Description:SYSTEM AND METHOD FOR EMERGENCY VEHICLE NOTIFICATION
TECHNICAL FIELD
[0001] The present subject matter generally relates to emergency vehicle notification. More particularly, but not exclusively to a system and method for emergency vehicle notification based on audio amplification. 5
BACKGROUND
[0002] In today's increasingly congested urban environments, safety of emergency responders and general public on roads has become a paramount concern. Emergency vehicles, such as ambulances, fire trucks, and police 10 cars, rely heavily on their audible sirens to navigate through traffic swiftly and reach their destinations in a timely manner. However, amidst cacophony of city noise and constant hum of traffic, effectiveness of these audible signals is often compromised, leading to potentially dangerous situations where vehicles fail to yield, or pedestrians remain unaware of approaching 15 emergency vehicles.
[0003] Blaring horns, engine revs, and general din of urban traffic can drown out sound of emergency vehicle sirens, making them difficult to hear even for attentive drivers. This issue is exacerbated in densely populated areas with high levels of ambient noise. In congested traffic conditions, emergency 20 vehicles may be obscured from view by surrounding vehicles, buildings, or other obstacles. This obstructed visibility reduces the effectiveness of visual cues for alerting drivers and pedestrians to the presence of emergency vehicles. Delayed response times from drivers and pedestrians can impede a progress of emergency vehicles and increase a risk of accidents or delays in 25 reaching critical emergencies. Improving response times by promptly alerting road users to the presence of emergency vehicles is essential for enhancing overall road safety.
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[0004] Conventional methods for notifying nearby pedestrians and user of vehicles of the presence of the emergency vehicle include using louder sirens or installing additional speakers on emergency vehicles to increase a volume of the audible signals. However, while this approach may improve audibility to some extent, the approach may not adequately address the problem of 5 sirens being drowned out by ambient noise in urban environments. Further, some vehicles are equipped with visual alert systems, such as flashing lights or LED displays, to complement audible signals. However, such systems rely on line-of-sight visibility and can be ineffective when emergency vehicles are obstructed from view by surrounding traffic or buildings. 10
[0005] Typically, traffic signal pre-emption systems use signal priority technology to give green lights to approaching emergency vehicles, facilitating their passage through intersections. While effective at reducing response times, traffic signal pre-emption systems do not address a broader challenge of alerting drivers and pedestrians to the presence of emergency 15 vehicles in congested traffic conditions.
[0006] Therefore, there is a need in the art for a system and method for emergency vehicle notification which addresses at least the aforementioned problems and other problems of known art.
[0007] Further limitations and disadvantages of conventional and traditional 20 approaches will become apparent to one of skill in the art, through comparison of described systems with some aspects of the present disclosure, as set forth in the remainder of the present application and with reference to the drawings.
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SUMMARY OF THE INVENTION
[0008] According to embodiments illustrated herein, the present invention provides a system and method for emergency vehicle notification. The system comprises a vehicle and one or more microphones associated with a vehicle. Herein, the one or more microphones is configured to determine first 30 environmental audio content associated with the vehicle. The system further
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comprises a speaker associated with the vehicle and a controller associated with the vehicle. The controller is configured to determine whether a first audio signal associated with the determined first environmental audio content corresponds to an emergency siren signal. The controller is configured to apply a machine learning model on the first audio signal based on the 5 determination that the first audio signal associated with the determined first environmental audio content corresponds to the emergency siren signal. The controller is configured to determine a direction of the first audio signal based on the application of the machine learning model. The controller is configured to amplify the first audio signal based on the determined direction. The 10 controller is configured to control the speaker associated with the vehicle for rendering of the amplified first audio signal. [0009] In another embodiment, the method for emergency vehicle notification is provided. The method comprises receiving, by a controller, first environmental audio content associated with a vehicle from one or more 15 microphones. The method comprises determining, by the controller, whether a first audio signal associated with the determined first environmental audio content corresponds to an emergency siren signal. The method comprises applying, by the controller, a machine learning model on the first audio signal based on the determination that the first audio signal associated with the 20 determined first environmental audio content corresponds to the emergency siren signal. The method comprises determining, by the controller, a direction of the first audio signal based on the application of the machine learning model. The method comprises amplifying, by the controller, the first audio signal based on the determined direction. The method comprises controlling, 25 by the controller, the speaker associated with the vehicle for rendering of the amplified first audio signal.
