WO2021102755A1 - 一种预防生命体被遗留在车辆内的方法及装置 - Google Patents

一种预防生命体被遗留在车辆内的方法及装置 Download PDF

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Publication number
WO2021102755A1
WO2021102755A1 PCT/CN2019/121343 CN2019121343W WO2021102755A1 WO 2021102755 A1 WO2021102755 A1 WO 2021102755A1 CN 2019121343 W CN2019121343 W CN 2019121343W WO 2021102755 A1 WO2021102755 A1 WO 2021102755A1
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WIPO (PCT)
Prior art keywords
vehicle
terminal
photo
living body
recognition result
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PCT/CN2019/121343
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English (en)
French (fr)
Inventor
阳俊林
Original Assignee
宇龙计算机通信科技(深圳)有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by 宇龙计算机通信科技(深圳)有限公司 filed Critical 宇龙计算机通信科技(深圳)有限公司
Priority to PCT/CN2019/121343 priority Critical patent/WO2021102755A1/zh
Priority to CN201980102507.9A priority patent/CN114846773A/zh
Publication of WO2021102755A1 publication Critical patent/WO2021102755A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R21/00—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks
    • B60R21/01—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents
    • B60R21/015—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents including means for detecting the presence or position of passengers, passenger seats or child seats, and the related safety parameters therefor, e.g. speed or timing of airbag inflation in relation to occupant position or seat belt use
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]

