Connaught Electronics Ltd. (20240282116). DETECTING AT LEAST ONE EMERGENCY VEHICLE USING A PERCEPTION ALGORITHM simplified abstract
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DETECTING AT LEAST ONE EMERGENCY VEHICLE USING A PERCEPTION ALGORITHM
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DETECTING AT LEAST ONE EMERGENCY VEHICLE USING A PERCEPTION ALGORITHM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240282116 titled 'DETECTING AT LEAST ONE EMERGENCY VEHICLE USING A PERCEPTION ALGORITHM
The patent application describes a method for training a perception algorithm to detect emergency vehicles using audio datasets and image data.
- Audio datasets are received from two microphones and spectrograms are generated.
- Interaural difference maps are generated based on the spectrograms to localize audio sources.
- A CRNN is applied to the input data containing spectrograms and interaural difference maps to identify audio sources in a spatial grid.
- Image data from a camera is used to predict a bounding box for the emergency vehicle using a further ANN.
- Network parameters are adapted based on the output data and audio source localization data.
Potential Applications: - Emergency vehicle detection systems for vehicles and smart cities. - Enhanced safety features for autonomous vehicles. - Surveillance systems for emergency response teams.
Problems Solved: - Improving the accuracy and efficiency of emergency vehicle detection. - Enhancing audio source localization capabilities. - Integrating audio and visual data for comprehensive perception algorithms.
Benefits: - Faster response times in emergency situations. - Reduced risk of accidents involving emergency vehicles. - Enhanced situational awareness for drivers and first responders.
Commercial Applications: Title: Advanced Emergency Vehicle Detection System for Smart Cities This technology can be utilized in: - Automotive industry for advanced driver assistance systems. - Public safety and emergency response agencies. - Smart city infrastructure for traffic management and public safety.
Questions about Emergency Vehicle Detection System: 1. How does this technology improve emergency response times?
- This technology enables faster detection and localization of emergency vehicles, allowing for quicker response by drivers and emergency services.
2. What are the potential challenges in implementing this system in real-world scenarios?
- Challenges may include integrating the system with existing infrastructure, ensuring accuracy in complex urban environments, and addressing privacy concerns related to audio and visual data collection.
Original Abstract Submitted
for training a perception algorithm to detect an emergency vehicle, respective audio datasets are received from two microphones and respective spectrograms are generated. at least one interaural difference map is generated based on the spectrograms, audio source localization data is generated, which specifies a number of audio sources in respective grid cells of a spatial grid, by applying a crnn to first input data containing the spectrograms and the least one interaural difference map. an image is received from a camera and output data comprising a bounding box for the emergency vehicle is predicted by applying at least one further ann to second input data containing the image and the spectrograms. network parameters are adapted depending on the output data and the audio source localization data.
