CN112614308A - Life detecting system in vehicle - Google Patents
Life detecting system in vehicle Download PDFInfo
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- CN112614308A CN112614308A CN202011548445.5A CN202011548445A CN112614308A CN 112614308 A CN112614308 A CN 112614308A CN 202011548445 A CN202011548445 A CN 202011548445A CN 112614308 A CN112614308 A CN 112614308A
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/0202—Child monitoring systems using a transmitter-receiver system carried by the parent and the child
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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
- B60R21/01512—Passenger detection systems
- B60R21/0153—Passenger detection systems using field detection presence sensors
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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
- B60R21/02—Occupant safety arrangements or fittings, e.g. crash pads
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
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- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
- H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
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Abstract
The invention discloses a life detection system in a vehicle, which comprises a vehicle, a server and user mobile equipment, wherein the vehicle comprises a vehicle-mounted data collection system, the vehicle-mounted data collection system comprises an OEM acceleration sensor, an OEM battery, a battery management system BMS, a CAN transceiver module, a vehicle-mounted mobile network module and vehicle-side application software installed on an IVI, the server is a cloud server, the cloud server comprises a data receiving unit, a data preprocessing unit, a neural network and a data sending unit, and the user mobile equipment comprises mobile equipment based on an android/IOS operating system. The system utilizes the vehicle-mounted entertainment information system IVI of the vehicle original factory, the vehicle original factory mobile network module, the cloud computing server and the user mobile terminal to judge and identify data returned by the vehicle original factory acceleration sensor in real time to carry out in-vehicle infant, child, adult and pet detection, and can trigger an alarm mechanism as long as the whole system detects that a life body exists in the vehicle.
Description
Technical Field
The invention relates to the technical field of life detection, in particular to a life detection system in a vehicle.
Background
In recent years, the number of cases of injury or death of pets has not been reduced due to passengers who suffer from high temperature and oxygen deficiency in an enclosed environment in a car, and children who remain in the car have become a major victim.
Currently, there are some patents related to motion detection on the market, such as: vehicle Occupant Safety System (refer to US 2017/088044a1), Sound, Temperature and Motion Alarm System (refer to US9,919,646B 1) and Monitor and Method for Monitoring a Baby in a Vehicle (refer to US 10,467,899B1) for Sound, Temperature and Motion of Occupants and Pets in the Vehicle; the above 2 inventions are all multi-sensor alarm systems based on temperature sensing, and their motion detection is accomplished by a whole set of sensors purchased in aftermarket, including infrared, microwave, ultrasonic, camera, etc. The last invention mainly relies on a vehicle-mounted microphone to collect sound signals and a set of waveform signal processing technology, so that when the system finds that any sound of children exists in the vehicle, the system gives an alarm.
The implementation of the technology in the existing patents requires the purchase of multiple high precision sensors or even external power sources by the aftermarket, such as: US 2017/088044A1 to Hensley, US9,919,646B1 to Arnold and US 10,467,899B1 to Elyakim. There are also some solutions on the market based on mounting a pressure sensor under the vehicle seat. The disadvantages of these solutions are: once the sensors are installed, they cannot move, and one sensor can only monitor the pressure on one seat in the vehicle; moreover, such devices are not easily detachable, besides the sensors need to be precisely installed and calibrated, which also increases the use and production costs for the user, and therefore such solutions are extremely impractical both for the manufacturer and for the user, and moreover there is a certain risk of installation of these complex devices, for example: the damage of the sensor and the vehicle in the installation process can cause the performance reduction and even the failure of the system, the efficiency of the simple alarm mechanism based on the vehicle whistle of the system is extremely low, if the parking position of the vehicle is remote (the surrounding people are rare), the alarms can be regarded as invalid alarms, the hardware-based system can not update and update the product, and once any function/performance problem of the product occurs, the problem can be solved only by the offline recall of the low efficiency.
Disclosure of Invention
Based on the technical problems in the background art, the invention provides an in-vehicle life detection system.
The life detection system in the vehicle comprises the vehicle, a server and user mobile equipment, wherein the vehicle comprises a vehicle-mounted data collection system, the vehicle-mounted data collection system comprises an OEM acceleration sensor, an OEM battery, a battery management system BMS, a CAN transceiver module, a vehicle-mounted mobile network module and vehicle-side application software installed on an IVI, the server is a cloud server, the cloud server comprises a data receiving unit, a data preprocessing unit, a neural network and a data sending unit, and the user mobile equipment comprises mobile equipment based on an android/IOS operating system.
Preferably, the OEM acceleration sensor receives a real-time transverse and longitudinal acceleration signal, a power supply is from an OEM battery, the CAN transceiver module or the T-Box obtains acceleration data from the acceleration sensor and then sends the acceleration data to the cloud end through the vehicle-mounted mobile network module or the T-Box, and the whole process is controlled by vehicle-end application software installed on the IVI.