Definitions

  • This application relates to the field of communication technology, and in particular to a method and device for preventing life from being left in a vehicle.
  • the embodiments of the present application provide a method and device for preventing life from being left in a vehicle, which can overcome the defects of the prior art, can effectively prevent life from being left in a vehicle, and improve user experience.
  • an embodiment of the present application provides a method for preventing a living body from being left in a vehicle, including:
  • a reminder message including the recognition result is sent to the terminal.
  • the tracker obtains the detection value of the under-seat pressure sensor, and compares the detection value with the threshold value. If the value is greater than or equal to the threshold, it indicates that there may be living bodies in the vehicle. Then take pictures of the environment in the vehicle and identify the obtained photos. The recognition result can indicate whether there are living bodies in the vehicle. The recognition result indicates that there is a living body in the vehicle. In the case of a living body, a reminder message containing the recognition result is sent to the terminal.
  • the implementation of the embodiments of the present application determines whether to send a reminder message to the terminal according to the relationship between the detection value of the pressure sensor and the threshold value and the recognition result of the photo in the vehicle, which can effectively prevent life bodies from being left in the vehicle and improve the user experience.
  • the identifying the photo includes:
  • the neural network recognition model is pre-trained based on multiple photos in the training set, and each photo in the training set includes a tag, and the tag is used to indicate whether all photos in the training set exist. Narrative life body.
  • the neural network recognition model is pre-trained based on multiple photos that include tags.
  • the tags are used to indicate whether there are living bodies in the photos.
  • the method further includes :
  • Receive window opening instructions and/or door opening instructions sent by the terminal and perform operations according to the window opening instructions and/or door opening instructions.
  • the tracker will send a reminder message to the terminal.
  • the terminal After the terminal receives the reminder message, the user finds that there is a living body in the vehicle by viewing the reminder message.
  • the terminal sends window opening instructions and/or door opening instructions to the tracker, and the tracker receives the instructions and operates according to the window opening instructions and/or door opening instructions, thereby avoiding life bodies being left in the closed vehicle for a long time and preventing accidents The incident happened.
  • the method before receiving the window opening instruction and/or the door opening instruction sent by the terminal, the method further includes:
  • the camera in the vehicle is activated to realize a video connection with the terminal to further confirm the condition of the living body in the vehicle.
  • the tracker may also receive the video connection instruction sent by the terminal.
  • the terminal user can see the inside of the vehicle and can further determine The condition of living organisms in the vehicle.
  • the method further includes:
  • the photo is sent to the terminal to further confirm the condition of the living body in the vehicle.
  • the tracker may also receive the photographing instruction sent by the terminal, and can send the above-photographed photos to the terminal, so that the terminal user can further determine the condition of the living body by viewing the target photo .
  • the embodiments of the present application provide a device for preventing life from being left in a vehicle, including:
  • the judgment module is used to obtain the detection value of the seat pressure sensor when the doors and windows of the vehicle are in the locked state, and determine whether the detection value is greater than or equal to the threshold;
  • the camera module is configured to take a picture of the environment inside the vehicle to obtain a photo when it is determined that the detection value is greater than or equal to the threshold value;
  • the recognition module is used to recognize the photo and obtain the recognition result
  • the communication module is configured to send a reminder message containing the recognition result to the terminal when the recognition result indicates that there is a living body in the vehicle.
  • the identification module is specifically configured to:
  • the neural network recognition model is pre-trained based on multiple photos in the training set, and each photo in the training set includes a tag, and the tag is used to indicate whether all photos in the training set exist. Narrative life body.
  • the communication module is further configured to receive The window opening instruction and/or the door opening instruction sent by the terminal are operated according to the window opening instruction and/or the door opening instruction.
  • the communication module is also used to receive a video connection instruction sent by the terminal;
  • the camera module is also used to activate the camera in the vehicle to realize a video connection with the terminal to further confirm the condition of the living body in the vehicle.
  • the communication module is further configured to receive a photographing instruction sent by the terminal; and send the photo to the terminal to further confirm the condition of the living body in the vehicle.
  • the device can be applied to a vehicle tracker.
  • Each functional module in the device provided in the embodiment of the present application is specifically used to implement the method described in the first aspect.
  • an embodiment of the present application provides a computing device, including a processor, a communication interface, and a memory; the memory is used to store instructions, the processor is used to execute the instructions, and the communication interface is used to receive or send Data; wherein, when the processor executes the instructions, it executes the method described in the first aspect or any specific implementation of the first aspect.
  • an embodiment of the present application provides a system for preventing life from being left in a vehicle, including: a vehicle tracker, a door control module, a window control module, and a terminal.
  • the door control module is the control unit of the door, which can control the opening and closing of the door.
  • the window control module is the control unit of the window, which can control the opening and closing of the window.
  • the vehicle's tracker can obtain the state of the doors and windows. When the doors and windows are locked, the detection value of the pressure sensor under the seat is obtained, and the detection value is compared with the threshold value.
  • the camera in the vehicle is started to take a photo, the photo obtained from the photo is input into the recognition model for recognition, the recognition result is obtained, and a reminder message is sent to the terminal according to the recognition result.
  • the terminal user can choose to send a video connection instruction or a photo instruction through the terminal to further determine the condition of the living body in the vehicle, and then the terminal user can also choose to send the window opening and the window according to the condition of the living body in the vehicle.
  • the tracker operates according to the window opening and/or door opening instructions to prevent life from being left in the closed vehicle for a long time.
  • an embodiment of the present application provides a non-volatile storage medium for storing program instructions.
  • program instructions When the program instructions are applied to a tracker of a vehicle, they can be used to implement the method described in the first aspect.
  • an embodiment of the present application provides a computer program product that includes program instructions.
  • the vehicle tracker executes the method described in the first aspect.
  • the computer program product may be a software installation package.
  • the computer program product may be downloaded and executed on the tracker of the vehicle. , In order to realize the method described in the first aspect.
  • the embodiment of the present application provides a method for preventing life from being left in a vehicle, and the method is applied to a tracker of a vehicle.
  • the door status and the window status are both locked, compare the detection value of the under-seat pressure sensor with the threshold value. If the detection value is greater than or equal to the threshold value, it indicates that there may be living bodies in the vehicle. In this case Next, start the camera in the vehicle, take a picture of the seat position of the vehicle, and then input the captured photo into the neural network recognition model for recognition, because the neural network recognition model is pre-trained from multiple photos including tags.
  • the tag is used to indicate whether there is a living body in the photo, so if the recognition result indicates that there is a living body in the vehicle, in this case, the tracker sends a reminder message containing the recognition result to the terminal.
  • the terminal receives the reminder message.
  • You can choose to further determine the condition of the living body in the vehicle through the video screen or through the photo, and then according to the situation of the living body, choose to send the window and/or door opening instructions, the tracker receives the corresponding instructions, and operates according to the corresponding instructions.
  • the implementation of the embodiments of the present application can effectively prevent life bodies from being left in the vehicle, reduce the occurrence of accidents, and improve the user experience.
  • FIG. 1 is a schematic diagram of a system architecture provided by an embodiment of the application
  • FIG. 2 is a schematic diagram of a method for preventing life from being left in a vehicle according to an embodiment of the application;
  • FIG. 3 is a schematic diagram of another method for preventing life from being left in a vehicle provided by an embodiment of the application;
  • FIG. 4 is a schematic diagram of another method for preventing life from being left in a vehicle according to an embodiment of the application.
  • FIG. 5 is a schematic diagram of a device for preventing life from being left in a vehicle according to an embodiment of the application
  • Fig. 6 is a schematic diagram of another device for preventing life from being left in a vehicle provided by an embodiment of the application;
  • Fig. 7 is a schematic diagram of another device for preventing life from being left in a vehicle provided by an embodiment of the application.
  • FIG. 1 is a schematic diagram of a system architecture provided by an embodiment of the present application.
  • the system architecture relates to a vehicle and a terminal, wherein a tracker is provided in the vehicle, and the vehicle is in communication with the terminal.
  • the vehicle can send information or instructions to the terminal, or receive information or instructions sent by the terminal, and then perform follow-up operations based on the information or instructions.
  • the terminal can receive information or instructions sent by the vehicle, or send information or instructions to the vehicle.
  • the terminal may be a mobile device such as a mobile phone, a tablet computer, a bracelet, a headset, etc. that can realize wireless communication, or even other wearable devices with communication functions.
  • Figure 2 is a method for preventing life from being left in a vehicle provided by an embodiment of the present application.
  • the method process includes but is not limited to the following steps:
  • the state includes an unlocked state and a locked state.
  • the user can freely set the tracker on or off according to the actual situation. For example, the user can set it to automatically start the tracker when the vehicle is parked or locked to prevent life from being left in the vehicle.
  • the tracker can obtain the state of the door through the door control module.
  • the door control module is the door control module, which can control the opening and closing of the door.
  • the locked state of the door here includes the state when all the doors on the vehicle are closed, and the unlocked state of the door This includes the state where at least one door of the vehicle is open.
  • the tracker can also obtain the status of the window through the window control module.
  • the window control module is the window control module, which can control the opening and closing of the window.
  • the locked state of the window here includes all the windows on the vehicle are closed.
  • the unlocked state of the window includes a state in which at least one window on the vehicle is open.
  • the door control module and the window control module can be deployed on an integrated electronic control unit (ECU), or they can be deployed on multiple independently deployed electronic control units (ECU).
  • ECU integrated electronic control unit
  • ECU independently deployed electronic control units
  • the pressure sensor under the seat can be a pressure sensor under a child seat, or a pressure sensor under any seat inside the vehicle, and the detection value of the pressure sensor is an output parameter of the pressure sensor.
  • the detection value of the pressure sensor is an output parameter of the pressure sensor.
  • it can be a mass value indicating the weight of a person or object, or a gravity value indicating the weight of a person or object, etc.
  • the type of the pressure sensor and the detection value type are not specifically limited here.
  • the tracker When the door and window are both locked, the tracker first obtains the detection value of the pressure sensor under the seat, and then compares the detection value with a preset threshold to determine whether the detection value is greater than or equal to The preset threshold value, if it is judged that the detection value is less than the preset threshold value, it means that there must be no life in the seat position where the pressure sensor is located, and the process can be ended; if it is judged that the detection value is greater than If it is equal to the preset threshold value, it indicates that there may be a living body in the seat position where the pressure sensor is located, and the subsequent step 203 needs to be continued.
  • the living body here means a living person or thing, such as the elderly, children, pets, etc. In actual applications, it can be set by the user according to the actual situation.
  • the preset threshold can be set by the user according to the actual situation. For example, if the owner often carries a pet to go out, and the output value of the pressure sensor is the quality, the threshold can be set to the approximate quality of the pet ; If the output value of the pressure sensor is gravity, the owner can set the threshold to the approximate gravity of the pet. For another example, if the car owner often carries a baby or the elderly out, the output value of the pressure sensor is mass, and the threshold can be set to the approximate mass of the baby or the approximate mass of the elderly; if the output value of the pressure sensor is gravity, the owner can Set the threshold to the approximate weight of a baby or the approximate weight of an elderly.