[00010] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed. 30
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BRIEF DESCRIPTION OF THE DRAWINGS
[00011] The details are described with reference to an embodiment of a system and a method for emergency vehicle notification along with the accompanying diagrams. The same numbers are used throughout the drawings to reference similar features and components. 5
[00012] Figure 1 exemplarily illustrates a system for emergency vehicle notification, in accordance with an embodiment of the present disclosure.
[00013] Figure 2 exemplarily illustrates a vehicle equipped with the system for emergency vehicle notification, in accordance with an embodiment of the present disclosure. 10
[00014] Figure 3 exemplarily illustrates a flowchart of a method for emergency vehicle notification, in accordance with an embodiment of the present disclosure.
DETAILED DESCRIPTION
[00015] Exemplary embodiments are described with reference to the 15 accompanying drawings. Wherever convenient, the same reference numbers are used throughout the drawings to refer to the same or like parts. While examples and features of disclosed principles are described herein, modifications, adaptations, and other implementations are possible without departing from the scope of the disclosed embodiments. It is intended that the 20 following detailed description be considered as exemplary only, with the true scope and spirit being indicated by the following claims.
[00016] The terms “an embodiment”, “embodiment”, “embodiments”, “the embodiment”, “the embodiments”, “one or more embodiments”, “some embodiments”, and “one embodiment” mean “one or more (but not all) 25 embodiments of the invention(s)” unless expressly specified otherwise. The terms “including”, “comprising”, “having” and variations thereof mean “including but not limited to”, unless expressly specified otherwise. The terms “a”, “an” and “the” mean “one or more”, unless expressly specified otherwise. 30
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[00017]
The embodiments of the present invention will now be described in detail with reference to a system and a method for emergency vehicle notification with the accompanying drawings. However, the present invention is not limited to the present embodiments. The present subject matter is further described with reference to accompanying figures. It should be noted 5 that the description and figures merely illustrate principles of the present subject matter. Various arrangements may be devised that, although not explicitly described or shown herein, encompass the principles of the present subject matter. Moreover, all statements herein reciting principles, aspects, and examples of the present subject matter, as well as specific examples 10 thereof, are intended to encompass equivalents thereof.
[00018] A person with ordinary skills in the art will appreciate that the systems, modules, and sub-modules have been illustrated and explained to serve as examples and should not be considered limiting in any manner. It will be further appreciated that the variants of the above disclosed system 15 elements, modules, and other features and functions, or alternatives thereof, may be combined to create other different systems or applications.
[00019] The present subject matter is described using the system and the method for emergency vehicle notification, whereas the claimed subject matter can be used in any other type of application employing above-20 mentioned method for emergency vehicle notification, with required changes and without deviating from the scope of invention. Further, it is intended that the disclosure and examples given herein be considered as exemplary only.
[00020] An objective of the present invention is to provide a system for emergency vehicle notification. The system comprises a vehicle and one or 25 more microphones associated with a vehicle. Herein, the one or more microphones is configured to determine first environmental audio content associated with the vehicle. The system further comprises a speaker associated with the vehicle and a controller associated with the vehicle. The controller is configured to determine whether a first audio signal associated 30 with the determined first environmental audio content corresponds to an
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emergency siren signal. The controller is configured to apply a machine learning model on the first audio signal based on the determination that the first audio signal associated with the determined first environmental audio content corresponds to the emergency siren signal. The controller is configured to determine a direction of the first audio signal based on the 5 application of the machine learning model. The controller is configured to amplify the first audio signal based on the determined direction. The controller is configured to control the speaker associated with the vehicle for rendering of the amplified first audio signal. [00021] Another objective of the present invention is to provide a method for 10 emergency vehicle notification is provided. The method comprises receiving, by a controller, first environmental audio content associated with a vehicle from one or more microphones. The method comprises determining, by the controller, whether a first audio signal associated with the determined first environmental audio content corresponds to an emergency siren signal. The 15 method comprises applying, by the controller, a machine learning model on the first audio signal based on the determination that the first audio signal associated with the determined first environmental audio content corresponds to the emergency siren signal. The method comprises determining, by the controller, a direction of the first audio signal based on the application of the 20 machine learning model. The method comprises amplifying, by the controller, the first audio signal based on the determined direction. The method comprises controlling, by the controller, the speaker associated with the vehicle for rendering of the amplified first audio signal.