Preferably, the cloud server receives the real-time acceleration data, performs data preprocessing, performs predictive computation, and transmits data by using a web socket protocol.
Preferably, the cloud server performs short-time fourier computation on the received data, converts time domain data into frequency domain data to facilitate computation of a neural network, performs Z-standardized computation on the frequency domain data by an algorithm in the cloud server to ensure that all input data have similar statistical distribution, obtains a result tensor which is used as input of a pre-trained deep separable convolutional neural network, performs prediction and judgment on the data within 3 seconds by the neural network during prediction and sends a neural network computation result to the user mobile device through a Web Socket protocol after judgment is finished, a pre-defined alarm logic can be set if any abnormality exists, and when the server finishes data judgment within 3 seconds, the vehicle end performs data collection for the next 3 seconds.
Preferably, the mobile device receives real-time data sent by the data sending unit and activates an alarm mechanism when there is a dangerous case, and the mobile device of the user utilizes the map service to ask for help to other users or nearby users.
Preferably, the system further comprises a vehicle-mounted air conditioning system and a vehicle window, the vehicle-mounted air conditioning system and the vehicle window can be automatically/manually controlled by a user at a mobile phone end, the user mobile device sends a control instruction to the cloud server, and the cloud server sends the control instruction to vehicle end application software installed on the IVI.
Preferably, the OEM acceleration sensor collects real-time acceleration data, any in-vehicle artificial mechanical vibration can cause the acceleration data to generate certain changes, the real-time data received by the vehicle-side application software installed on the IVI can be transmitted to the cloud server in real time to perform neural network prediction calculation, the prediction result of the cloud server is transmitted to the user mobile terminal, and in order to eliminate the vehicle mechanical vibration caused by external interference (such as strong wind and the like) which may occur during the neural network prediction calculation, the interference data can also be used as training data in the neural network training stage for network training.
Preferably, the vehicle-mounted data collection system is deployed on a vehicle end, the cloud server is deployed with a motion detection mechanism, the APP on the user mobile device is used for receiving the motion detection mechanism, and communication among the vehicle-mounted data collection system, the vehicle end, the cloud server, the motion detection mechanism and the user mobile device is based on a Web Socket protocol.
Preferably, the onboard data collection system is downloaded by a user in the form of software to an onboard application software installed on the IVI.
Preferably, the operation steps of the in-vehicle life detection system are as follows:
s1, judging whether the vehicle stops, if not, closing life detection in the vehicle, if so, judging whether the user position is the same as the vehicle stopping position, and if so, closing life detection in the vehicle;
s2, judging whether the parking time is less than 5 hours when the user position is not the same as the parking position of the vehicle, otherwise, closing life detection in the vehicle; if yes, the life detection in the vehicle is started;
s3, after the in-vehicle life detection is started, whether a life body is found is judged, if yes, the vehicle window is lowered, the air conditioner is started, then warning information is sent to a user, and the user is alert, and then rescue is organized;
s3, if the user is not alert, sending warning information to other mobile equipment matched with the accident vehicle, judging whether the user is alert, and if the user is alert, organizing rescue;
s4, if the user is not alert, judging whether other users are nearby, if yes, sending warning information to other nearby users, if the user is alert, organizing the rescue, if no other users and users are nearby, notifying the police, and the police organizing the rescue.
In the in-vehicle life detection system, a vehicle original factory vehicle-mounted entertainment information system IVI, a vehicle original factory mobile network module (T-BOX of some vehicles, namely, in Telematics Box), a cloud computing server and a user mobile terminal are utilized to judge and identify data returned by an acceleration sensor of the vehicle original factory in real time so as to detect babies, children, adults and pets in the vehicle, wherein the acceleration sensor is used as an action detector, and an alarm mechanism can be triggered as long as the whole system detects that a life body exists in the vehicle.
Drawings
FIG. 1 is a schematic diagram of a hardware architecture of an in-vehicle life detection system according to the present invention;
FIG. 2 is a diagram of the software architecture of the life detection system in a vehicle according to the present invention;
fig. 3 is an overall architecture diagram of a system under vehicle-mounted data collection of the in-vehicle life detection system according to the present invention;
fig. 4 is a flow chart of data of the in-vehicle life detection system in the cloud server according to the present invention;
fig. 5 is a data preprocessing diagram of the in-vehicle life detection system according to the present invention;
FIG. 6 is a diagram of a neural network architecture of the in-vehicle life detection system according to the present invention;
FIG. 7 is a logic diagram of the control and alarm of the in-vehicle life detection system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Referring to fig. 1-7, the in-vehicle life detection system comprises a vehicle, a server and a user mobile device, wherein the vehicle comprises an on-board data collection system, the on-board data collection system comprises an OEM acceleration sensor, an OEM battery and a battery management system BMS, a CAN transceiver module, an on-board mobile network module, vehicle-side application software installed on an IVI, the server is a cloud server, the cloud server comprises a data receiving unit, a data preprocessing unit, a neural network and a data sending unit, and the user mobile device comprises a mobile device based on an android/IOS operating system.
