A method, system and vehicle for controlling the communication environment

Abstract

This invention discloses a communication environment control method, system, electronic device, storage medium, and vehicle. The method includes determining whether a passenger is currently in a communication state based on real-time acquired in-vehicle image information; when a passenger is in a communication state, acquiring current in-vehicle noise data; locating the noise source emitting the noise data and the corresponding passenger, and obtaining the noise distance between the noise source and the passenger; based on the noise distance, calculating the adjustment ratio required to reach a preset target noise value according to a defined adjustment algorithm; dynamically adjusting the noise source according to the adjustment ratio until the noise data reaches the target noise value; and responding to a control signal indicating that the passenger has ended their communication, controlling the noise source to restore the noise data to its initial state. By automatically adjusting the noise source, noise interference in the cabin is effectively reduced. Passengers do not need to manually operate the noise source; the automatic adjustment of the noise source achieves stable and accurate results.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and in particular to a communication environment control method, system, electronic device, storage medium, and vehicle. Background Technology

[0002] Inside the cabin, passengers are often disturbed by other noises while making phone calls, such as the sound of air conditioning vents and audio system noise. These noises not only affect call quality but also impact the passenger's auditory experience. Furthermore, because passengers are on the phone, they are often unable to manually reduce these noises.

[0003] When passengers manually adjust noise sources in the cabin, such as adjusting the volume of the air conditioning vents or turning off the audio system, the following problems arise:

[0004] Inconvenient to operate: Passengers need to manually operate the device while making or receiving calls, which not only increases the complexity of the operation but may also affect the quality of the passenger's call.

[0005] Unstable adjustment effect: Manual adjustment is often limited by the speed and accuracy of operation, resulting in an unstable adjustment effect and difficulty in achieving the best noise reduction effect.

[0006] Lack of personalized service: Manual adjustment cannot be customized according to the needs of different passengers, and cannot meet the different needs of different passengers for sound environment.

[0007] Therefore, this application provides a call environment control method to solve the above-mentioned technical problems. Summary of the Invention

[0008] The purpose of this invention is to provide a method, system, electronic device, storage medium, and vehicle for controlling the call environment, which can solve at least one of the aforementioned technical problems.

[0009] To address the aforementioned technical problems, this invention provides a call environment control method, comprising:

[0010] Based on real-time acquired in-vehicle image information, it is determined whether the current occupants are in a call state, wherein the call state is determined based on the action data of the occupants contained in the in-vehicle image information;

[0011] When the person inside the vehicle is in the call state, the current noise data inside the vehicle is obtained, and the noise source emitting the noise data and the corresponding person inside the vehicle are located respectively, and the noise distance of the noise source relative to the person inside the vehicle is obtained.

[0012] Based on the noise distance, according to the defined adjustment algorithm, the adjustment ratio required to reach the preset target noise value is calculated. The noise source is dynamically adjusted according to the adjustment ratio until the noise data reaches the target noise value.

[0013] In response to a control signal indicating that the person inside the vehicle has ended the call, the noise source is controlled to restore the noise data to its initial state.

[0014] In some specific embodiments, based on real-time acquired in-vehicle image information, it is determined whether the occupants are currently on a call. The call status is determined based on the occupants' motion data contained in the in-vehicle image information, specifically including:

[0015] Based on the current operating status of the vehicle, the in-vehicle image information is acquired in real time, wherein the operating status includes the driving status;

[0016] Motion capture is performed on the acquired in-vehicle image information to obtain the motion data of the occupants contained in the in-vehicle images;

[0017] Based on the motion data, it is determined whether the person inside the vehicle is on a call.

[0018] In some specific embodiments, when the occupant is in the call state, current in-vehicle noise data is acquired, and the noise source emitting the noise data and the corresponding occupant are located respectively. The noise distance of the noise source relative to the occupant is obtained, specifically including:

[0019] When the person inside the vehicle is in the call state, obtain the location information of the person inside the vehicle and the noise source and lock them;

[0020] Obtain the angle information of the noise source relative to the occupants inside the vehicle;

[0021] Based on the angle information, the location information of the occupants in the vehicle, and the noise source, the noise distance of the noise source relative to the occupants in the vehicle is obtained.