[00022] It may be appreciated that in today's increasingly congested urban 25 environments, safety of emergency responders and general public on roads has become a paramount concern. Emergency vehicles, such as ambulances, fire trucks, and police cars, rely heavily on their audible sirens to navigate through traffic swiftly and reach their destinations in a timely manner. However, amidst cacophony of city noise and constant hum of traffic, 30 effectiveness of these audible signals is often compromised, leading to
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potentially dangerous situations where vehicles fail to yield, or pedestrians remain unaware of approaching emergency vehicles. [00023] In order to mitigate the aforesaid issues, disclosed is the system for emergency vehicle notification. The system comprises a vehicle. In an embodiment, the vehicle can be a two wheeler, a three-wheeler, a four-5 wheeler, a six-wheeler, and the like.
[00024] The system comprises one or more microphones associated with the vehicle. Herein, the one or more microphones is configured to determine first environmental audio content associated with the vehicle.
[00025] In an embodiment, the one or more microphones is disposed at a first 10 region of the vehicle and the speaker is positioned at a second region of the vehicle. In an embodiment, the determined first environmental audio content comprises a set of first audio signals, and wherein the controller is configured to filter the first audio signal corresponding to the emergency siren signal from the set of first audio signals. 15
[00026] In an embodiment, the one or more microphones associated with the vehicle includes a first microphone and a second microphone. Herein, the first microphone is configured to determine second environmental audio content and the second microphone is configured to determine third environmental audio content. 20
[00027] The system comprises a speaker associated with the vehicle. The system comprises a controller associated with the vehicle. The controller is configured to determine whether a first audio signal associated with the determined first environmental audio content corresponds to an emergency siren signal. 25
[00028] In an embodiment, the controller is further configured to determine a frequency of the first audio signal. The controller is further configured to compare the determined frequency with a predefined emergency frequency band. Herein, whether the first audio signal associated with the received first environmental audio content corresponds to the emergency siren signal is 30 determined based on the comparison.
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[00029] The controller is configured to apply a machine learning model on the first audio signal based on the determination that the first audio signal associated with the determined first environmental audio content corresponds to the emergency siren signal.
[00030] In an embodiment, the controller is further configured to determine 5 a type of an emergency vehicle based on the determination that the first audio signal associated with the determined first environmental audio content corresponds to the emergency siren signal, wherein the type of emergency vehicle is at least one of: an ambulance, a fire truck, a police vehicle, and wherein the machine learning model is applied based on the determined type 10 of the emergency vehicle.
[00031] In an embodiment, the controller is further configured to: determine a first set of parameters associated with the second environmental audio content and the third environmental audio content, wherein the first set of parameters is at least one of: a time difference, an amplitude difference 15 between the second environmental audio content and the third environmental audio content. The controller is further configured to: determine a second set of parameters associated with the vehicle, wherein the second of parameters is at least one of: a speed of the vehicle, a state of the vehicle, a location of the vehicle, wherein the machine learning model is applied on the determined 20 first set of parameters and the determined second set of parameters.
[00032] The controller is configured to determine a direction of the first audio signal based on the application of the machine learning model. The controller is configured to amplify the first audio signal based on the determined direction. In an embodiment, the determined direction is a front 25 direction, or a rear direction, wherein if the direction is the rear direction, then the first audio signal is amplified, and wherein if the direction is the front direction, then the first audio signal is unamplified.