In the invention, an OEM acceleration sensor receives a real-time transverse and longitudinal acceleration signal, a power supply is from an OEM battery, a CAN transceiver module or a T-Box obtains acceleration data from the acceleration sensor and then sends the acceleration data to a cloud end through a vehicle-mounted mobile network module or the T-Box, and the whole process is controlled by vehicle-end application software installed on an IVI.
In the invention, the cloud server receives real-time acceleration data, performs data preprocessing, performs predictive calculation and transmits the data by using a web socket protocol.
In the invention, the cloud server firstly performs short-time Fourier calculation on received data, converts time domain data into frequency domain data to facilitate calculation of a neural network, an algorithm in the cloud server performs Z-standardized calculation on the frequency domain data to ensure that all input data have similar statistical distribution, an obtained result tensor is used as the input of a pre-trained deep separable convolutional neural network, the neural network performs prediction and judgment on the data within 3 seconds during prediction calculation, after the judgment is finished, the cloud server transmits the calculation result of the neural network to user mobile equipment through a Web Socket protocol, if any abnormality exists, a pre-defined alarm logic can be set, and when the server finishes the data judgment within 3 seconds, the vehicle end performs data collection for the next 3 seconds.
In the invention, the mobile equipment receives the real-time data sent by the data sending unit and activates the alarm mechanism when there is a dangerous case, and the mobile equipment of the user utilizes the map service to ask for help to other users or nearby users.
In the invention, the system also comprises a vehicle-mounted air conditioning system and a vehicle window, wherein the vehicle-mounted air conditioning system and the vehicle window can be automatically/manually controlled by a user at a mobile phone end, the mobile device of the user sends a control instruction to the cloud server, and the cloud server sends the control instruction to vehicle-end application software installed on the IVI.
In the invention, an OEM acceleration sensor collects real-time acceleration data, any man-made mechanical vibration in a vehicle can cause the acceleration data to generate certain change, the real-time data received by vehicle-end application software installed on an IVI can be transmitted to a cloud server in real time to carry out neural network prediction calculation, the prediction result of the cloud server is transmitted to a user mobile end, and in order to eliminate the vehicle mechanical vibration caused by external interference (such as strong wind and the like) which possibly occurs in the neural network prediction calculation, the interference data can also be used as training data in the neural network training stage for network training.
In the invention, the vehicle-mounted data collection system is deployed on a vehicle end, the cloud server is deployed with a motion detection mechanism, the APP on the user mobile equipment is used for receiving the motion detection structure, and the communication among the vehicle-mounted data collection system, the vehicle end, the cloud server, the motion detection mechanism and the user mobile equipment is based on a Web Socket protocol.
In the invention, the vehicle-mounted data collection system is downloaded to vehicle-end application software installed on the IVI by a user in a software mode.
In the invention, the operation steps of the life detection system in the vehicle are as follows:
s1, judging whether the vehicle stops, if not, closing life detection in the vehicle, if so, judging whether the user position is the same as the vehicle stopping position, and if so, closing life detection in the vehicle;
s2, judging whether the parking time is less than 5 hours when the user position is not the same as the parking position of the vehicle, otherwise, closing life detection in the vehicle; if yes, the life detection in the vehicle is started;
s3, after the in-vehicle life detection is started, whether a life body is found is judged, if yes, the vehicle window is lowered, the air conditioner is started, then warning information is sent to a user, and the user is alert, and then rescue is organized;
s3, if the user is not alert, sending warning information to other mobile equipment matched with the accident vehicle, judging whether the user is alert, and if the user is alert, organizing rescue;
s4, if the user is not alert, judging whether other users are nearby, if yes, sending warning information to other nearby users, if the user is alert, organizing the rescue, if no other users and users are nearby, notifying the police, and the police organizing the rescue.