[0022] In some specific embodiments, when the occupant is in the call state, before acquiring current in-vehicle noise data, locating the noise source emitting the noise data and the corresponding occupant, and acquiring the noise distance of the noise source relative to the occupant, the method further includes:

[0023] When the person inside the vehicle is in the call state, the person inside the vehicle is locked based on the in-vehicle image information;

[0024] Recognize the gesture data contained in the action data of the occupants in the vehicle;

[0025] The recognized gesture data is matched with a preset gesture recognition command. When the match is successful, the current in-vehicle noise data is obtained.

[0026] In some specific embodiments, based on the noise distance, an adjustment ratio required to reach a preset target noise value is calculated according to a defined adjustment algorithm. The noise source is then dynamically adjusted using this adjustment ratio until the noise data reaches the target noise value. Specifically, this includes:

[0027] The adjustment algorithm includes a noise attenuation algorithm and an adjustment ratio algorithm, wherein the noise attenuation algorithm includes:

[0028] L=L0-10lg(1 / 4πd) 2 );

[0029] Wherein, L represents the decibel value after noise attenuation; L0 represents the original decibel value of the noise; d represents the noise distance; 10lg represents the logarithm of the logarithm to the base 10; π represents pi.

[0030] Substitute the attenuated decibel value L into the adjustment ratio algorithm:

[0031] L(m-1) <= (X-(m-1)*3) dB;

[0032] Wherein, m represents the number of noise sources; X represents the preset target noise value;

[0033] Substitute the result of L(m-1) into the formula:

[0034] R = (L0 - L(m-1)) / L0 * 100%;

[0035] Wherein, R represents the adjustment ratio;

[0036] Based on the adjustment ratio, the noise source is dynamically adjusted until the noise data reaches the target noise value.

[0037] In some specific embodiments, in response to a control signal indicating that the person inside the vehicle has ended the call, the noise source is controlled to restore the noise data to its initial state, specifically including:

[0038] Based on the movement data of the people inside the vehicle, it is determined in real time whether the people inside the vehicle are maintaining the call status;

[0039] When the person inside the vehicle is not in the communication state, the control signal is triggered to control the noise source to restore the noise data to the initial state, wherein the initial state includes the noise data before adjustment, and the current noise data is saved when adjustment begins.

[0040] Based on the same concept, the present invention also provides a call environment control system, comprising:

[0041] The call status determination module is configured to determine whether the current occupant in the vehicle is in a call state based on real-time acquired in-vehicle image information, wherein the call status is determined based on the action data of the occupant in the vehicle contained in the in-vehicle image information;

[0042] The noise distance acquisition module is configured to acquire current in-vehicle noise data when the occupant is in the call state, locate the noise source emitting the noise data and the corresponding occupant, and acquire the noise distance of the noise source relative to the occupant.

[0043] The dynamic adjustment module is configured to calculate the adjustment ratio required to reach the preset target noise value based on the noise distance and according to a defined adjustment algorithm, and to dynamically adjust the noise source according to the adjustment ratio until the noise data reaches the target noise value.

[0044] The noise data restoration module is configured to control the noise source to restore the noise data to its initial state in response to a control signal indicating that the person inside the vehicle has ended the call.

[0045] Based on the same concept, the present invention also provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of a call environment control method.

[0046] Based on the same concept, the present invention also provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of a call environment control method.

[0047] Based on the same concept, the present invention also provides a vehicle equipped with the aforementioned call environment control system.

[0048] Compared with existing technologies, its advantages are as follows:

[0049] This invention discloses a method, system, electronic device, storage medium, and vehicle for controlling the call environment. By automatically adjusting the noise source, it effectively reduces noise interference in the cabin, improves call quality and auditory experience, and allows passengers to automatically adjust the noise source without manual operation. The adjustment effect is stable and accurate, meeting the different needs of different passengers for the sound environment. Attached Figure Description

[0050] Figure 1 This is a flowchart illustrating some specific embodiments of a call environment control method of the present invention;

[0051] Figure 2 This is a flowchart illustrating a call environment control method of the present invention in some applications;

[0052] Figure 3 This is a schematic diagram of the architecture of the call environment control method of the present invention in some applications;

[0053] Figure 4 This is a schematic diagram illustrating a call environment control method of the present invention in some applications.