  • the detection value is greater than or equal to the threshold value
  • perform photo recognition to obtain a recognition result, and determine whether the recognition result indicates whether there is a living body in the vehicle. If the recognition result indicates that there is a living body in the vehicle, the subsequent step 204 is continued; if the recognition result indicates that there is no living body in the vehicle, the process is ended.
  • the detection value is greater than or equal to the threshold value, it indicates that there is a living body or a non-living body on the seat, and further photo identification can be used to determine whether it is a living body.
  • the camera can be the camera of the driving recorder inside the vehicle (this camera needs to be able to capture the position of the seat or the situation of all the space environment in the vehicle), or it can be an independent camera, or the camera can be coupled with the tracker. together.
  • the photos obtained by taking pictures obtain the recognition results, and determine whether there are living bodies in the vehicle according to the recognition results.
  • photo recognition There are many methods for photo recognition. For example, you can extract the features of the photo based on some algorithms, and then match the features of the extracted photo with the features stored in the tracker, and use the results to identify whether there are living bodies in the photo. .
  • a neural network recognition model can be used to recognize photos, and the obtained photos can be input into the neural network recognition model for recognition, and the recognition result is obtained, and the recognition result indicates whether there is a living body in the vehicle.
  • the method for recognizing photos is not specifically limited.
  • This method first needs to train the neural network recognition model, and then use the trained neural network recognition model to recognize the photo.
  • the neural network recognition model is pre-trained based on multiple photos, and each photo includes a label, which is used to indicate whether there is a living body in the photo.
  • the multiple photos can be photos containing life forms that the user takes in advance through the camera in the vehicle and stored in the tracker, or the photos containing life forms are copied into the tracker of the vehicle through the mobile device in advance.
  • Yes and there is at least one living body contained in the photo.
  • this living body may be a child, an old man, or a dog.
  • the photo contains various postures of each living body.
  • the label is used to indicate whether there is a living body in the photo, for example, if the photo used in the training sample is a photo of a child in the owner’s family, the label is "Life: Child", if the photo used in the training sample is the owner’s family The photo of the old man in the village is labeled as "Life: Old Man”. If the photo used in the training sample is a photo of a pet dog in the owner's home, the label is "Life: Dog", etc.
  • the taken photos are input into the trained neural network recognition model for recognition, and the recognition result is obtained.
  • the recognition result indicates whether there are living bodies in the vehicle.
  • the training samples used include photos containing children, photos containing old people, photos containing dogs, a total of three life forms of multi-posture photos, if the captured photos include dogs, it will be included
  • the dog’s photo is input into the trained neural network recognition model for recognition, and the recognition result can be obtained: "Recognition is successful, life body: dog”; if the photo taken contains a potted flower, input the photo containing a potted flower into the trained Recognition in the neural network recognition model, you can get the recognition result: "recognition failed, inanimate body”; if the taken photo contains the child's mother, input the photo of the child's mother into the trained neural network recognition model.
  • Recognition you can get the recognition result: "Recognition failed, inanimate body”; if the taken photo contains a child, input the photo containing the child into the trained neural network recognition model for recognition, and the recognition result can be obtained: "Recognition successful , Life Body: Child”, etc.
  • the photo before recognizing the photo, can be processed first, for example, the image segmentation method is used to segment the target subject in the photo, and the image enhancement method is applied to the segmented photo to enhance the photo, etc. And so on, can achieve a better recognition effect.
  • the tracker sends a reminder message to the terminal.
  • a reminder message containing the recognition result needs to be sent to the terminal. Accordingly, after the terminal receives the reminder message, the user obtains the information in the vehicle by viewing the reminder message. News of living entities.
  • the terminal sends a window opening instruction and/or a door opening instruction, and accordingly, the tracker receives a window opening instruction and/or a door opening instruction.
  • the user can send a window opening instruction to the tracker through the terminal, or send a door opening instruction, or send both the window opening instruction and the door opening instruction, and the tracker will receive the window opening instruction accordingly. Either the door opening instruction, or both the window opening instruction and the door opening instruction are received.
  • the tracker operates according to the window opening instruction and/or the door opening instruction.
  • the tracker After the tracker receives the window opening command, it sends the window opening command to the window control module of the vehicle, and the window control module receives the command and controls the window to open.
  • the air in the vehicle circulates with the outside air, and the living bodies in the vehicle can breathe fresh air, which prevents accidents caused by the living bodies being left in the vehicle for a long time.
  • the tracker after receiving the door opening instruction, the tracker sends the door opening instruction to the door control module of the vehicle, and the door control module receives the instruction and controls the door to open. In this way, the living bodies in the vehicle can come out and will not be left in the vehicle.
  • the tracker after receiving the window opening command and the door opening command, the tracker sends the window opening command to the vehicle window control module, and the door opening command is sent to the vehicle door control module, and then the window control module receives the window opening command. , Control the window to open, the door control module will control the door to open after receiving the door opening command. Similarly, living bodies will not cause accidents because they are left in the vehicle.
  • step 201 is optional.
  • the tracker can obtain the locked state of the doors and windows in other ways; steps 205 and 206 are optional.
  • After the tracker sends a reminder message containing the recognition result to the terminal The user obtains the recognition result and determines that there is a living body in the vehicle, and other methods can also be used to prevent the living body from being left in the vehicle to ensure the safety of the living body.
  • the owner’s vehicle is placed downstairs, and the children of the owner’s family play downstairs. After a while, they get tired of playing and climb into the car and rest in it. Unexpectedly, because they are too tired to play, The child fell asleep in the car, but now the doors and windows of the car are closed, the air in the car is limited and there is no circulation. In this case, it is very dangerous for the child to sleep in the car. If you sleep for a long time , There may be life-threatening.
  • the tracker on the car acquires that the doors and windows are locked, and then acquires the detection value of the pressure sensor, after judging that the detection value exceeds the preset threshold, the tracker starts the neural network to proceed.
  • Recognition If the recognition result indicates that there is a living body in the vehicle, the tracker will send a reminder message to the owner’s mobile phone. The reminder message includes the recognition result.
  • the owner can send window opening instructions and door opening instructions to the tracker
  • the tracker then opens the windows and doors of the car according to the window opening instructions and door opening instructions to realize the circulation of air inside and outside the vehicle, thereby ensuring the safety of the children.
  • the owner knows that there are children in the car, they still need Move the child out of the car as soon as possible so that they can breathe the fresh air outside the car.
  • the tracker obtains the state of the door, the window, and the detection value of the seat pressure sensor, and determines the relationship between the detection value and the threshold value.
  • the neural network is activated to identify whether there is a living body in the vehicle. After identification, if it is determined that there is a living body in the vehicle, the tracker sends a reminder message to the terminal. After the terminal receives the reminder message, it can send an open message to the tracker. Window instructions and/or door opening instructions to prevent life from being left in the vehicle. Therefore, the implementation of the embodiments of the present application can prevent accidents from occurring due to life being left in the vehicle.
  • photo recognition is performed.
  • the tracker sends a reminder message to the terminal.
  • the terminal After the terminal receives the reminder message, it can further confirm the inside of the vehicle through the video screen.
  • the terminal After the specific situation of the living body, after confirming the specific situation of the living body, the terminal can also send a warning instruction to prevent the living body from being left in the vehicle, see Figure 3.
  • the tracker obtains the state of the doors and windows of the vehicle, and the state includes an unlocked state and a locked state.
  • the detection value is greater than or equal to the threshold value
  • perform photo recognition to obtain a recognition result, and determine whether the recognition result indicates whether there is a living body in the vehicle. If the recognition result indicates that there is a living body in the vehicle, the subsequent step 204 is continued; if the recognition result indicates that there is no living body in the vehicle, the process is ended.
  • the tracker sends a reminder message to the terminal.
  • the terminal user After the terminal user has determined that there is a living body in the vehicle by viewing the reminder message, he can further confirm the situation of the living body in the form of a video screen.
  • the process of establishing a video connection between the terminal and the tracker is as follows.
  • the terminal sends a video connection instruction to the tracker.
  • the tracker activates the camera to take pictures of the inside of the vehicle, so that the terminal can view the inside of the vehicle.
  • the end user can further determine the condition of the living body through the video screen, for example, can further confirm the recognition result of the neural network, and check the physical health of the living body.
  • the terminal sends a warning instruction, and correspondingly, the tracker receives the warning instruction.
  • the end user can also send warning instructions to the tracker to seek help from nearby people.
  • the warning instruction can be to activate the horn, or to activate the dual flashing lights, or to activate the horn and turn on the flashing lights.
  • the tracker receives the warning instruction sent by the terminal.
  • the tracker operates according to the warning instruction.
  • the tracker executes at least one of the following operations according to the received warning instruction: activate the alarm, turn on the double flashing lights, etc.
  • This method is especially suitable for when the owner is far away from the vehicle, by starting the horn to make it sound continuously or turn on the double flashing light to make it flash continuously, etc., to attract the attention of nearby people and seek help from nearby people. , Nearby people can avoid being left in the vehicle for a long time by smashing a window or making a phone call.
  • step 301 is optional.
  • the tracker can obtain the locked state of the doors and windows in other ways;
  • step 305 is optional.
  • the tracker sends a reminder message containing the recognition result to the terminal, the user obtains According to the recognition result, it is known that there are living bodies in the vehicle.
  • other methods can be used besides establishing a video connection;
  • Steps 306 and 307 are optional, and other methods can also be used to prevent lives.
  • the body is left in the vehicle to ensure the safety of the living body.
  • the terminal user monitors the images in the vehicle by establishing a video connection, thereby further determining the specific situation of the living body in the vehicle.
  • the terminal can also be used Send warning instructions to the tracker, and the tracker performs operations according to the warning instructions to avoid life bodies being left in the vehicle.
  • the situation of the living body in the vehicle can be specifically determined, and corresponding operations can be performed according to the specific situation of the living body.
  • photo recognition is performed.
  • the tracker sends a reminder message to the terminal. After the terminal receives the reminder message, it can further confirm the life in the vehicle by taking pictures. For details of the body, see Figure 4.
  • the tracker obtains the state of the door and window of the vehicle, and the state includes an unlocked state and a locked state.
  • the detection value is greater than or equal to the threshold value
  • perform photo recognition to obtain a recognition result, and determine whether the recognition result indicates whether there is a living body in the vehicle. If the recognition result indicates that there is a living body in the vehicle, the subsequent step 204 is continued; if the recognition result indicates that there is no living body in the vehicle, the process is ended.
  • the tracker sends a reminder message to the terminal.
  • the terminal user After the terminal user determines that there is a living body in the vehicle by viewing the reminder message, he can further confirm the situation of the living body by taking a photo to confirm.
  • the terminal sends a photographing instruction to the tracker.
  • the tracker After the tracker receives the photographing instruction, it starts the camera to take a picture of the situation in the vehicle and sends the photographed picture to the terminal.
  • the terminal user can view the picture. Determine the specific situation of the living body.