[00033] The controller is configured to control the speaker associated with the vehicle for rendering of the amplified first audio signal. In an 30 embodiment, the controller is configured to determine a state of vehicle,
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wherein the state of the vehicle is at least one of: a stationary state, an idle state, ignition on state, engine running state, moving state, or parking state. Herein, the amplified first audio signal is rendered on the speaker based on the determined state of the vehicle. [00034] In an embodiment, if the state of the vehicle is one of: the ignition 5 on state, the engine running state, the moving state, the idle state, then the amplified first audio signal is rendered on the speaker.
[00035] Figure 1 exemplarily illustrates a system for emergency vehicle notification, in accordance with an embodiment of the present disclosure. Figure 1 depicts a system (100). The system (100) comprises one or more 10 microphones (102) associated with a vehicle (200 of Figure 2), a speaker (104)associated with the vehicle (200), a controller (106) associated with thevehicle (200), a power supply (108), a set of vehicle parameters (110). Thepower supply (108) provides power to the one or more microphones (102),the speaker (104), and the controller (106). The set of vehicle parameters 15 (110)may correspond to a second of parameters associated with the vehicle.
[00036] The one or more microphones (102) is configured to determine first environmental audio content associated with the vehicle (200). In an embodiment, the one or more microphones is disposed at a first region of the vehicle (200) and the speaker (104) is positioned at a second region of the 20 vehicle (200). In an embodiment, the one or more microphones (102) associated with the vehicle (200) includes a first microphone and a second microphone. Herein, the first microphone is configured to determine second environmental audio content and the second microphone is configured to determine third environmental audio content. 25
[00037] The controller (106) is configured to determine whether a first audio signal associated with the determined first environmental audio content corresponds to an emergency siren signal. In an embodiment, the determined first environmental audio content comprises a set of first audio signals. Herein, the controller (106) is configured to filter the first audio signal 30 corresponding to the emergency siren signal from the set of first audio signals.
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The controller (106) is further configured to determine a frequency of the first audio signal and compare the determined frequency with a predefined emergency frequency band. Herein, whether the first audio signal associated with the received first environmental audio content corresponds to the emergency siren signal is determined based on the comparison. 5 [00038] The controller (106) is further configured to apply a machine learning model on the first audio signal based on the determination that the first audio signal associated with the determined first environmental audio content corresponds to the emergency siren signal.
[00039] In an embodiment, the controller (106) is further configured to 10 determine a type of an emergency vehicle based on the determination that the first audio signal associated with the determined first environmental audio content corresponds to the emergency siren signal. Herein, the type of the emergency vehicle is at least one of: an ambulance, a fire truck, a police vehicle, and the machine learning model is applied based on the determined 15 type of the emergency vehicle.
[00040] In an embodiment, the controller (106) is further configured to determine a first set of parameters associated with the second environmental audio content and the third environmental audio content. Herein, the first set of parameters is at least one of: a time difference, an amplitude difference 20 between the second environmental audio content and the third environmental audio content. The controller (106) is further configured to determine a second set of parameters associated with the vehicle (200). Herein, the second of parameters is at least one of: a speed of the vehicle (200), a state of the (200), a location of the vehicle (200). Herein, the machine learning model is 25 applied on the determined first set of parameters and the determined second set of parameters.
[00041] The controller (106) is further configured to determine a direction of the first audio signal based on the application of the machine learning model. The controller (106) is further configured to amplify the first audio signal 30 based on the determined direction. In an embodiment, the determined
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direction is a front direction, or a rear direction, wherein if the direction is the rear direction, then the first audio signal is amplified, and wherein if the direction is the front direction, then the first audio signal is unamplified. [00042] The controller (106) is further configured to control the speaker(104) associated with the vehicle (200) for rendering of the amplified first5 audio signal. In an embodiment, the controller (106) is further configured todetermine a state of the vehicle (200). Herein, the state of the vehicle (200) isat least one of: a stationary state, an idle state, ignition on state, engine runningstate, moving state, or parking state. The amplified first audio signal isrendered on the speaker (104) based on the determined state of the vehicle 10 (200).