[0054] Figure 5 This is a schematic diagram of the structure of a call environment control system according to some specific embodiments of the present invention;

[0055] Figure 6 This is a schematic diagram of the structure of an electronic device according to some specific embodiments of the present invention. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0057] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms “a,” “said,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0058] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0059] It should be understood that although the terms first, second, third, etc., may be used in the embodiments of this application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, first may also be referred to as second without departing from the scope of the embodiments of this application, and similarly, second may also be referred to as first.

[0060] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0061] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0062] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.

[0063] Reference Figure 1 A method for controlling the call environment, comprising:

[0064] S101, based on the real-time acquired in-vehicle image information, determine whether the current in-vehicle personnel are in a call state, wherein the call state is determined based on the action data of the in-vehicle personnel contained in the in-vehicle image information;

[0065] Understandably, in this step, cameras installed inside the vehicle capture real-time images of the interior, analyze these images, and extract data related to the actions of occupants. This action data includes, but is not limited to, head movements and gestures. The extracted action data is then identified and judged. If an occupant is detected making a phone call, such as holding a mobile phone, it is determined to be in a call state. When a call state is determined, the noise sources inside the vehicle are automatically adjusted, such as reducing the volume of the air conditioning vents and the audio system. By acquiring and analyzing action data from the in-vehicle images in real time, the function of automatically determining whether occupants are in a call state is achieved.

[0066] In some applications, to accurately determine whether occupants are on a call, real-time in-vehicle image information is used to determine whether they are currently on a call. The call status is determined based on the motion data of the occupants contained in the in-vehicle image information. Based on the current vehicle operating status, in-vehicle image information is acquired in real time, including the driving state. Motion capture is performed on the acquired in-vehicle image information to obtain the motion data of the occupants contained in the in-vehicle image. Based on the motion data, it is determined whether the occupants are on a call.

[0067] Understandably, in this application, when the vehicle is powered on, hardware devices such as cameras and sensors are initialized to ensure their normal operation. Data interfaces related to the vehicle's operating status are established to acquire real-time information about the vehicle's status. Cameras installed inside the vehicle capture images in real time and transmit this information to the control unit. The control unit simultaneously receives the vehicle's operating status information, analyzes the acquired images, and extracts data related to the actions of occupants. This action data includes, but is not limited to, head movements and gestures. Based on the vehicle's operating status information, the control unit determines the vehicle's movement status. For example, when the vehicle is moving, the control unit will determine it to be in motion, and will then determine the call status based on the action data and the movement status. If the vehicle is moving and detects an occupant making a phone call, such as holding a mobile phone, the control unit will determine it to be in a call state.

[0068] S102, when the person inside the vehicle is in the call state, the current noise data inside the vehicle is obtained, the noise source emitting the noise data and the corresponding person inside the vehicle are located respectively, and the noise distance of the noise source relative to the person inside the vehicle is obtained.

[0069] Understandably, when occupants are on a call, noise sensors installed inside the vehicle collect noise data in real time. This data is then transmitted to the control unit, which processes the data to identify and locate the noise source. During the location process, different noise sources are differentiated and located based on their sound characteristics. Once located, the noise source's location information is associated with the corresponding occupant, and the noise distance between the noise source and the occupant is calculated based on their relative positions. By acquiring in-vehicle noise data and locating noise sources, it is possible to accurately identify and address noise sources that interfere with calls, thereby improving in-vehicle call quality and the overall auditory experience.

[0070] In some applications, to accurately determine the noise distance of a noise source relative to the occupants of the vehicle, when the occupants are on a call, the current in-vehicle noise data is acquired, and the noise source emitting the noise data and the corresponding occupants are located. The noise distance between the noise source and the occupants is then determined. Furthermore, when the occupants are on a call, the location information of the occupants and the noise source is acquired and locked. The angle information of the noise source relative to the occupants is also acquired. Based on the angle information, the location information of the occupants, and the noise source, the noise distance between the noise source and the occupants is determined.