  • the tracker sends the photos taken to the terminal.
  • the form of photos sent by the tracker can be set by the user.
  • the user can choose the camera to send all the photos taken to the terminal at once after the camera is taken.
  • the terminal receives all the photos sent by the tracker; the user can also choose Each time the camera takes a picture, the tracker sends a picture taken, and accordingly, the terminal receives the pictures sent by the tracker one by one.
  • the photos sent by the tracker to the terminal may also be the photos taken in 403 above.
  • the terminal sends a warning instruction, and correspondingly, the tracker receives the warning instruction.
  • the tracker operates according to the warning instruction.
  • step 401 is optional.
  • the tracker can obtain the locked state of the doors and windows in other ways; step 405 is optional.
  • the tracker sends a reminder message containing the recognition result to the terminal, the user obtains According to the recognition result, it is known that there is a living body in the vehicle.
  • steps 406 and 407 are optional, and other methods can also be used to prevent life.
  • the body is left in the vehicle to ensure the safety of the living body.
  • the tracker on the car obtains that the doors and windows are locked, and then obtains the detection value of the pressure sensor, after judging that the detection value exceeds the preset threshold, then it will start the neural network for recognition, and the recognition result Indicates that there is a living body in the vehicle, and the living body is a dog.
  • the tracker will send a reminder message to the terminal.
  • the terminal user can choose to send a photo instruction to the tracker, and the tracker will receive it accordingly.
  • start the camera take a photo of the space in the car, and send the captured photo to the terminal. The end user can check the photo to determine the specific situation of the dog in the vehicle.
  • the end user can send warning instructions to the tracker.
  • the tracker receives the warning instruction, the horn keeps beeping and the double flashing lights keep flashing. Then, after the nearby people notice, they succeed with the help of the nearby people. Rescue the dog from the car.
  • the terminal sends a photographing instruction to the tracker.
  • the tracker After the tracker receives the photographing instruction, it starts the camera to take a picture of the inside of the vehicle, obtains the picture, and sends the picture to the terminal, or sends the picture to the terminal.
  • the photos collected during photo recognition are sent to the terminal.
  • the terminal user determines the specific situation of the living body by viewing the photos, and then sends instructions according to the specific situation of the living body, and the tracker operates according to the corresponding instructions.
  • the specific situation of the living body can be determined from multiple photos from multiple angles, and the living body can be prevented from being left in the vehicle.
  • FIG. 5 is a schematic diagram of a device 50 for preventing life from being left in a vehicle according to an embodiment of the present application.
  • the device 50 is suitable for a tracker and may include:
  • the judging module 501 is configured to obtain the detection value of the seat pressure sensor when the doors and windows of the vehicle are in a locked state, and determine whether the detection value is greater than or equal to a threshold;
  • the camera module 502 is used to take a picture of the vehicle's interior environment to obtain a photo when it is determined that the detection value is greater than or equal to the threshold value;
  • the recognition module 503 is used to recognize the photo and obtain the recognition result
  • the communication module 504 is configured to send a reminder message containing the recognition result to the terminal when the recognition result indicates that there is a living body in the vehicle.
  • the identification module 503 is specifically configured to:
  • the neural network recognition model is pre-trained based on multiple photos in the training set, and each photo in the training set includes a label, and the label is used to indicate whether there is a living body in the photo in the training set.
  • the communication module 504 is further configured to receive a window opening instruction and/or a door opening instruction sent by the terminal , And operate according to window opening instructions and/or door opening instructions.
  • the communication module 504 is also used to receive a video connection instruction sent by the terminal;
  • the camera module 502 is also used to activate the camera in the vehicle to realize a video connection with the terminal to further confirm the condition of the living body in the vehicle.
  • the communication module 504 is also configured to receive a photographing instruction sent by the terminal; and send the photo to the terminal to further confirm the condition of the living body in the vehicle.
  • the functional modules of the above-mentioned device 50 can be used to implement the method described in the embodiment of FIG. 2 or FIG. 3 or FIG. 4.
  • FIG. 6 is a schematic diagram of another device 600 for preventing life from being left in a vehicle according to an embodiment of the present application.
  • the device 600 is suitable for a tracker and includes at least a processor 610, a communication interface 620, and a memory. 630.
  • the processor 610, the communication interface 620, and the memory 630 are coupled through a bus 640. among them,
  • the processor 610 is used to run the judgment module 501, the camera module 502, the identification module 503, and the communication module 504 in FIG. 5 by calling the program code in the memory 630.
  • the processor 610 may include one or more general-purpose processors.
  • the general-purpose processor may be any type of device capable of processing electronic instructions, including a central processing unit (CPU) and a microprocessor. , Microcontroller, main processor, controller and ASIC (Application Specific Integrated Circuit, application specific integrated circuit) and so on.
  • the processor 610 reads the program code stored in the memory 630, and cooperates with the communication interface 620 to execute part or all of the steps of the method executed by the device 600 for preventing life from being left in the vehicle in the foregoing embodiment of the present application.
  • the communication interface 620 may be a wired interface (for example, an Ethernet interface) for communicating with other computing nodes or devices.
  • the communication interface 620 may adopt a protocol family over TCP/IP, for example, RAAS protocol, Remote Function Call (RFC) protocol, Simple Object Access Protocol (Simple Object Access Protocol, SOAP) protocol, Simple Network Management Protocol (SNMP) protocol, Common Object Request Broker Architecture (CORBA) protocol, distributed protocol, etc.
  • RAAS Remote Function Call
  • SOAP Simple Object Access Protocol
  • SOAP Simple Object Access Protocol
  • SNMP Simple Network Management Protocol
  • CORBA Common Object Request Broker Architecture
  • the memory 630 may store program codes and program data.
  • the program code includes the code of the judgment module 501, the code of the camera module 502, the code of the identification module 503, and the code of the communication module 504.
  • the program data includes: the state of the door, the state of the window, the detection value of the pressure sensor, the threshold value and the recognition result, etc.
  • the memory 630 may include volatile memory (Volatile Memory), such as random access memory (Random Access Memory, RAM); the memory may also include non-volatile memory (Non-Volatile Memory), such as read-only memory. Memory (Read-Only Memory, ROM), Flash Memory (Flash Memory), Hard Disk Drive (HDD), or Solid-State Drive (SSD) memory may also include a combination of the foregoing types of memories.
  • the present application provides a schematic structural diagram of another device for preventing life from being left in a vehicle.
  • the device for preventing life from being left in a vehicle in this embodiment can be implemented in a cloud service cluster 900, including at least : Including at least one computing node 910 and at least one storage node 920. among them,
  • the computing node 910 includes one or more processors 911, a communication interface 912, and a memory 913, and the processor 911, the communication interface 912, and the memory 913 may be connected through a bus 914.
  • the processor 911 includes one or more general-purpose processors. By calling the program code in the memory 913, it is used to run the judgment module 501, the camera module 502, the identification module 503, and the communication module 504 in FIG.
  • a general-purpose processor can be any type of equipment that can process electronic instructions, including a central processing unit (CPU), a microprocessor, a microcontroller, a main processor, a controller, and an ASIC (Application Specific Integrated Circuit). , ASIC) and so on. It can be a dedicated processor used only for the computing node 910 or can be shared with other computing nodes 910.
  • the processor 911 reads the program code stored in the memory 913, and cooperates with the communication interface 912 to execute part or all of the steps of the method executed by the device for preventing life from being left in the vehicle in the foregoing embodiment of the present application.
  • the communication interface 912 may be a wired interface (for example, an Ethernet interface) for communicating with other computing nodes or users.
  • the communication interface 912 may adopt a protocol family over TCP/IP, for example, the RAAS protocol, the remote function call (Remote Function Call, RFC) protocol, and the simple object access protocol (Simple Object Access Protocol, SOAP) protocol, Simple Network Management Protocol (SNMP) protocol, Common Object Request Broker Architecture (CORBA) protocol, distributed protocol, etc.
  • RAAS Remote Function Call
  • RFC Remote Function Call
  • SOAP Simple Object Access Protocol
  • SNMP Simple Network Management Protocol
  • CORBA Common Object Request Broker Architecture
  • the memory 913 may include volatile memory (Volatile Memory), such as random access memory (Random Access Memory, RAM); the memory may also include non-volatile memory (Non-Volatile Memory), such as read-only memory (Read-Only Memory). Memory, ROM, Flash Memory, Hard Disk Drive (HDD), or Solid-State Drive (SSD) memory may also include a combination of the foregoing types of memories.
  • volatile memory such as random access memory (Random Access Memory, RAM
  • non-Volatile Memory such as read-only memory (Read-Only Memory).
  • Memory, ROM, Flash Memory, Hard Disk Drive (HDD), or Solid-State Drive (SSD) memory may also include a combination of the foregoing types of memories.
  • the storage node 920 includes one or more storage controllers 921 and a storage array 922. Wherein, the storage controller 921 and the storage array 922 may be connected through a bus 923.
  • the storage controller 921 includes one or more general-purpose processors, where the general-purpose processor may be any type of device capable of processing electronic instructions, including a CPU, a microprocessor, a microcontroller, a main processor, a controller, and an ASIC, etc. Wait. It can be a dedicated processor used only for a single storage node 920 or can be shared with the computing node 900 or other storage nodes 920. It can be understood that in this embodiment, each storage node includes a storage controller. In other embodiments, multiple storage nodes may also share a storage controller, which is not specifically limited here.
  • the memory array 922 may include multiple memories.
  • the memory may be a non-volatile memory, such as ROM, flash memory, HDD or SSD memory, and may also include a combination of the above types of memory.
  • the storage array may be composed of multiple HDDs or multiple SDDs, or the storage array may be composed of HDDs and SDDs.
  • multiple memories are combined in different ways with the assistance of the storage controller 921 to form a memory group, thereby providing higher storage performance than a single memory and providing data backup technology.
  • the memory array 922 may include one or more data centers. Multiple data centers can be set up at the same location, or at different locations, and there is no specific limitation here.
  • the memory array 922 may store program codes and program data.
  • the program code includes the code of the judgment module 501, the code of the camera module 502, the code of the identification module 503, and the code of the communication module 504.
  • the program data includes: the state of the door, the state of the window, the detection value of the pressure sensor, the threshold value, the recognition result, and so on.
  • the embodiment of the present application also provides a computer-readable storage medium.
  • the computer-readable storage medium stores a computer program.
  • the computer program is executed by hardware (such as a processor, etc.) to realize the prevention of life in the embodiment of the present application. Part or all of the steps of any method executed by the device left in the vehicle.
  • the embodiment of the present application also provides a computer program product.
  • the tracker executes part or all of the steps of the method for preventing life from being left in the vehicle in the embodiment of the present application. .
  • the computer program product includes one or more computer instructions.
  • the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.
  • the computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium.
  • the computer instructions may be transmitted from a website, computer, server, or data center. Transmission to another website, computer, server or data center via wired (such as coaxial cable, optical fiber, digital subscriber line) or wireless (such as infrared, wireless, microwave, etc.).
  • the computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or a data center integrated with one or more available media.
  • the usable medium may be a magnetic medium, (for example, a floppy disk, a storage disk, and a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk, SSD), etc.
  • the description of each embodiment has its own emphasis. For parts that are not described in detail in an embodiment, reference may be made to related descriptions of other embodiments.
  • the disclosed device may also be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or It can be integrated into another system, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may also be electrical, mechanical or other forms of connection.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments of the present application.
  • the functional units in the various embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.
  • the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium.
  • the technical solution of this application is essentially or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium. It includes several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in each embodiment of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disks or optical disks and other media that can store program codes. .