[00043] In an embodiment, if the state of the vehicle (200) is one of: the ignition on state, the engine running state, the moving state, the idle state, then the amplified first audio signal is rendered on the speaker (104).
[00044] Figure 2 exemplarily illustrates a vehicle (200) equipped with the 15 system (100) for emergency vehicle notification, in accordance with an embodiment of the present disclosure. Figure 2 depicts the vehicle (200). Referring to Figure 2, the one or more microphones is disposed at a first region of the vehicle (200) and the speaker (104) is positioned at a second region of the vehicle (200). The one or more microphones (102) is configured 20 to determine first environmental audio content associated with the vehicle (200). Further, the speaker (104) associated with the vehicle (200) is controlled for rendering of the amplified first audio signal.
[00045] Figure 3 exemplarily illustrates a flowchart (300) of a method for emergency vehicle notification, in accordance with an embodiment of the 25 present disclosure. The flowchart (300) comprises blocks from 302 to 316.
[00046] At 302, the one or more microphones (102) listens for environment audio. Herein, the controller (106) receives the first environmental audio content associated with the vehicle (200) from the one or more microphones (102). 30
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[00047] At 304, an operation detecting a presence of an emergency siren audio in the first environmental audio content is executed. Herein, whether a first audio signal associated with the determined first environmental audio content corresponds to an emergency siren signal is determined.
[00048] At 306, an operation of identifying a nature of an emergency vehicle 5 is executed. Herein, a type of an emergency vehicle is determined based on the determination that the first audio signal associated with the determined first environmental audio content corresponds to the emergency siren signal. The type of the emergency vehicle is at least one of: an ambulance, a fire truck, a police vehicle, 10
[00049] At 308, an operation of applying a machine learning model to detect if the emergency vehicle is coming from behind the vehicle is executed. Herein, the machine learning model is applied on the first audio signal based on the determination that the first audio signal associated with the determined first environmental audio content corresponds to the emergency siren signal. 15 In an embodiment, the machine learning model is applied based on the determined type of the emergency vehicle.
[00050] At 310, an operation of determining whether the emergency vehicle is coming from behind the vehicle is executed. Herein, a direction of the first audio signal is determined based on the application of the machine learning 20 model. Herein, if the direction is the rear direction (that is, the emergency vehicle is coming from behind the vehicle), then the flowchart 300 moves to the block (312). If the direction is the front direction (that is, the emergency vehicle is coming from front side of the vehicle), then the flowchart (300) moves to the block (302). 25
[00051] At 312, an operation of amplifying the first audio signal is executed. Herein, the first audio signal based on the determined direction. If the determined direction is the rear direction (that is, the emergency vehicle is coming from behind the vehicle) then the first audio signal is amplified.
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[00052] At 314, the amplified first audio signal is rendered on the speaker (104)associated with the vehicle (200) for rendering of the amplified firstaudio signal.
[00053] At 316, an operation of determining whether the emergency vehicle has passed the vehicle (200) and is no longer present behind the vehicle (200) 5 is determined. In case the emergency vehicle has passed the vehicle (200), then the flowchart (300) moves to the block 302. In case the emergency vehicle is still behind the vehicle (200), then the flowchart (300) moves to the block 314.
[00054] In a scenario, a driver is navigating through a busy city street while 10 listening to music in his/her vehicle. Unbeknownst to the driver, an ambulance approaches from behind with its sirens blaring, attempting to reach a nearby emergency.
[00055] The disclosed system is installed in the driver's vehicle. As the ambulance draws closer, the system's microphones pick up the audio signals 15 of the approaching emergency siren from the rear of the vehicle. The controller analyses the audio signals, applying machine learning algorithms to identify t distinct characteristics of emergency siren signals.