[0071] Understandably, in this application, multiple noise source detection devices are deployed inside the vehicle to monitor and collect noise data from each source in real time. For example, noise detectors are installed in areas such as the vehicle's amplifier, windows, seats, and air conditioning vents. These detectors monitor and record the decibel values ​​of each noise source in real time. To accurately measure the distance between the noise source and the occupants, a ranging camera and a gyroscope are also installed inside the vehicle. The ranging camera measures and locks onto the location of the noise source and the relative position of the head of an occupant making a phone call. The gyroscope measures the angle between the noise source and the occupant's head. Combining the measurement data from the ranging camera, the noise distance relative to the occupant is calculated using trigonometric functions. For example, if the angle between the noise source and the occupant's head is measured as θ degrees using the gyroscope, and the distance between the noise source and the occupant's head is measured as s meters using the ranging camera, the noise distance is calculated using trigonometric functions. Taking a sine function as an example, the formula is as follows:

[0072] d = s / sin(θ / 180×π)

[0073] Here, π is the mathematical constant pi, used to convert angles to radians. Using this formula, the noise distance can be calculated based on known angles and distance values.

[0074] In some embodiments, to meet personalized user needs, when an in-vehicle occupant is in a call state, the following steps are taken: acquiring current in-vehicle noise data; locating the noise source emitting the noise data and the corresponding in-vehicle occupant; and before acquiring the noise distance of the noise source relative to the in-vehicle occupant, the following steps are also taken: when an in-vehicle occupant is in a call state, locking the in-vehicle occupant based on in-vehicle image information; recognizing gesture data contained in the in-vehicle occupant's action data; matching the recognized gesture data with preset gesture recognition commands; and when a match is successful, acquiring current in-vehicle noise data.

[0075] Understandably, when an occupant is on a call, the vehicle's internal cameras capture and analyze real-time images of the interior. Based on the analysis, the system identifies and locks onto the occupant. After locking onto the occupant, it further captures their gesture data, including their movements. The identified gesture data is then matched in real-time with preset gesture recognition commands. When a match is successful, the corresponding control command is executed. Simultaneously, the system acquires information about the noise sources inside the vehicle and adjusts accordingly.

[0076] S103, based on the noise distance, according to the defined adjustment algorithm, calculate the adjustment ratio required to reach the preset target noise value, and dynamically adjust the noise source according to the adjustment ratio until the noise data reaches the target noise value;

[0077] Understandably, the adjustment algorithm calculates the required adjustment ratio to reach the preset target noise value. This algorithm dynamically adjusts based on actual noise data and the target noise value to ensure accuracy and real-time performance. Based on the calculated adjustment ratio, various noise sources are dynamically adjusted. For example, parameters of in-vehicle audio systems and air conditioning systems are adjusted to reduce or increase noise. Throughout the adjustment process, the collected noise data is continuously monitored, and the adjustment ratio is dynamically adjusted based on the noise data to ensure that the noise data gradually approaches and ultimately reaches the preset target value.

[0078] In some applications, to accurately calculate and adjust the noise modulation ratio, based on the noise distance and according to a defined modulation algorithm, the modulation ratio required to reach a preset target noise value is calculated. The noise source is then dynamically adjusted according to this ratio until the noise data reaches the target noise value. The modulation algorithm includes a noise attenuation algorithm and a modulation ratio algorithm. The noise attenuation algorithm includes:

[0079] L=L0-10lg(1 / 4πd) 2 );

[0080] Where L represents the attenuated decibel value; L0 represents the original decibel value of the noise; d represents the noise distance; 10lg represents the logarithm of the logarithm to base 10; π represents pi; Substituting the attenuated decibel value L into the adjustment ratio algorithm:

[0081] L(m-1) <= (X-(m-1)*3) dB;

[0082] Where m represents the number of noise sources; X represents the preset target noise value; substituting the result of L(m-1) into the formula:

[0083] R = (L0 - L(m-1)) / L0 * 100%;

[0084] Wherein, R represents the adjustment ratio; based on the adjustment ratio, the noise source is dynamically adjusted until the noise data reaches the target noise value;

[0085] Understandably, in this application, we assume there is an in-vehicle noise source with an original decibel value of L0 = 70 dB, and the distance between the noise source and the occupant's head is d = 2 meters. According to the formula L = L0 - 10lg(1 / 4πd) 2 ), calculate the attenuated decibel value L, first, calculate 1 / 4πd 2 We get 1 / 4π*2 2 =1.57, then calculate 10lg(1.57), which gives approximately 0.5dB. Finally, subtract 0.5dB from L0 = 70dB to obtain the attenuated decibel value L = 69.5dB.