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Abstract

本申请实施例提供一种预防生命体被遗留在车辆内的方法及装置，该方法包括：当车辆的车门和车窗均为锁定状态时，获取座椅下压力传感器的检测值，并判断检测值是否大于或等于阈值；在判断检测值大于或等于阈值的情况下，对车辆的车内环境进行拍照，获得照片；对照片进行识别，获得识别结果；在识别结果指示车辆内有生命体存在的情况下，向终端发送包含识别结果的提醒消息。实施本申请实施例，可以预防生命体被遗留在车辆内，避免意外事件的发生。

Description

一种预防生命体被遗留在车辆内的方法及装置 技术领域
本申请涉及通信技术领域，尤其涉及一种预防生命体被遗留在车辆内的方法及装置。
背景技术
随着社会的飞速发展，人们的生活节奏越来越快。而汽车作为人们生活中较好的代步工具，给人们的生活带来了很多便利。
随着汽车的拥有量剧增，儿童被关汽车内的事件也屡屡发生。这种事件会发生，有的是因为车主的大意疏忽而导致，有的是在车主未知的情况下，意外发生的等等，但往往都由于没有办法及时通知车主或者没有办法及时处理，而造成严重的后果，虽然有的智能汽车上安装有红外检测装置，但是有的时候，车上的生命体状态不端正或者其他原因等，而造成红外检测不成功的情况，而无法通知车主。
发明内容
本申请实施例提供了一种预防生命体被遗留在车辆内的方法及装置，可以克服现有技术的缺陷，能够有效预防生命体被遗留在车辆内，提升用户使用体验。
第一方面，本申请实施例提供一种预防生命体被遗留在车辆内的方法，包括：
当车辆的车门和车窗均为锁定状态时，获取座椅下压力传感器的检测值，并判断所述检测值是否大于或等于阈值；
在判断所述检测值大于或等于所述阈值的情况下，对所述车辆的车内环境进行拍照，获得照片；
对所述照片进行识别，获得识别结果；
在所述识别结果指示所述车辆内有生命体存在的情况下，向终端发送包含所述识别结果的提醒消息。
可以看到，本申请实施例中，在车辆的车门和车窗均处于锁定状态的情况下，追踪器获取座椅下压力传感器的检测值，并将该检测值与阈值进行比较，若该检测值大于或等于阈值，说明车辆内有可能存在生命体，则再对车辆内的环境进行拍照，并对获得的照片进行识别，识别结果能够指示车辆内是否有生命体，在识别结果指示车辆内有生命体的情况下，向终端发送包含识别结果的提醒消息。所以实施本申请实施例，根据压力传感器的检测值与阈值的关系以及车辆内照片的识别结果，确定是否向终端发送提醒消息，能够有效预防生命体被遗留在车辆内，提升用户使用体验。
基于第一方面，在可能的实施方式中，所述对所述照片进行识别包括：
将所述照片输入神经网络识别模型进行识别；
其中，所述神经网络识别模型是预先基于训练集中的多个照片训练得到的， 所述训练集中的每个照片包括标签，所述标签用于指示所述训练集中的所述照片中是否存在所述生命体。
可以看到，神经网络识别模型是以包括标签的多个照片为样本预先训练得到的，其中标签用于指示照片中是否存在生命体，在将相机拍摄的照片输入神经网络识别模型中进行识别时，能够具有较准确的识别结果。
基于第一方面，在可能的实施方式中，所述在所述识别结果指示所述车辆内有生命体存在的情况下，向终端发送包含所述识别结果的提醒消息之后，所述方法还包括：
接收所述终端发送的开窗指令和/或开门指令，并根据所述开窗指令和/或开门指令进行操作。
可以看到，在识别结果指示车辆内有生命体存在时，追踪器会向终端发送提醒消息，终端在接收到该提醒消息后，用户通过查看该提醒消息发现车辆内有生命体存在，可以通过终端向追踪器发送开窗指令和/或开门指令，追踪器接收到指令，并根据开窗指令和/或开门指令进行操作，从而可以避免生命体长时间被遗留在封闭的车辆内，防止意外事件发生。
基于第一方面，在可能的实施方式中，在接收所述终端发送的开窗指令和/或开门指令之前，所述方法还包括：
接收所述终端发送的视频连接指令；
启动所述车辆内的相机，实现与所述终端的视频连接，以进一步确认所述车辆内生命体的情况。
可以看到，追踪器向终端发送提醒消息之后，追踪器还可能会接收到终端发送的视频连接指令，通过将追踪器与终端视频连接，终端用户可以看到车辆内部的情况，从而可以进一步确定车辆内生命体的情况。
基于第一方面，在可能的实施方式中，所述方法还包括：
接收所述终端发送的拍照指令；
将所述照片发送至所述终端，以进一步确认所述车辆内所述生命体的情况。
可以看到，追踪器向终端发送提醒消息之后，追踪器也可能会接收到终端发送的拍照指令，可将上述拍摄的照片发送至终端，这样终端用户可以通过查看目标照片进一步确定生命体的情况。
第二方面，本申请实施例提供了一种预防生命体被遗留在车辆内的装置，包括：
判断模块，用于当车辆的车门和车窗均为锁定状态时，获取座椅下压力传感器的检测值，并判断所述检测值是否大于或等于阈值；
相机模块，用于在判断所述检测值大于或等于所述阈值的情况下，对所述车辆的车内环境进行拍照，获得照片；
识别模块，用于对所述照片进行识别，获得识别结果；
通信模块，用于在所述识别结果指示所述车辆内有生命体存在的情况下，向终端发送包含所述识别结果的提醒消息。
在一具体实施例中，所述识别模块具体用于：
将所述照片输入神经网络识别模型进行识别；
其中，所述神经网络识别模型是预先基于训练集中的多个照片训练得到的，所述训练集中的每个照片包括标签，所述标签用于指示所述训练集中的所述照片中是否存在所述生命体。
在一具体实施例中，所述在所述识别结果指示所述车辆内有生命体存在的情况下，向终端发送包含所述识别结果的提醒消息之后，所述通信模块，还用于接收所述终端发送的开窗指令和/或开门指令，并根据所述开窗指令和/或开门指令进行操作。
在一具体实施例中，在接收所述终端发送的开窗指令和/或开门指令之前，
所述通信模块，还用于接收所述终端发送的视频连接指令；
所述相机模块，还用于启动所述车辆内的相机，实现与所述终端的视频连接，以进一步确认所述车辆内生命体的情况。
在一具体实施例中，所述通信模块，还用于接收所述终端发送的拍照指令；将所述照片发送至所述终端，以进一步确认所述车辆内所述生命体的情况。
在一种实现中，该装置可应用于车辆的追踪器。
本申请实施例提供的装置中的各个功能模块具体用于实现第一方面所描述的方法。
第三方面，本申请实施例提供一种计算设备，包括处理器、通信接口以及存储器；所述存储器用于存储指令，所述处理器用于执行所述指令，所述通信接口用于接收或者发送数据；其中，所述处理器执行所述指令时，执行如上述第一方面或者第一方面的任意具体实现方式中所描述方法。
第四方面，本申请实施例提供一种预防生命体被遗留在车辆内的系统，包括：车辆的追踪器、车门控制模块，车窗控制模块和终端。车门控制模块是车门的控制单元，能够控制车门的打开与关闭。车窗控制模块是车窗的控制单元，能够控制车窗的打开与关闭。车辆的追踪器能够获取车门和车窗的状态，在车门和车窗均处于锁定状态的情况下，获取座椅下压力传感器的检测值，并将该检测值与阈值进行比较，若该检测值大于或等于阈值，则启动车辆内的相机进行拍照，将拍照获得的照片输入识别模型中进行识别，获得识别结果，根据识别结果向终端发送提醒消息。终端用户在获得提醒消息后，可以通过终端选择发送视频连接指令或者拍照指令，以进一步确定车辆内生命体的情况，然后终端用户还可以根据车辆内生命体的情况，通过终端选择发送开窗和/或开门指令，追踪器根据开窗和/或开门指令进行操作，以预防生命体长时间被遗留在封闭的车辆内。本申请实施例提供的系统中的各个装置和功能模块具体用于实现第一方面所描述的方法。
第五方面，本申请实施例提供一种非易失性存储介质，用于存储程序指令，当该程序指令应用于车辆的追踪器时，可用于实现第一方面所描述的方法。
第六方面，本申请实施例提供一种计算机程序产品，该计算机程序产品包括程序指令，当该计算机程序产品被车辆的追踪器执行时，该车辆的追踪器执行前 述第一方面所述方法。该计算机程序产品可以为一个软件安装包，在需要使用前述第一方面的任一种可能的设计提供的方法的情况下，可以下载该计算机程序产品并在车辆的追踪器上执行该计算机程序产品，以实现第一方面所述方法。
可以看到，本申请实施例提供了一种预防生命体被遗留在车辆内的方法，该方法应用于车辆的追踪器。在车门状态和车窗状态均为锁定状态的情况下，比较座椅下压力传感器的检测值与阈值的大小，若该检测值大于或等于阈值，说明车辆内可能存在生命体，在这种情况下，启动车辆内的相机，对车辆座椅位置进行拍照，然后将拍摄获得的照片输入神经网络识别模型中进行识别，由于神经网络识别模型是预先由包括标签的多个照片训练得到的，其中标签用于指示照片中是否存在生命体，所以若识别结果指示车辆内有生命体，在这种情况下，追踪器向终端发送包含识别结果的提醒消息相应地，终端在接收到提醒消息后，可以选择通过视频画面或通过照片来进一步确定车辆内生命体的情况，再根据生命体的情况，选择发送开窗和/或开门指令，追踪器接收到相应的指令，根据相应指令进行操作，以防止生命体被遗留在车辆内。所以，实施本申请实施例，能够有效预防生命体被遗留在车辆内，减少意外事件的发生，提升用户使用体验。
附图说明
为了更清楚地说明本申请实施例技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本申请实施例提供的一种系统架构示意图；
图2为本申请实施例提供的一种预防生命体被遗留在车辆内的方法示意图；
图3为本申请实施例提供的又一种预防生命体被遗留在车辆内的方法示意图；
图4为本申请实施例提供的又一种预防生命体被遗留在车辆内的方法示意图；
图5为本申请实施例提供的一种预防生命体被遗留在车辆内的装置示意图；
图6为本申请实施例提供的又一种预防生命体被遗留在车辆内的装置示意图；
图7为本申请实施例提供的又一种预防生命体被遗留在车辆内的装置示意图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本实用新型一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
需要说明的是，在本申请实施例中使用的术语是仅仅出于描述特定实施例的目的，而非旨在限制本申请。在本申请实施例和所附权利要求书中所使用的单数形式的“一种”、“所述”和“该”也旨在包括多数形式，除非上下文清楚地表示其他含义。还应当理解，本文中使用的术语“和/或”是指并包含一个或多个相关联的列出项目的任何或所有可能组合。
需要说明的是，当在本说明书和所附权利要求书中使用时，术语“包括”以及它们的任何变形，意图在于覆盖不排他的包含。例如包含了一系列单元/器件的系统、产品或者装置没有限定于已列出的单元/器件，而是可选地还包括没有列出的单元/器件，或者还可选地包括这些产品或者装置固有的其他单元/器件。
还应当理解，术语“如果”可以依据上下文被解释为“当...时”或“一旦”或“响应于确定”或“响应于检测到”或“在…的情况下”。
还需要说明的是，本说明书和权利要求书中的术语“第一”“第二”“第三”“第四”等用于区别不同的对象，而并非用于描述特定的顺序。
参见图1，图1是本申请实施例提供的一种系统架构示意图，本系统架构涉及车辆和终端，其中车辆中设置有追踪器，车辆与终端通信连接。车辆可以发送信息或指令至终端，也可以接收终端发送的信息或指令，再根据信息或指令进行后续操作，相应地，终端可以接收车辆发送的信息或指令，也可以发送信息或指令至车辆。其中，终端可以是手机、平板电脑、手环、耳机等可实现无线通信的移动设备，甚至是具有通信功能的其他穿戴设备等。
参见图2，图2是本申请实施例提供的一种预防生命体被遗留在车辆内的方法，该方法流程包括但不限于以下步骤：
201、获取车辆的车门和车窗的状态，状态包括开锁状态和锁定状态。
用户可以根据实际情况自由设置开启或者关闭追踪器。比如，用户可以设置为：当车辆停车或者锁车后，自动启动追踪器，以预防生命体被遗留在车辆内。
追踪器可以通过车门控制模块获取车门的状态，车门控制模块是车门的控制模块，可以控制车门的打开、关闭，这里车门的锁定状态包括车辆上所有车门均处于关闭时的状态，车门的开锁状态包括车辆上有至少一个车门处于打开的状态。追踪器也可以通过车窗控制模块获取车窗的状态，车窗控制模块是车窗的控制模块，可以控制车窗的打开与关闭，这里车窗的锁定状态包括车辆上所有的车窗均关闭时的状态，车窗的开锁状态包括车辆上至少有一个车窗处于打开的状态。
其中，车门控制模块和车窗控制模块可以部署在一块集成式电子控制单元(Electronic Control Unit，ECU)上，也可以分别部署在多块独立部署的电子控制单元(Electronic Control Unit，ECU)上。
202、在车门和车窗均为锁定状态时，获取座椅下压力传感器的检测值，并判断检测值是否大于或等于阈值。若是，则继续执行后续步骤203；若否，则结束流程。