The invention comprises the following steps: when the system is used, whether the vehicle stops or not is judged, if not, life detection in the vehicle is closed, if yes, whether the position of a user is the same as the position of the vehicle when the vehicle stops or not is judged, and if not, life detection in the vehicle is closed; if the user position is not the same as the vehicle parking position, judging whether the parking time is less than 5 hours, and if not, closing life detection in the vehicle; if yes, the life detection in the vehicle is started; after the in-vehicle life detection is started, whether a life body is found is judged, if yes, a vehicle window is lowered, an air conditioner is started, then warning information is sent to a user, and the user is alert, then rescue is organized; if the user is not alert, warning information is sent to other mobile equipment matched with the accident vehicle, whether the user is alert or not is judged, and if the user is alert, rescue is organized; if the user is not alert, judging whether other users exist nearby, if so, sending warning information to other nearby users, if the user is alert, organizing the rescue, if not, notifying the police, and otherwise, organizing the rescue.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (10)
1. The in-vehicle life detection system is characterized in that the system comprises a vehicle, a server and user mobile equipment, the vehicle comprises an on-vehicle data collection system, the on-vehicle data collection system comprises an OEM acceleration sensor, an OEM battery, a battery management system BMS, a CAN transceiver module, an on-vehicle mobile network module and vehicle-side application software installed on an IVI, the server is a cloud server, the cloud server comprises a data receiving unit, a data preprocessing unit, a neural network and a data sending unit, and the user mobile equipment comprises mobile equipment based on an android/IOS operating system.
2. The in-vehicle life detection system of claim 1, wherein the OEM acceleration sensor receives real-time lateral longitudinal acceleration signals, power is supplied from an OEM battery, and after the acceleration data is obtained from the acceleration sensor by the CAN transceiver module or the T-Box, the acceleration data is sent to the cloud end by the in-vehicle mobile network module or the T-Box, and the whole process is controlled by the in-vehicle application software installed on the IVI.
3. The in-vehicle life detection system of claim 1, wherein the cloud server receives real-time acceleration data, performs pre-processing on the data, performs predictive computation, and transmits the data using a web socket protocol.
4. The in-vehicle life detection system according to claim 3, wherein the cloud server performs short-time Fourier computation on the received data, converts time domain data into frequency domain data to facilitate computation of the neural network, an algorithm in the cloud server performs Z-standardized computation on the frequency domain data to ensure that all input data have similar statistical distribution, an obtained result tensor is used as an input of a pre-trained deep separable convolutional neural network, the neural network performs prediction and judgment on the data within 3 seconds during prediction computation, after judgment, the cloud server transmits a neural network computation result to the user mobile device through a Web Socket protocol, if any abnormality exists, predefined alarm logic can be started, and when the server completes data judgment within 3 seconds, the vehicle end will perform the next 3 seconds of data collection.
5. The in-car life detection system of claim 1, wherein the mobile device receives real-time data from the data sending unit and activates an alarm mechanism in case of a dangerous situation, and the mobile device of the user utilizes a map service to ask for help from other users or nearby users.
6. The in-vehicle life detection system according to claim 1, wherein the system further comprises an in-vehicle air conditioning system and a vehicle window, the in-vehicle air conditioning system and the vehicle window can be automatically/manually controlled by a user at a mobile phone end, the user mobile device sends a control instruction to the cloud server, and the cloud server sends the control instruction to vehicle end application software installed on the IVI.
7. The in-vehicle life detection system of claim 1, wherein the OEM acceleration sensor collects real-time acceleration data, any in-vehicle artificial mechanical shock can cause a certain change in the acceleration data, the real-time data received by the vehicle-side application software installed on the IVI is transmitted to the cloud server in real time for neural network prediction calculation, and the prediction result of the cloud server is transmitted to the user mobile terminal.
8. The in-vehicle life detection system of claim 1, wherein the in-vehicle data collection system is deployed on a vehicle end, the cloud server is deployed with a motion detection mechanism, the APP on the user mobile device is configured to receive the motion detection mechanism, and communication among the in-vehicle data collection system, the vehicle end, the cloud server, the motion detection mechanism, and the user mobile device is based on a Web Socket protocol.
9. The in-vehicle life detection system of claim 1, wherein said in-vehicle data collection system is downloaded by a user in the form of software to an in-vehicle application installed on the IVI.
10. The in-vehicle life detection system of claim 1, wherein the in-vehicle life detection system operates as follows:
s1, judging whether the vehicle stops, if not, closing life detection in the vehicle, if so, judging whether the user position is the same as the vehicle stopping position, and if so, closing life detection in the vehicle;
s2, judging whether the parking time is less than 5 hours when the user position is not the same as the parking position of the vehicle, otherwise, closing life detection in the vehicle; if yes, the life detection in the vehicle is started;
s3, after the in-vehicle life detection is started, whether a life body is found is judged, if yes, the vehicle window is lowered, the air conditioner is started, then warning information is sent to a user, and the user is alert, and then rescue is organized;
s3, if the user is not alert, sending warning information to other mobile equipment matched with the accident vehicle, judging whether the user is alert, and if the user is alert, organizing rescue;
s4, if the user is not alert, judging whether other users are nearby, if yes, sending warning information to other nearby users, if the user is alert, organizing the rescue, if no other users and users are nearby, notifying the police, and the police organizing the rescue.
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| CN114906074A (en) * | 2022-04-07 | 2022-08-16 | 中国第一汽车股份有限公司 | Method and system for protecting children in vehicle at high temperature, vehicle-mounted equipment and vehicle thereof |
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