[0086] Assuming the preset target noise value X is 40dB and the number of noise sources m is 2, substituting into the formulas L(m-1)<=(X-(m-1)*3)dB and L(2-1)<=(40-(2-1)*3)dB, then L(m-1) is 37dB. Substituting the result of L(m-1) 37dB into the formulas R=(L0-L(m-1)) / L0*100% and R=(70-37) / 70*100%, then the adjustment ratio R is equal to 47.14%, and finally the original decibel value L0 is reduced by 47.14%.

[0087] S104, in response to the control signal that the person in the vehicle has ended the call, the noise source is controlled to restore the noise data to its initial state.

[0088] Understandably, in this step, when the action of a person in the vehicle ending a call is detected, it is identified as a control signal. After receiving the control signal, the current noise data is collected, including the decibel values ​​of each noise source. Before starting the noise adjustment operation, the current noise data is stored as the initial state. Based on the initial noise data and the control signal, the parameters of each noise source, such as the volume of the audio system and the air conditioning fan speed, are automatically adjusted to restore the initial noise level.

[0089] In some applications, in order to perform an initial restoration when the person in the vehicle ends the call, in response to the control signal indicating that the person in the vehicle has ended the call, the noise source is controlled to restore the noise data to the initial state. Based on the person's action data, it is determined in real time whether the person in the vehicle is still in the call state. When the person in the vehicle is not in the call state, the control signal is triggered to control the noise source to restore the noise data to the initial state. The initial state includes the noise data before adjustment. When adjustment begins, the current noise data is saved.

[0090] Understandably, in this application, a control signal is triggered when it is determined that the occupants are not engaged in a conversation. Upon receiving the control signal, the noise sources are restored to their initial state. This initial state includes the noise data before adjustment, which is saved at the start of the adjustment process. Based on this saved initial noise data, the parameters of each noise source, such as the volume of the audio system and the air conditioning fan speed, are automatically adjusted to restore the initial noise level. For example, when the driver's action of ending a call is detected (such as lowering their hand or removing their head from the phone), it is determined that the call has ended. At this point, a control signal is triggered, and the data before adjustment is automatically retrieved from the saved initial noise data. Then, based on this data, the parameters of noise sources such as the audio system and air conditioning are adjusted to restore the noise data inside the vehicle to its initial state. The entire process is completed automatically without any additional driver intervention. By automatically adjusting the noise sources, noise interference in the cabin is effectively reduced, improving call quality and auditory experience. Passengers do not need to manually operate the noise sources; the automatic adjustment effect is stable and accurate, meeting the diverse sound environment needs of different passengers.

[0091] The following is combined Figures 2-4 This invention describes embodiments of a call environment control method in some applications:

[0092] like Figure 2 , Figure 3 and Figure 4 As shown:

[0093] Step 1: The in-vehicle OMS camera captures real-time motion data of the occupants and transmits it to the multi-mode control unit of the vehicle system to determine whether the occupants are making phone calls.

[0094] Step 2: If Step 1 detects that an occupant is making a phone call, the in-vehicle gesture recognition camera is activated, facing the occupant making the call, capturing the occupant's gesture data, and transmitting it to the multi-mode control unit of the vehicle system. The multi-mode control unit matches the occupant's gesture data with preset quiet gesture data.

[0095] Step 3: If the occupant gesture data from Step 2 matches the preset silence gesture data, then continue with the response operation:

[0096] Step A: Noise source detection measures the noise data (decibels L0 and distance d) for each noise source and sends it to the multi-mode control unit. Fixed-point noise detectors installed inside the vehicle (amplifier location, window location, seat location, air conditioning vent location) measure the decibel value (L0) of each noise source. A ranging camera and gyroscope are also installed inside the vehicle. The ranging camera measures the distance between the noise source location and the head of the person making the call, and the gyroscope measures the angle between the noise source location and the head of the person making the call. Then, trigonometric functions are used to calculate the actual distance (d) between the noise source location and the head of the person making the call.

[0097] Step B: The multi-mode control unit calculates the attenuated decibel value of each noise source when it reaches the head of the person making the call. The attenuated decibel value L = L0 - 10lg(1 / 4πd) 2 The noise sources are sorted from highest to lowest decibel value after attenuation: N1, N2, N3...Nm;

[0098] Step C: The multi-mode control unit calculates the highest decibel value of each noise source after adjustment and the percentage reduction that the decibel value should be. According to the noise superposition principle, when two noise sources have the same decibel value (L1 = L2), the superimposed decibel value L = L1 + 3. The goal is to reduce the noise superposition value at the phone call location to 40 (quiet environment). The decibel values ​​of each noise source are adjusted according to the following rules:

[0099] LN1 <= 37dB;

[0100] LN2 <= 34dB;

[0101] LN3 <= 31dB;

[0102] LN(m-1) <= (40-(m-1)*3) dB;

[0103] LNm <= (40 - (m - 1) * 3) dB;

[0104] If the calculated L < 0, then take 0;

[0105] The decibel reduction percentage for each noise source should be: R = (L0 - L) / L0 * 100%.