本申请实施例中，座椅下的压力传感器可以是儿童座椅下的压力传感器，也 可以是车辆内部的任意一个座椅下的压力传感器，压力传感器的检测值是压力传感器的一个输出参数，比如可以是表示人或物轻重的质量值，也可以是表示人或物轻重的重力值等，这里对压力传感器的类型和检测值类型不做具体限定。
在车门和车窗的状态均为锁定状态的情况下，追踪器首先获取座椅下压力传感器的检测值，然后将该检测值与预设定的阈值进行比较，判断该检测值是否大于或等于预设定的阈值，若经判断，该检测值小于预设定的阈值，则表明该压力传感器所在的座椅位置上一定没有生命体，则可以结束流程；若经判断，该检测值是大于或等于预设定的阈值，则表明该压力传感器所在的座椅位置上可能有生命体，则需要继续执行后续步骤203。其中，这里的生命体表示的是有生命的人或物，比如可以是老人、小孩、宠物等。实际应用中，可由用户根据实际情况进行设置。
本申请实施例中，预设定的阈值可以由用户根据实际情况进行设定，例如，若车主经常搭载宠物出门的话，而压力传感器的输出值是质量，可以将阈值设定为宠物大约的质量；若压力传感器的输出值是重力，车主可以将阈值设定为宠物大约的重力。又例如，若车主经常搭载小宝宝或者老人出门的话，压力传感器的输出值是质量，可以将阈值设定为小宝宝大约的质量或者老人大约的质量；若压力传感器的输出值是重力，车主可以将阈值设定为小宝宝大约的重力或者老人大约的重力等。
203、在判断检测值是大于或等于阈值的情况下，进行照片识别，获得识别结果，并确定识别结果指示车辆内是否有生命体存在。若识别结果指示车辆内是有生命体存在，则继续执行后续步骤204；若识别结果指示车辆内没有生命体存在，则结束流程。
在判断检测值是大于或等于阈值的情况下，说明座椅上有生命体或非生命体存在，可以进一步通过照片识别的方式来确定是否是生命体。
首先启动相机，对车辆内压力传感器所在座椅位置或者车辆内所有空间环境进行拍照，获得照片。其中，相机可以是车辆内部行车记录仪的相机(此相机需要能够拍摄到座椅位置的情况或车辆内所有空间环境的情况)，也可以是一独立相机，或者也可以相机与追踪器耦合在一起。
然后对拍照获得的照片进行识别，获得识别结果，并根据识别结果确定车辆内是否有生命体。对照片识别的方法有多种，比如，可以基于某些算法来提取照片的特征，再将提取的照片的特征与追踪器中预先存储的特征进行匹配，通过结果来识别照片中是否存在生命体。又比如，可以采用神经网络识别模型来对照片进行识别，将获得的照片输入神经网络识别模型中进行识别，获得识别结果，识别结果指示车辆内是否有生命体存在。本申请实施例中，对照片进行识别的方法不做具体的限定。
下面简述介绍一下采用神经网络识别模型对照片进行识别的方法，该方法首先需要训练神经网络识别模型，然后再用训练好的神经网络识别模型对照片进行识别。
神经网络识别模型是预先基于多个照片训练得到的，每个照片中包括标签，标签用于指示照片中是否有生命体。其中，多个照片可以是用户预先通过车辆内的相机拍摄的包含生命体的照片，并存储在追踪器中的，也可以是预先通过移动设备将包含生命体的照片拷入车辆的追踪器中的，且照片中包含的生命体至少有一个，比如这个生命体可能是小孩，也可能是老人，也可能是狗等，照片中包含每一个生命体的各种姿态。标签用于指示照片中是否有生命体，，比如，若训练样本中采用的照片是车主家庭里小孩子的照片，则标签为“生命体：小孩”，若训练样本中采用的照片是车主家庭里老人的照片，则标签为“生命体：老人”，若训练样本中采用的照片是车主家庭里宠物狗的照片，则标签为“生命体：狗”等。
将拍摄的照片输入训练好的神经网络识别模型中进行识别，获得识别结果，识别结果指示车辆内是否有生命体存在。例如，神经网络识别模型训练时，采用的训练样本包括含有小孩的照片、含有老人的照片、含有狗的照片共三个生命体的多姿态的照片，假如拍摄的照片中包含狗，将该包含狗的照片输入训练好的神经网络识别模型中进行识别，可以得到识别结果：“识别成功，生命体：狗”；假如拍摄的照片中包含一盆花，将该包含一盆花的照片输入训练好的神经网络识别模型中进行识别，可以得到识别结果：“识别失败，无生命体”；假如拍摄的照片中包含小孩的妈妈，将该包含小孩的妈妈的照片输入训练好的神经网络识别模型中进行识别，可以得到识别结果：“识别失败，无生命体”；假如拍摄的照片中包含小孩，将该包含小孩的照片输入训练好的神经网络识别模型中进行识别，可以得到识别结果：“识别成功，生命体：小孩”，等等。
可选的，在对照片进行识别前，可以先对照片进行处理，比如，运用图像分割方法将照片中的目标主体分割出来，在对分割后的照片运用图像增强方法，对照片进行增强，等等，可以达到更好的识别效果。
最后，当识别结果为识别成功的时候，即识别结果指示车辆内是有生命体存在的，则继续执行后续步骤204；当识别结果为识别失败的时候，即识别结果指示车辆内没有生命体存在，则结束流程。
204、在识别结果指示车辆内是有生命体存在的情况下，追踪器向终端发送提醒消息。
经识别后，若识别结果指示车辆内是有生命体存在的，则需要向终端发送包含识别结果的提醒消息，相应地，终端接收到提醒消息后，用户通过查看该提醒消息，得到了车辆内有生命体的消息。
205、终端发送开窗指令和/或开门指令，相应地，追踪器接收开窗指令和/或开门指令。
用户在确定了车辆内存在生命体后，用户可以通过终端向追踪器发送开窗指令，或者发送开门指令，或者开窗指令和开门指令都发送，相应地，追踪器会收到开窗指令，或者开门指令，或者开窗指令和开门指令都收到。
206、追踪器根据开窗指令和/或开门指令进行操作。
追踪器在接收到开窗指令后，将该开窗指令发送至车辆的车窗控制模块，车窗控制模块接收到该指令，控制车窗打开。这样，车辆内的空气实现与外界空气的循环流通，车辆内的生命体能够呼吸到新鲜的空气，防止生命体因为长时间被遗留在车辆内而导致意外事件。
或者，追踪器在接收到开门指令后，将该开门指令发送至车辆的车门控制模块，车门控制模块接收到该指令，控制车门打开。这样，车辆内的生命体就可以出来，不会被遗留在车辆内。
或者，追踪器在接收到开窗指令和开门指令后，分别将开窗指令发送至车辆的车窗控制模块，开门指令发送至车辆的车门控制模块，然后车窗控制模块接收到开窗指令后，控制车窗打开，车门控制模块接收到开门指令后，控制车门打开。同样，生命体不会因为被遗留在车辆内而导致意外事件。
需要说明的是，步骤201是可选的，追踪器可以通过其他方式获得车门和车窗的锁定状态；步骤205、206是可选的，追踪器在向终端发送包含识别结果的提醒消息之后，用户获得识别结果，确定了车辆内是有生命体存在，还可以通过其他方式来预防生命体被遗留在车辆内，保证生命体的安全。
为了更加清楚地理解本申请的方案，下面以一个实际应用场景为例进行描述。
在一应用场景中，车主的车辆放在楼下，车主家的小孩子在楼下玩，一会玩累了，就爬上了车，在里面休息，不料，由于玩得太累了，小孩子在车里睡着了，但是现在的车门和车窗均是关闭的，车内空气有限且不流通，这种情况下，小孩子在车里面睡觉是很危险的，如果睡得时间很长，有可能会出现生命危险。
但如果车上的追踪器获取到车门和车窗是锁定的状态，然后又获取了压力传感器的检测值，经判断该检测值超过了预设定的阈值的情况下，追踪器启动神经网络进行识别，若识别结果指示车辆内有生命体，则追踪器会向车主手机发送提醒消息，提醒消息中包括识别结果，车主在接收到该提醒消息后，可以通过发送开窗指令和开门指令至追踪器，追踪器再根据开窗指令和开门指令打开车上的窗户和门，实现车辆内部和外部空气的流通，从而保障小孩子的安全，当然，车主既然知道有小孩子在车内，还需尽快将小孩子从车内移出至车外，使其呼吸车外新鲜的空气。
可以看到，实施本申请实施例的技术方案，追踪器通过获取车门、车窗的状态和座椅下压力传感器的检测值，并判断该检测值与阈值的关系，在检测值大于或等于阈值的情况下，启动神经网络识别车辆内是否有生命体存在，经识别后若确定车辆内有生命体存在，则追踪器向终端发送提醒消息，终端接收到提醒消息后，可以向追踪器发送开窗指令和/或开门指令，以预防生命体被遗留在车辆内。所以实施本申请实施例，能够防止因生命体被遗留在车辆内而发生意外事件。
在本申请实施例中，进行照片识别，在识别结果指示车辆内是有生命体存在的情况下，追踪器向终端发送提醒消息，终端接收到提醒消息之后，还可以进一步通过视频画面确认车辆内生命体的具体情况，在确认了生命体的具体情况之后，终端还可以通过发送警示指令，来预防生命体被遗留在车辆内，参见图3。
本申请实施例中的301～304的具体内容参见图2中的201～204中的具体内容，为了说明书的简洁，在此不再赘述。
301、追踪器获取车辆的车门和车窗的状态，状态包括开锁状态和锁定状态。
302、在车门和车窗均为锁定状态时，获取座椅下压力传感器的检测值，并判断检测值是否大于或等于阈值。
303、在判断检测值是大于或等于阈值的情况下，进行照片识别，获得识别结果，并确定识别结果指示车辆内是否有生命体存在。若识别结果指示车辆内是有生命体存在，则继续执行后续步骤204；若识别结果指示车辆内没有生命体存在，则结束流程。
304、在识别结果指示车辆内是有生命体存在的情况下，追踪器向终端发送提醒消息。
305、建立视频连接。
终端用户通过查看提醒消息，确定了车辆内有生命体存在之后，可以通过视频画面的形式进一步确定生命体的情况。
终端建立与追踪器的视频连接过程如下，终端向追踪器发送视频连接的指令，相应地，追踪器接收到该视频连接指令后，启动相机，对车辆内画面进行拍摄，实现终端对车辆内画面的视频监控，终端用户通过视频画面可以进一步确定生命体的情况，比如，可以对神经网络识别结果进行进一步的确认，以及查看生命体的身体健康情况等。
306、终端发送警示指令，相应地，追踪器接收警示指令。
终端用户在确定了生命体的具体情况后，还可以向追踪器发送警示指令，以寻求附近的人的帮助。警示指令可以是启动喇叭，也可以是开启双闪灯，也可以是启动喇叭和开启闪光灯等。相应地，追踪器接收到终端发送的警示指令。
307、追踪器根据警示指令进行操作。
追踪器根据接收到的警示指令执行以下至少一种操作：启动喇器，开启双闪灯等。这种方式尤其适用于车主距离车辆较远时，通过启动喇叭，使其不断地鸣响或者开启双闪灯，使其不断地闪烁等，引起附近的人的注意，以寻求附近的人的帮助，附近的人可以通过砸窗或者拨打电话来避免生命体长时间遗留在车辆内。
需要说明的是，步骤301是可选的，追踪器可以通过其他方式获得车门和车窗的锁定状态；步骤305是可选的，追踪器在向终端发送包含识别结果的提醒消息之后，用户获得识别结果，得知车辆内有生命体存在，为了确定车辆内生命体的具体情况，除了建立视频连接，还可以采用其他方式；步骤306、307是可选的，还可以通过其他方式来预防生命体被遗留在车辆内，保证生命体的安全。
可以看到，本申请实施例中，通过建立视频连接，实现终端用户对车辆内画面的监控，从而进一步确定车辆内生命体的具体情况，在确定了生命体的具体情况后，还可以通过终端向追踪器发送警示指令，追踪器根据警示指令执行操作，来避免生命体被遗留在车辆内。实施本申请实施例，可以具体确定车辆内生命体的情况，根据生命体的具体情况可以进行相应的操作。
在本申请实施例中，进行照片识别，在识别结果指示车辆内是有生命体存在的情况下，追踪器向终端发送提醒消息，终端接收到提醒消息之后，还可以进一步通过拍照确认车辆内生命体的具体情况，参见图4。
本申请实施例中的401～404中的具体内容参见图2中201～204中的具体内容，406～407的具体内容参见图3中306～307中的具体内容，为了说明书的简洁，在此不再赘述。
401、追踪器获取车辆的车门和车窗的状态，状态包括开锁状态和锁定状态。
402、在车门和车窗均为锁定状态时，获取座椅下压力传感器的检测值，并判断检测值是否大于或等于阈值。
403、在判断检测值是大于或等于阈值的情况下，进行照片识别，获得识别结果，并确定识别结果指示车辆内是否有生命体存在。若识别结果指示车辆内是有生命体存在，则继续执行后续步骤204；若识别结果指示车辆内没有生命体存在，则结束流程。
404、在识别结果指示车辆内是有生命体存在的情况下，追踪器向终端发送提醒消息。
405、拍照确认。
终端用户通过查看提醒消息，确定了车辆内有生命体存在之后，可以通过拍照确认的形式进一步确定生命体的情况。
首先，终端向追踪器发送拍照指令，相应地，追踪器接收到拍照指令后，然后，启动相机，对车辆内的情况进行拍照，并将拍摄的照片发送至终端，终端用户通过查看照片，可以确定生命体的具体情况。其中，追踪器发送拍摄的照片至终端。追踪器发送照片的形式可由用户自己设置，用户可以选择相机在拍摄完毕后，追踪器将拍摄的所有照片一次性发送至终端，相应地，终端接收到追踪器发送的所有照片；用户也可以选择相机每拍摄一张照片，追踪器就发送一张拍摄的照片，相应地，终端也是一张一张地接收到追踪器发送的照片。
需要说明的是，追踪器向终端发送的照片还可以是前述403中拍摄的照片。
