound Mapping for Real-Time Venue Audio Adjustment
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Solution Overview
Problem
Venues face challenges in maintaining optimal sound quality due to varying acoustics and different sound requirements for different events and speakers, with existing systems struggling to adjust sound intensity in real-time effectively.
Innovation Solution
A method utilizing IoT-enabled aerial vehicles to collect data on sound intensity across regions of a venue, comparing it to a pre-generated sound intensity map, and adjusting audio equipment parameters in real-time to match predicted sound quality, while also identifying and facilitating attendee participation by directing microphones to questioners.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional fixed audio systems are used in venues, then system simplicity is maintained, but sound quality cannot be adjusted to match different events and speakers
Solution Approach 1:
The audio system transitions from a fixed configuration to a dynamic one where audio components can be automatically adjusted in real-time based on event requirements and environmental conditions. The system continuously adapts sound intensity, equalization, and speaker routing without manual intervention, resolving the contradiction between adaptability and complexity through automated control.
Solution Approach 2:
The audio system performs self-adjustment by automatically analyzing event data, comparing actual sound measurements against target profiles, and modifying audio component settings without external control. This self-service capability enables the system to adapt to different events and speakers while managing its own complexity internally.
2Manufacturing precision
If manual audio adjustments are made for different events, then sound quality can be optimized, but time consumption and operational complexity increase
Solution Approach 1:
The system pre-configures audio profiles for different event types and speakers before events occur. By preparing target sound profiles and component settings in advance, the system eliminates time-consuming manual adjustments during events while maintaining high sound quality optimization through pre-planned configurations.
Solution Approach 2:
The system implements real-time feedback by continuously measuring actual sound output, comparing it against target profiles, and automatically making adjustments. This closed-loop control achieves precise sound quality optimization without manual intervention, resolving the time loss associated with traditional manual adjustment processes.
3Measurement precision
If multiple audio components are used to cover different regions, then sound quality across the venue improves, but system complexity and difficulty of coordination increase
Solution Approach 1:
The venue is divided into multiple acoustic zones or regions, each with its own target sound profile and controlled by specific audio components. This segmentation allows precise control of sound intensity distribution across different areas while simplifying the coordination problem by breaking it into manageable regional units with dedicated control logic.
Solution Approach 2:
The system automatically adjusts multiple audio component parameters (gain, equalization, delay, pan) based on real-time measurements and event requirements. By dynamically changing these parameters without manual intervention, the system achieves accurate sound intensity distribution across the venue while managing the complexity of coordinating multiple components through automated parameter optimization.
4Reliability
If real-time sound adjustments are implemented, then sound quality during events improves, but system complexity and computational requirements increase
Solution Approach 1:
The system implements real-time feedback control by continuously monitoring sound output during events, comparing measurements against target profiles, and automatically adjusting audio components. This closed-loop approach ensures sound quality consistency throughout the event while managing real-time control complexity through automated algorithms that adapt to changing conditions without manual intervention.
Data Source
AI summary
A method, the method comprising retrieving a sound intensity map for a venue, wherein the sound intensity map is divided up into a plurality of regions, wherein the sound intensity map predicts a sound quality for each region during a current event. Receiving data from a plurality of IOT enabled operated aerial vehicles, where each IOT enabled operated aerial vehicle of the plurality of IOT enabled operated aerial vehicles travels around different regions of the plurality of regions, wherein each IOT enabled operated aerial vehicle collects data during the event. Comparing the received data to the sound intensity map to determine the region where an audio component of a venue audio needs to be adjusted. Determining the adjustment required for the audio component and adjusting the audio equipment.