[0106] Step D: The multi-mode control unit distributes the decibel reduction ratio R of each noise source to each noise source control module. Each control module reduces the volume accordingly according to the reduction ratio, and each control module remembers the noise state before the reduction.

[0107] Step 4: The in-vehicle OMS camera captures the motion data of passengers making phone calls and transmits it to the multi-mode control unit of the vehicle system to determine whether the passenger is still making phone calls.

[0108] Step 5: If the passenger stops making a phone call in Step 4, the multi-mode control unit will transmit the stop phone call signal S to the noise source control module that performs noise reduction in Step 3. After receiving the stop phone call signal S, each control module will restore each noise source to the state before noise reduction.

[0109] The following describes this embodiment in conjunction with an application scenario:

[0110] Imagine a passenger in the left rear seat of a car receiving an important phone call from their boss while the car is in motion. The car's interior environment is as follows: the window is slightly ajar, the air conditioning is on (fan speed 4), music is playing at volume 15, navigation is in progress at volume 15, and the front passenger and right rear passenger are talking.

[0111] Step 1: The in-vehicle motion capture camera detects whether passengers are making or receiving phone calls. In this case, a passenger in the left rear seat is detected making or receiving a phone call, and the current phone call status of all occupants in the vehicle is recorded.

[0112]

[0113] Step Two: The in-vehicle gesture recognition camera detects whether a passenger making a phone call is making a predefined gesture, such as opening their palm and swiping downwards twice. If a passenger making a phone call (i.e., the passenger in the left rear seat) makes the predefined gesture, it indicates that the passenger requires cabin noise reduction.

[0114]

[0115] Step 3: Inspect the noise sources in the cockpit and respond accordingly. Noise source detection mainly involves measuring the straight-line distance between the noise source and the phone call location, and the noise level in decibels.

[0116]

[0117]

[0118] Calculate the noise intensity at each point where the phone call is made:

[0119]

[0120]

[0121] Noise superposition:

[0122] (1) First, find the difference between L1 and L2: L1-L2;

[0123] (2) Find the increment ΔL from the table based on the obtained difference;

[0124] (3) Calculate the combined sound pressure level value from L1+L2=L1+△L.

[0125]

[0126] When two sound pressure levels are equal, the combined L = L1 + 3dB; when the two sound pressure levels are unequal, the increase does not exceed 3dB (L1 > L2, L1 + L2 ≤ L1 + 3); when the two sound pressure levels are unequal, if the difference is ≥10dB, the increase is very small and can be ignored, still equal to L1. For example, if L1 = 90dB and L2 = 75dB, the combined L = 90dB; when multiple sound sources are superimposed, they are superimposed pairwise successively, regardless of the order.

[0127] System response to noise:

[0128] The goal is to reduce the noise superposition value at the phone call location to 40 (in a quiet environment), assuming there are a total of m noise sources:

[0129] The noise with the highest intensity at the location where you make the call needs to be reduced to 37.

[0130] The second loudest noise at the location where you make a phone call needs to be reduced to 34.

[0131] If the noise level is the third highest at the location where you are making a phone call, you need to reduce its intensity to 31.

[0132] The noise with the highest intensity m-1 at the location where the phone is being made needs to be reduced to 40-(m-1)*3;

[0133] For the noise with the highest intensity m at the location where the phone is being made, its intensity needs to be reduced to 40-(m-1)*3; if the calculated intensity is less than 0, then take 0.

[0134]

[0135]

[0136] Step 4: The in-vehicle motion capture camera detects passengers making or receiving phone calls (i.e., the left rear passenger) and checks if their phone-making activity has stopped. If the left rear passenger stops making or receiving phone calls, the system updates the phone-making status for all passengers in the vehicle.