406、终端发送警示指令，相应地，追踪器接收警示指令。
407、追踪器根据警示指令进行操作。
需要说明的是，步骤401是可选的，追踪器可以通过其他方式获得车门和车窗的锁定状态；步骤405是可选的，追踪器在向终端发送包含识别结果的提醒消息之后，用户获得识别结果，得知车辆内有生命体存在，为了确定车辆内生命体的具体情况，除了通过拍照确认，还可以采用其他方式；步骤406、407是可选的，还可以通过其他方式来预防生命体被遗留在车辆内，保证生命体的安全。
为了更加清楚地理解本申请的方案，下面以一个实际应用场景为例进行描述。
在又一应用场景中，车主出门办事时，家里的宠物狗也跟着上了车，到达目的地后，车主急着办事，就匆忙忙地下了车，而把宠物狗留在了车上。车主办完事情后，又去旁边的商场逛街了，结果就忘记了宠物狗还在车上，这种情况下，宠物狗长时间呆在封闭的车里面是有生命危险的。
但如果车上的追踪器获取到车门和车窗是锁定的状态，又获取了压力传感器的检测值，经判断该检测值超过了预设定的阈值，然后会启动神经网络进行识别，识别结果指示车辆内有生命体，生命体为狗，这种情况下，追踪器会向终端发送提醒消息，终端用户通过查看该提醒消息后，可以选择向追踪器发送拍照指令，相应地，追踪器接收到拍照指令，启动相机，对车内的空间进行拍照，并将拍摄的照片发送至终端，终端用户通过查看照片，确定车辆内狗的具体情况，但是由于车主在商场，距离车辆较远，为了防止意外发生，终端用户可以通过发送警示指令至追踪器，追踪器接收到警示指令后，喇叭不断鸣响、双闪灯不断闪烁，然后附近的人注意到后，经过附近的人的帮助，成功将狗从车内救出。
可以看到，实施本申请实施例的技术方案，终端通过向追踪器发送拍照指令，追踪器接收到拍照指令后，启动相机对车辆内画面进行拍照，获得照片，将照片发送至终端，或者将进行照片识别时采集的照片发送至终端，终端用户通过查看照片，确定生命体的具体情况，再根据生命体的具体情况，来发送指令，追踪器根据相应指令进行操作。实施本申请实施例方案，可以通过多张照片多角度地确定生命体的具体情况，防止生命体被遗留在车辆内。
参见图5，图5是本申请实施例提供的一种预防生命体被遗留在车辆内的装置50示意图，该装置50适用于追踪器，可以包括：
判断模块501，用于当车辆的车门和车窗均为锁定状态时，获取座椅下压力传感器的检测值，并判断检测值是否大于或等于阈值；
相机模块502，用于在判断检测值大于或等于阈值的情况下，对车辆的车内环境进行拍照，获得照片；
识别模块503，用于对照片进行识别，获得识别结果；
通信模块504，用于在识别结果指示车辆内有生命体存在的情况下，向终端发送包含识别结果的提醒消息。
在一具体实施例中，识别模块503具体用于：
将照片输入神经网络识别模型进行识别；
其中，神经网络识别模型是预先基于训练集中的多个照片训练得到的，训练集中的每个照片包括标签，标签用于指示训练集中的照片中是否存在生命体。
在一具体实施例中，在识别结果指示车辆内有生命体存在的情况下，向终端发送包含识别结果的提醒消息之后，通信模块504还用于接收终端发送的开窗指令和/或开门指令，并根据开窗指令和/或开门指令进行操作。
在一具体实施例中，在接收终端发送的开窗指令和/或开门指令之前，
通信模块504，还用于接收终端发送的视频连接指令；
相机模块502，还用于启动车辆内的相机，实现与终端的视频连接，以进一步确认车辆内生命体的情况。
在一具体实施例中，通信模块504还用于接收终端发送的拍照指令；将照片发送至终端，以进一步确认车辆内生命体的情况。
上述装置50的各功能模块可用于实现图2或图3或图4实施例所描述的方法，具体内容可参考图2、图3、图4实施例的相关内容中的描述，为了说明书的简洁，这里不再赘述。
参见图6，图6是本申请实施例提供的另一种预防生命体被遗留在车辆内的装置600的示意图，该装置600适用于追踪器，至少包括：处理器610、通信接口620和存储器630，处理器610、通信接口620和存储器630通过总线640进行耦合。其中，
处理器610通过调用存储器630中的程序代码，用于运行图5中的判断模块501、相机模块502、识别模块503、通信模块504。在实际应用中，处理器610可以包括一个或者多个通用处理器，其中，通用处理器可以是能够处理电子指令的任何类型的设备，包括中央处理器(Central Processing Unit，CPU)、微处理器、微控制器、主处理器、控制器以及ASIC(Application Specific Integrated Circuit，专用集成电路)等等。处理器610读取存储器630中存储的程序代码，与通信接口620配合执行本申请上述实施例中预防生命体被遗留在车辆内的装置600执行的方法的部分或者全部步骤。
通信接口620可以为有线接口(例如以太网接口)，用于与其他计算节点或装置进行通信。当通信接口620为有线接口时，通信接口620可以采用TCP/IP之上的协议族，例如，RAAS协议、远程函数调用(Remote Function Call，RFC)协议、简单对象访问协议(Simple Object Access Protocol，SOAP)协议、简单网络管理协议(Simple Network Management Protocol，SNMP)协议、公共对象请求代理体系结构(Common Object Request Broker Architecture，CORBA)协议以及分布式协议等等。
存储器630可以存储有程序代码以及程序数据。其中，程序代码包括判断模块501的代码、相机模块502的代码、识别模块503的代码、通信模块504的代码。程序数据包括：车门状态、车窗状态、压力传感器的检测值、阈值和识别结果等等。在实际应用中，存储器630可以包括易失性存储器(Volatile Memory)，例如随机存取存储器(Random Access Memory，RAM)；存储器也可以包括非易失性存储器(Non-Volatile Memory)，例如只读存储器(Read-Only Memory，ROM)、快闪存储器(Flash Memory)、硬盘(Hard Disk Drive，HDD)或固态硬盘(Solid-State Drive，SSD)存储器还可以包括上述种类的存储器的组合。
参见图7，本申请提供了另一种预防生命体被遗留在车辆内的装置的结构示意图，本实施方式的预防生命体被遗留在车辆内的装置可以在云服务集群900中实现，至少包括：包括至少一个计算节点910以及至少一个存储节点920。其中，
计算节点910包括一个或多个处理器911、通信接口912和存储器913，处理器911、通信接口912和存储器913之间可以通过总线914连接。
处理器911包括一个或者多个通用处理器，通过调用存储器913中的程序代 码，用于运行图5中的判断模块501、相机模块502、识别模块503、通信模块504。其中，通用处理器可以是能够处理电子指令的任何类型的设备，包括中央处理器(Central Processing Unit，CPU)、微处理器、微控制器、主处理器、控制器以及ASIC(Application Specific Integrated Circuit，专用集成电路)等等。它能够是仅用于计算节点910的专用处理器或者能够与其它计算节点910共享。处理器911读取存储器913中存储的程序代码，与通信接口912配合执行本申请上述实施例中预防生命体被遗留在车辆内的装置执行的方法的部分或者全部步骤。
通信接口912可以为有线接口(例如以太网接口)，用于与其他计算节点或用户进行通信。当通信接口912为有线接口时，通信接口912可以采用TCP/IP之上的协议族，例如，RAAS协议、远程函数调用(Remote Function Call，RFC)协议、简单对象访问协议(Simple Object Access Protocol，SOAP)协议、简单网络管理协议(Simple Network Management Protocol，SNMP)协议、公共对象请求代理体系结构(Common Object Request Broker Architecture，CORBA)协议以及分布式协议等等。
存储器913可以包括易失性存储器(Volatile Memory)，例如随机存取存储器(Random Access Memory，RAM)；存储器也可以包括非易失性存储器(Non-Volatile Memory)，例如只读存储器(Read-Only Memory，ROM)、快闪存储器(Flash Memory)、硬盘(Hard Disk Drive，HDD)或固态硬盘(Solid-State Drive，SSD)存储器还可以包括上述种类的存储器的组合。
存储节点920包括一个或多个存储控制器921、存储阵列922。其中，存储控制器921和存储阵列922之间可以通过总线923连接。
存储控制器921包括一个或者多个通用处理器，其中，通用处理器可以是能够处理电子指令的任何类型的设备，包括CPU、微处理器、微控制器、主处理器、控制器以及ASIC等等。它能够是仅用于单个存储节点920的专用处理器或者能够与计算节点900或者其它存储节点920共享。可以理解，在本实施例中，每个存储节点包括一个存储控制器，在其他的实施例中，也可以多个存储节点共享一个存储控制器，此处不作具体限定。
存储器阵列922可以包括多个存储器。存储器可以是非易失性存储器，例如ROM、快闪存储器、HDD或SSD存储器还可以包括上述种类的存储器的组合。例如，存储阵列可以是由多个HDD或者多个SDD组成，或者，存储阵列可以是由HDD以及SDD组成。其中，多个存储器在存储控制器921的协助下按不同的方式组合起来形成存储器组，从而提供比单个存储器更高的存储性能和提供数据备份技术。可选地，存储器阵列922可以包括一个或者多个数据中心。多个数据中心可以设置在同一个地点，或者，分别在不同的地点，此处不作具体限定。存储器阵列922可以存储有程序代码以及程序数据。其中，程序代码包括判断模块501的代码、相机模块502的代码、识别模块503的代码、通信模块504的代码。程序数据包括：车门状态、车窗状态、压力传感器的检测值、阈值和识别结果等等。
本申请实施例还提供一种计算机可读存储介质，该计算机可读存储介质中存储有计算机程序，所述计算机程序被硬件(例如处理器等)执行，以实现本申请实施例中预防生命体被遗留在车辆内的装置执行的任意一种方法的部分或者全部步骤。
本申请实施例还提供一种计算机程序产品，当所述计算机程序产品被计算机读取并执行时，使得追踪器执行本申请实施例中预防生命体被遗留在车辆内的方法的部分或全部步骤。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件实现时，可以全部或部分地以计算机程序产品的形式实现。所述计算机程序产品包括一个或多个计算机指令。在计算机上加载和执行所述计算机程序指令时，全部或部分地产生按照本申请实施例所述的流程或功能。所述计算机可以是通用计算机、专用计算机、计算机网络、或者其他可编程装置。所述计算机指令可以存储在计算机可读存储介质中，或者从一个计算机可读存储介质向另一个计算机可读存储介质传输，例如，所述计算机指令可以从一个网站站点、计算机、服务器或数据中心通过有线(例如同轴电缆、光纤、数字用户线)或无线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。所述计算机可读存储介质可以是计算机能够存取的任何可用介质或者是包含一个或多个可用介质集成的服务器、数据中心等数据存储设备。所述可用介质可以是磁性介质，(例如，软盘、存储盘、磁带)、光介质(例如，DVD)、或者半导体介质(例如固态存储盘Solid State Disk，SSD))等。在所述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可以参见其他实施例的相关描述。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置，也可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口、装置或单元的间接耦合或通信连接，也可以是电的，机械的或其它的形式连接。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本申请实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以是两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分，或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以权利要求的保护范围为准。

