International business machines corporation (20240161637). DYNAMIC CONTEXT-BASED UNMANNED AERIAL VEHICLE AUDIO GENERATION ADJUSTMENT simplified abstract
Contents
- 1 DYNAMIC CONTEXT-BASED UNMANNED AERIAL VEHICLE AUDIO GENERATION ADJUSTMENT
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DYNAMIC CONTEXT-BASED UNMANNED AERIAL VEHICLE AUDIO GENERATION ADJUSTMENT - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
DYNAMIC CONTEXT-BASED UNMANNED AERIAL VEHICLE AUDIO GENERATION ADJUSTMENT
Organization Name
international business machines corporation
Inventor(s)
Martin G. Keen of Cary NC (US)
Jana H. Jenkins of Raleigh NC (US)
Jennifer A. Mallette of Vienna VA (US)
DYNAMIC CONTEXT-BASED UNMANNED AERIAL VEHICLE AUDIO GENERATION ADJUSTMENT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240161637 titled 'DYNAMIC CONTEXT-BASED UNMANNED AERIAL VEHICLE AUDIO GENERATION ADJUSTMENT
Simplified Explanation
The abstract describes a method, computer system, and computer program product for dynamic acoustics adjustment in an unmanned aerial vehicle (UAV) environment. The system captures contextual information, generates an environmental model, identifies dominant sounds, calculates the impact of UAV operations on activities, and modifies operations to minimize impact on the soundscape.
- Capturing contextual information of the environment surrounding a UAV
- Generating an environmental model using machine learning techniques
- Identifying dominant sounds within the soundscape
- Calculating the impact of UAV operations on activities within the environment
- Modifying UAV operations to minimize impact on the soundscape
Potential Applications
This technology could be applied in various industries such as surveillance, agriculture, and wildlife monitoring where minimizing noise pollution is crucial.
Problems Solved
This technology addresses the issue of noise pollution caused by UAV operations, especially in sensitive environments where sound disturbances can disrupt activities or wildlife.
Benefits
The benefits of this technology include reducing noise pollution, minimizing disruption to activities or wildlife, and improving the overall environmental impact of UAV operations.
Potential Commercial Applications
Potential commercial applications of this technology include UAV manufacturers, environmental monitoring companies, and government agencies involved in surveillance or wildlife conservation efforts.
Possible Prior Art
One possible prior art could be noise cancellation technology used in consumer electronics to reduce background noise during audio playback.
=== What are the specific machine learning techniques used in generating the environmental model? The abstract mentions using a cluster of machine learning techniques to generate the environmental model. However, it does not specify the exact techniques employed.
=== How does the system determine the impact of UAV operations on activities within the environment? The abstract describes calculating the impact of UAV operations on activities based on the generated environmental model and identified dominant sounds. It would be interesting to know the specific metrics or algorithms used to determine this impact accurately.
Original Abstract Submitted
according to one embodiment, a method, computer system, and computer program product for dynamic acoustics adjustment is provided. the embodiment may include capturing contextual information of an environment surrounding an unmanned aerial vehicle (uav). the embodiment may also include generating an environmental model using a cluster of machine learning techniques based on the captured contextual information. the embodiment may further include identifying one or more dominant sounds within a soundscape of the captured contextual information. the embodiment may also include calculating an impact of an operation of the uav on one or more activities within the environment based on the generated environmental model and the one or more identified dominant sounds. the embodiment may further include, in response to determining the calculated impact affects an activity within the one or more activities, modifying the operation to minimize the impact on the soundscape.