[0137]

[0138]

[0139] Step 5: If Step 4 is satisfied, then all responses made in Step 3 will be restored to their previous state: the car window is open for ventilation (a small crack is opened), the air conditioning is on with a fan speed of 4, music is playing in the car with a volume of 15, and the navigation is broadcasting with a volume of 15.

[0140] For the purpose of simplicity, the method steps disclosed in the above embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0141] like Figure 5 As shown, the present invention also provides a call environment control system, comprising:

[0142] The call status determination module 201 is configured to determine whether the current person in the vehicle is in a call state based on the real-time acquired in-vehicle image information, wherein the call status is determined based on the action data of the person in the vehicle contained in the in-vehicle image information.

[0143] The noise distance acquisition module 202 is configured to acquire current in-vehicle noise data when the occupant is in the call state, locate the noise source emitting the noise data and the corresponding occupant, and acquire the noise distance of the noise source relative to the occupant.

[0144] The dynamic adjustment module 203 is configured to calculate the adjustment ratio required to reach the preset target noise value based on the noise distance and according to a defined adjustment algorithm, and to dynamically adjust the noise source according to the adjustment ratio until the noise data reaches the target noise value.

[0145] The noise data restoration module 204 is configured to control the noise source to restore the noise data to its initial state in response to a control signal indicating that the person in the vehicle has ended the call.

[0146] It is worth noting that although only some basic functional modules are disclosed in the embodiments of this invention, it does not mean that the composition of this system is limited to the above-mentioned basic functional modules. On the contrary, what this embodiment intends to express is that, based on the above-mentioned basic functional modules, those skilled in the art can arbitrarily add one or more functional modules in combination with existing technology to form an infinite number of embodiments or technical solutions. That is to say, this system is open rather than closed. The fact that this embodiment only discloses a few basic functional modules should not be considered as the scope of protection of the claims of this invention being limited to the disclosed basic functional modules. At the same time, for the convenience of description, the above device is described separately according to its functions as various units and modules. Of course, in implementing this invention, the functions of each unit and module can be implemented in one or more software and / or hardware.

[0147] like Figure 6 As shown, the present invention also provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of a call environment control method.

[0148] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. For example... Figure 6 The structure shown in this embodiment of the invention includes an electronic device comprising one or more processors 710 and a storage device 720; the processors 710 in this electronic device may be one or more. Figure 6 Taking a processor 710 as an example; a storage device 720 is used to store one or more programs; the one or more programs are executed by the one or more processors 710, causing the one or more processors 710 to implement the call environment control method as described in any one of the embodiments of the present invention.

[0149] The electronic device may also include an input device 730 and an output device 740.

[0150] The processor 710, storage device 720, input device 730, and output device 740 in this electronic device can be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0151] The storage device 720 in this electronic device serves as a computer-readable storage medium, capable of storing one or more programs. These programs can be software programs, computer-executable programs, or modules, such as the program instructions / modules corresponding to the call environment control method provided in this embodiment of the invention. The processor 710 executes various functional applications and data processing of the electronic device by running the software programs, instructions, and modules stored in the storage device 720, thereby implementing the call environment control method described in the above embodiment.

[0152] Storage device 720 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the electronic device. Furthermore, storage device 720 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, storage device 720 may further include memory remotely located relative to processor 710, which can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0153] Input device 730 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the electronic device. Output device 740 may include display devices such as a display screen.

[0154] The present invention also provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of a call environment control method.

[0155] Specifically, the computer storage medium in this embodiment of the invention can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be—but is not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0156] The present invention also provides a vehicle equipped with a call environment control system as described above.

[0157] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the call environment, characterized in that, include: Based on real-time acquired in-vehicle image information, it is determined whether the current occupants are in a call state, wherein the call state is determined based on the action data of the occupants contained in the in-vehicle image information; When the person inside the vehicle is in the call state, the current noise data inside the vehicle is obtained, and the noise source emitting the noise data and the corresponding person inside the vehicle are located respectively, and the noise distance of the noise source relative to the person inside the vehicle is obtained. Based on the noise distance, according to the defined adjustment algorithm, the adjustment ratio required to reach the preset target noise value is calculated. The noise source is dynamically adjusted according to the adjustment ratio until the noise data reaches the target noise value. In response to a control signal indicating that the person inside the vehicle has ended the call, the noise source is controlled to restore the noise data to its initial state.