[00056] Upon determining that the detected audio signal corresponds to an emergency siren, the system further analyses the direction from which the 20 sound is coming, utilizing Doppler effect or other directional sensing techniques. This allows the system to pinpoint a location of the emergency vehicle relative to the vehicle. Based on this directional analysis, the system amplifies the audio signal of the emergency siren and projects it through the vehicle's front-facing speaker. An amplified alert effectively notifies vehicles 25 and pedestrians ahead of the presence of the approaching emergency vehicle, prompting them to clear the way and allow the ambulance to pass unhindered. Therefore, by utilizing advanced audio analysis, machine learning, and directional alerting mechanisms, the system enhances the awareness and responsiveness of road users to approaching emergency vehicles, thereby 30 improving overall road safety in urban environments.
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[00057] In another scenario, a driver, Sarah, is driving her car in a bustling city during rush hour. She's listening to music on the car stereo and is navigating through heavy traffic. Meanwhile, an ambulance is rapidly approaching from behind with its sirens blaring, responding to an emergency situation. The vehicle is equipped with multiple microphones strategically 5 positioned to capture environmental audio content. For this example, let's assume there are two microphones, one on each side of the vehicle. The vehicle has a front-facing speaker mounted inside a dashboard, facing towards the windshield. A central controller unit processes the audio signals captured by the microphones and determines appropriate actions based on the 10 analysis. The controller utilizes a machine learning model trained to recognize the distinctive patterns of emergency siren signals and to determine the direction from which they originate. An emergency siren frequency range is from 500Hz to 2000Hz. A threshold for directional analysis is ±30 degrees from the rear of the vehicle. An amplification factor of 3x is considered for 15 amplifying the first audio signal. The microphones detect the audio signals from the ambulance's siren as it approaches from behind Sarah's vehicle. The captured audio signals are relayed to the controller for analysis. The controller applies the machine learning model to analyse the audio signals. It identifies the frequency range (500Hz to 2000Hz) characteristic of emergency sirens, 20 confirming that an emergency vehicle is nearby. The controller calculates the direction of the incoming emergency vehicle based on the differences in arrival times and intensities of the siren signals captured by the two microphones. In an example, the analysis indicates that the ambulance is approaching from directly behind Sarah's vehicle, within the ±30° threshold. 25 Since the ambulance is determined to be approaching from behind, the controller activates the amplification mechanism. The audio signal of the ambulance's siren is amplified by a factor of 3x to ensure it is clearly audible to vehicles and pedestrians ahead of Sarah's vehicle. The amplified audio signal is played through the front-facing speaker, projecting the sound 30 towards the front of the vehicle and into the surrounding environment. The heightened volume and directionality of the alert effectively notify nearby
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vehicles and pedestrians of the approaching emergency vehicle. The system continuously monitors the state of Sarah's vehicle to ensure that alerts are provided only when necessary. For instance, if Sarah's vehicle is stationary or parked, the alert may be temporarily deactivated to prevent unnecessary distractions. Thus, by employing advanced audio analysis, directional 5 sensing, and amplification techniques, the system successfully enhances awareness and responsiveness to approaching emergency vehicles, contributing to improved road safety in urban settings. [00058] The disclosed system and the method provided enhanced audibility. By amplifying the audio signals of approaching emergency vehicles, the 10 disclosed system and the method ensures that sirens are more easily heard by drivers and pedestrians, even in noisy urban environments. This improves the effectiveness of auditory alerts, reducing the likelihood of accidents and allowing for timely responses.
[00059] The disclosed system and the method incorporate directional 15 analysis capabilities to determine the source and direction of the emergency vehicle's siren. This allows for targeted amplification of the audio alert, ensuring that it is directed towards vehicles and pedestrians in the path of the emergency vehicle, thus maximizing its effectiveness.
[00060] The disclosed system and the method consider the state of the host 20 vehicle (e.g., stationary, moving) to determine when to render the audio alert. This adaptive feature prevents unnecessary distractions and ensures that alerts are provided only when the vehicle is operational and potentially in a position to respond effectively.
[00061] By leveraging machine learning algorithms, the disclosed system 25 and the method can accurately distinguish emergency siren signals from ambient noise and other audio sources. This improves the reliability and accuracy of the alerting system, reducing false positives and enhancing overall performance.