Claims (10)

  1. 一种预防生命体被遗留在车辆内的方法，其特征在于，所述方法应用于车辆的追踪器，包括：
    当车辆的车门和车窗均为锁定状态时，获取座椅下压力传感器的检测值，并判断所述检测值是否大于或等于阈值；
    在判断所述检测值大于或等于所述阈值的情况下，对所述车辆的车内环境进行拍照，获得照片；
    对所述照片进行识别，获得识别结果；
    在所述识别结果指示所述车辆内有生命体存在的情况下，向终端发送包含所述识别结果的提醒消息。
  2. 根据权利要求1所述的方法，其特征在于，所述对所述照片进行识别包括：
    将所述照片输入神经网络识别模型进行识别；
    其中，所述神经网络识别模型是预先基于训练集中的多个照片训练得到的，所述训练集中的每个照片包括标签，所述标签用于指示所述训练集中的所述照片中是否存在所述生命体。
  3. 根据权利要求1所述的方法，其特征在于，所述在所述识别结果指示所述车辆内有生命体存在的情况下，向终端发送包含所述识别结果的提醒消息之后，所述方法还包括：
    接收所述终端发送的开窗指令和/或开门指令，并根据所述开窗指令和/或开门指令进行操作。
  4. 根据权利要求3所述的方法，其特征在于，在接收所述终端发送的开窗指令和/或开门指令之前，所述方法还包括：
    接收所述终端发送的视频连接指令；
    启动所述车辆内的相机，实现与所述终端的视频连接，以进一步确认所述车辆内所述生命体的情况。
  5. 根据权利要求4所述的方法，其特征在于，所述方法还包括：
    接收所述终端发送的拍照指令；
    将所述照片发送至所述终端，以进一步确认所述车辆内所述生命体的情况。
  6. 一种预防生命体被遗留在车辆内的装置，其特征在于，所述装置应用于车辆的追踪器，包括：
    判断模块，用于当车辆的车门和车窗均为锁定状态时，获取座椅下压力传感器的检测值，并判断所述检测值是否大于或等于阈值；
    相机模块，用于在判断所述检测值大于或等于所述阈值的情况下，对所述车辆的车内环境进行拍照，获得照片；
    识别模块，用于对所述照片进行识别，获得识别结果；
    通信模块，用于在所述识别结果指示所述车辆内有生命体存在的情况下，向终端发送包含所述识别结果的提醒消息。
  7. 根据权利要求6所述的装置，其特征在于，所述识别模块具体用于：
    将所述照片输入神经网络识别模型进行识别；
    其中，所述神经网络识别模型是预先基于训练集中的多个照片训练得到的，所述训练集中的每个照片包括标签，所述标签用于指示所述训练集中的所述照片中是否存在所述生命体。
  8. 根据权利要求6所述的装置，其特征在于，所述在所述识别结果指示所述车辆内有生命体存在的情况下，向终端发送包含所述识别结果的提醒消息之后，
    所述通信模块，还用于接收所述终端发送的开窗指令和/或开门指令，并根据所述开窗指令和/或开门指令进行操作。
  9. 根据权利要求8所述的装置，其特征在于，在接收所述终端发送的开窗指令和/或开门指令之前，
    所述通信模块，还用于接收所述终端发送的视频连接指令；
    所述相机模块，还用于启动所述车辆内的相机，实现与所述终端的视频连接，以进一步确认所述车辆内生命体的情况。
  10. 根据权利要求9所述的装置，其特征在于，
    所述通信模块，还用于接收所述终端发送的拍照指令；将所述照片发送至所述终端，以进一步确认所述车辆内所述生命体的情况。
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113960693A (zh) * 2021-10-29 2022-01-21 上海洛轲智能科技有限公司 活动物体检测方法、系统、电子设备及介质
CN114407822A (zh) * 2021-12-09 2022-04-29 北京罗克维尔斯科技有限公司 信息推送方法、装置、电子设备、存储介质和车辆
CN114987379A (zh) * 2022-05-24 2022-09-02 阿维塔科技(重庆)有限公司 车辆的控制方法、车辆以及计算机存储介质
CN115045583A (zh) * 2021-09-28 2022-09-13 长城汽车股份有限公司 一种车辆的车窗控制方法、装置车辆及存储介质
CN115230635A (zh) * 2022-08-25 2022-10-25 阿维塔科技(重庆)有限公司 远程控制车门解锁方法及装置
CN115848306A (zh) * 2022-12-23 2023-03-28 阿维塔科技(重庆)有限公司 一种车辆遗留人员的检测方法、检测装置与车辆

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115871556A (zh) * 2022-11-29 2023-03-31 重庆长安汽车股份有限公司 车辆的智能报警方法及装置

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7170401B1 (en) * 2004-07-13 2007-01-30 Cole Charles J System to detect the presence of an unattended child in a vehicle
CN105128734A (zh) * 2015-08-26 2015-12-09 江苏科技大学 防止儿童遗忘车内的警示方法、系统及其应用
CN106515645A (zh) * 2016-12-27 2017-03-22 埃泰克汽车电子(芜湖)有限公司 一种儿童遗忘在车内的保护系统及其方法
CN108711254A (zh) * 2018-03-22 2018-10-26 河南科技大学 一种用于防止车内生命遗忘被锁的提醒防护装置及方法
CN110310457A (zh) * 2019-07-12 2019-10-08 深圳恩生科技有限公司 一种用于校车的生命检测呼救系统

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105427529B (zh) * 2015-12-04 2018-06-29 北京奇虎科技有限公司 一种车内环境监控的方法及终端
CN205283734U (zh) * 2016-01-06 2016-06-01 三峡大学 一种车内生命体监控系统
CN109835295A (zh) * 2017-11-29 2019-06-04 中移(苏州)软件技术有限公司 一种车内遗忘生命体检测方法、装置和介质
CN109532741B (zh) * 2018-11-23 2021-03-23 中科传启（苏州）科技有限公司 车内生命体提醒方法、装置及行车记录仪

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7170401B1 (en) * 2004-07-13 2007-01-30 Cole Charles J System to detect the presence of an unattended child in a vehicle
CN105128734A (zh) * 2015-08-26 2015-12-09 江苏科技大学 防止儿童遗忘车内的警示方法、系统及其应用
CN106515645A (zh) * 2016-12-27 2017-03-22 埃泰克汽车电子(芜湖)有限公司 一种儿童遗忘在车内的保护系统及其方法
CN108711254A (zh) * 2018-03-22 2018-10-26 河南科技大学 一种用于防止车内生命遗忘被锁的提醒防护装置及方法
CN110310457A (zh) * 2019-07-12 2019-10-08 深圳恩生科技有限公司 一种用于校车的生命检测呼救系统

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115045583A (zh) * 2021-09-28 2022-09-13 长城汽车股份有限公司 一种车辆的车窗控制方法、装置车辆及存储介质
CN113960693A (zh) * 2021-10-29 2022-01-21 上海洛轲智能科技有限公司 活动物体检测方法、系统、电子设备及介质
CN113960693B (zh) * 2021-10-29 2023-12-15 上海洛轲智能科技有限公司 活动物体检测方法、系统、电子设备及介质
CN114407822A (zh) * 2021-12-09 2022-04-29 北京罗克维尔斯科技有限公司 信息推送方法、装置、电子设备、存储介质和车辆
CN114987379A (zh) * 2022-05-24 2022-09-02 阿维塔科技(重庆)有限公司 车辆的控制方法、车辆以及计算机存储介质
CN114987379B (zh) * 2022-05-24 2023-11-07 阿维塔科技(重庆)有限公司 车辆的控制方法、车辆以及计算机存储介质
CN115230635A (zh) * 2022-08-25 2022-10-25 阿维塔科技(重庆)有限公司 远程控制车门解锁方法及装置
CN115848306A (zh) * 2022-12-23 2023-03-28 阿维塔科技(重庆)有限公司 一种车辆遗留人员的检测方法、检测装置与车辆
CN115848306B (zh) * 2022-12-23 2024-05-17 阿维塔科技(重庆)有限公司 一种车辆遗留人员的检测方法、检测装置与车辆

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