2. The call environment control method according to claim 1, characterized in that, Based on real-time acquired in-vehicle image information, it is determined whether the occupants are currently on a call. The call status is determined based on the occupants' motion data contained in the in-vehicle image information, specifically including: Based on the current operating status of the vehicle, the in-vehicle image information is acquired in real time, wherein the operating status includes the driving status; Motion capture is performed on the acquired in-vehicle image information to obtain the motion data of the occupants contained in the in-vehicle images; Based on the motion data, it is determined whether the person inside the vehicle is on a call.

3. The call environment control method according to claim 1, characterized in that, When the occupants are in the call state, the current in-vehicle noise data is acquired, and the noise source emitting the noise data and the corresponding occupants are located. The noise distance of the noise source relative to the occupants is obtained, specifically including: When the person inside the vehicle is in the call state, obtain the location information of the person inside the vehicle and the noise source and lock them; Obtain the angle information of the noise source relative to the occupants inside the vehicle; Based on the angle information, the location information of the occupants in the vehicle, and the noise source, the noise distance of the noise source relative to the occupants in the vehicle is obtained.

4. The call environment control method according to claim 3, characterized in that, When the occupant is in the call state, the method further includes: acquiring current in-vehicle noise data, locating the noise source emitting the noise data and the corresponding occupant, and before acquiring the noise distance of the noise source relative to the occupant, the method further includes: When the person inside the vehicle is in the call state, the person inside the vehicle is locked based on the in-vehicle image information; Recognize the gesture data contained in the action data of the occupants in the vehicle; The recognized gesture data is matched with a preset gesture recognition command. When the match is successful, the current in-vehicle noise data is obtained.

5. The call environment control method according to claim 3, characterized in that, Based on the noise distance, according to the defined adjustment algorithm, the adjustment ratio required to reach the preset target noise value is calculated. The noise source is then dynamically adjusted using this adjustment ratio until the noise data reaches the target noise value. Specifically, this includes: The adjustment algorithm includes a noise attenuation algorithm and an adjustment ratio algorithm, wherein the noise attenuation algorithm includes: L=L0-10 lg(1 / 4πd 2 ); Wherein, L represents the decibel value after noise attenuation; L0 represents the original decibel value of the noise; d represents the noise distance; 10lg represents the logarithm of the logarithm to the base 10; π represents pi. Substitute the attenuated decibel value L into the adjustment ratio algorithm: L(m-1) <= (X-(m-1)*3) dB; Wherein, m represents the number of noise sources; X represents the preset target noise value; Substitute the result of L(m-1) into the formula: R = (L0 - L(m-1)) / L0 * 100%; Wherein, R represents the adjustment ratio; Based on the adjustment ratio, the noise source is dynamically adjusted until the noise data reaches the target noise value.

6. The call environment control method according to claim 5, characterized in that, In response to a control signal indicating that the person inside the vehicle has ended the call, the noise source is controlled to restore the noise data to its initial state, specifically including: Based on the movement data of the people inside the vehicle, it is determined in real time whether the people inside the vehicle are maintaining the call status; When the person inside the vehicle is not in the communication state, the control signal is triggered to control the noise source to restore the noise data to the initial state, wherein the initial state includes the noise data before adjustment, and the current noise data is saved when adjustment begins.

7. A call environment control system, characterized in that, include: The call status determination module is configured to determine whether the current occupant in the vehicle is in a call state based on real-time acquired in-vehicle image information, wherein the call status is determined based on the action data of the occupant in the vehicle contained in the in-vehicle image information; The noise distance acquisition module is configured to acquire current in-vehicle noise data when the occupant is in the call state, locate the noise source emitting the noise data and the corresponding occupant, and acquire the noise distance of the noise source relative to the occupant. The dynamic adjustment module is configured to calculate the adjustment ratio required to reach the preset target noise value based on the noise distance and according to a defined adjustment algorithm, and to dynamically adjust the noise source according to the adjustment ratio until the noise data reaches the target noise value. The noise data restoration module is configured to control the noise source to restore the noise data to its initial state in response to a control signal indicating that the person inside the vehicle has ended the call.

8. An electronic device, characterized in that, include: The system includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus; the memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, It stores a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the method according to any one of claims 1 to 6.

10. A vehicle, characterized in that, The vehicle is equipped with a call environment control system as described in claim 7.

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