[00062] The use of multiple microphones and advanced signal processing 30 techniques enables the disclosed system and the method to efficiently capture
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and analyse environmental audio content. This optimizes resource utilization while maintaining high levels of alerting effectiveness, making the system both robust and resource efficient. [00063] The disclosed system and the method contribute to significant improvements in road safety. By alerting drivers and pedestrians to the 5 presence of emergency vehicles in advance, the invention helps prevent accidents, reduce response times, and facilitate the smooth passage of emergency responders through traffic, thereby saving lives and minimizing risks on the road.
[00064] The objectives of the claimed invention collectively aim to address 10 the technical challenges associated with audio signals played by the emergency vehicle and provide a comprehensive solution that amplifies the audio signals played on the emergency vehicle in order to notify nearby vehicles and pedestrians about the presence of the emergency vehicle.
[00065] In light of the above-mentioned advantages and the technical 15 advancements provided by the disclosed system and the method, the claimed steps as discussed above are not routine, conventional, or well understood in the art, as the claimed steps enable the following solutions to the existing problems in conventional technologies. Further, the claimed steps clearly bring an improvement in the functioning of the configuration itself as the 20 claimed steps provide a technical solution to a technical problem.
[00066] A description of an embodiment with several components in communication with another does not imply that all such components are required, On the contrary, a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention. 25
[00067] Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter and is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application 30 based here on. Accordingly, the embodiments of the present invention are
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intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims. [00068] While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of 5 illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.
[00069] While the present disclosure has been described with reference to certain embodiments, it will be understood by those skilled in the art that various changes may be made, and equivalents may be substituted without 10 departing from the scope of the present disclosure. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the present disclosure without departing from its scope. Therefore, it is intended that the present disclosure not be limited to the particular embodiment disclosed, but that the present disclosure will include 15 all embodiments falling within the scope of the appended claims.
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Reference Numerals:
100– System
102-One or more microphones
104– Speaker
106-Controller 5
108-Power supply
110-Set of vehicle parameters
200-Vehicle
300-Flowchart , Claims:We Claim:
1.A system (100) for emergency vehicle notification, the system (100) 5 comprising:
one or more microphones (102) associated with a vehicle (200), wherein
the one or more microphones (102) is configured to determine first environmental audio content associated with the 10 vehicle (200);
a speaker (104) associated with the vehicle (200); and
a controller (106) associated with the vehicle (200), wherein the controller (106) is configured to:
determine whether a first audio signal associated with 15 the determined first environmental audio content corresponds to an emergency siren signal;
apply a machine learning model on the first audio signal based on the determination that the first audio signal associated with the determined first environmental audio 20 content corresponds to the emergency siren signal;
determine a direction of the first audio signal based on the application of the machine learning model;
amplify the first audio signal based on the determined direction; and 25
control the speaker (104) associated with the vehicle (200)for rendering of the amplified first audio signal.
2.The system (100) for emergency vehicle notification as claimed inclaim 1, wherein the one or more microphones is disposed at a first30 region of the vehicle (200) and the speaker (104) is positioned at asecond region of the vehicle (200).
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3.The system (100) for emergency vehicle notification as claimed inclaim 1, wherein the controller (106) is further configured to:
determine a frequency of the first audio signal; and
compare the determined frequency with a predefined 5 emergency frequency band, wherein
whether the first audio signal associated with the received first environmental audio content corresponds to the emergency siren signal is determined based on the comparison. 10
4.The system (100) for emergency vehicle notification as claimed inclaim 1, wherein the controller (106) is further configured todetermine a type of an emergency vehicle based on the determinationthat the first audio signal associated with the determined first15 environmental audio content corresponds to the emergency sirensignal, wherein the type of the emergency vehicle is at least one of: anambulance, a fire truck, a police vehicle, and wherein the machinelearning model is applied based on the determined type of theemergency vehicle.20
5.The system (100) for emergency vehicle notification as claimed inclaim 1, wherein the one or more microphones (102) associated withthe vehicle (200) includes a first microphone and a secondmicrophone, wherein the first microphone is configured to determine25 second environmental audio content and the second microphone isconfigured to determine third environmental audio content.
6.The system (100) for emergency vehicle notification as claimed inclaim 1, wherein the controller (106) is further configured to:30
determine a first set of parameters associated with the second environmental audio content and the third environmental audio
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content, wherein the first set of parameters is at least one of: a time difference, an amplitude difference between the second environmental audio content and the third environmental audio content;
determine a second set of parameters associated with the 5 vehicle (200), wherein the second of parameters is at least one of: a speed of the vehicle (200), a state of the (200), a location of the vehicle (200), wherein the machine learning model is applied on the determined first set of parameters and the determined second set of parameters. 10
7.The system (100) for emergency vehicle notification as claimed inclaim 1, wherein the determined first environmental audio contentcomprises a set of first audio signals, and wherein the controller (106)is configured to filter the first audio signal corresponding to the15 emergency siren signal from the set of first audio signals.
8.The system (100) for emergency vehicle notification as claimed inclaim 1, wherein the controller (106) is configured to:
determine a state of the vehicle (200), wherein the state of the 20 vehicle (200) is at least one of: a stationary state, an idle state, ignition on state, engine running state, moving state, or parking state,
wherein the amplified first audio signal is rendered on the speaker (104) based on the determined state of the vehicle 25 (200).
9.The system (100) for emergency vehicle notification as claimed inclaim 8, wherein if the state of the vehicle (200) is one of: the ignitionon state, the engine running state, the moving state, the idle state, thenthe amplified first audio signal is rendered on the speaker (104).30
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10.The system (100) for emergency vehicle notification as claimed inclaim 1, wherein the determined direction is a front direction, or a reardirection, wherein if the direction is the rear direction, then the firstaudio signal is amplified, and wherein if the direction is the frontdirection, then the first audio signal is unamplified.5
11.The method for emergency vehicle notification, the methodcomprising:
receiving, by a controller (106), first environmental audio content associated with a vehicle (200) from one or more 10 microphones (102);
determining, by the controller (106), whether a first audio signal associated with the determined first environmental audio content corresponds to an emergency siren signal; 15
applying, by the controller (106), a machine learning model on the first audio signal based on the determination that the first audio signal associated with the determined first environmental audio content corresponds to the emergency siren signal; 20
determining, by the controller (106), a direction of the first audio signal based on the application of the machine learning model;
amplifying, by the controller (106), the first audio signal based on the determined direction; and 25
controlling, by the controller, the speaker (104) associated with the vehicle for rendering of the amplified first audio signal.
12.The method for emergency vehicle notification as claimed in claim 1130 comprising:
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determining, by the controller, a frequency of the first audio signal; and
comparing, by the controller, the determined frequency with a predefined emergency frequency band, wherein
whether the first audio signal associated with the 5 received first environmental audio content corresponds to the emergency siren signal is determined based on the comparison.
13.The method for emergency vehicle notification as claimed in claim 1110 comprising:
determining, by the controller, a first set of parameters associated with the second environmental audio content and the third environmental audio content, wherein the first set of parameters is at least one of: a time difference, an amplitude difference between the 15 second environmental audio content and the third environmental audio content; and
determining, by the controller, a second set of parameters associated with the vehicle (200), wherein the second of parameters is at least one of: a speed of the vehicle (200), a state of the (200), a 20 location of the vehicle (200), wherein the machine learning model is applied on the determined first set of parameters and the determined second set of parameters.
14.The method for emergency vehicle notification as claimed in claim 1125 comprising:
determining, by the controller, a state of the vehicle (200),
wherein the state of the vehicle (200) is at least one of: a stationary state, an idle state, ignition on state, engine running state, moving state, or parking state, and 30
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wherein the amplified first audio signal is rendered on the speaker (104) based on the determined state of the vehicle (200).
15.The method for emergency vehicle notification as claimed in claim5 11, wherein if the state of the vehicle (200) is one of: the ignition onstate, the engine running state, the moving state, the idle state, thenthe amplified first audio signal is rendered on the speaker (104).