CN109677324B - Parking vehicle collision alarm method based on NB-IoT technology - Google Patents
Parking vehicle collision alarm method based on NB-IoT technology Download PDFInfo
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- CN109677324B CN109677324B CN201910074675.3A CN201910074675A CN109677324B CN 109677324 B CN109677324 B CN 109677324B CN 201910074675 A CN201910074675 A CN 201910074675A CN 109677324 B CN109677324 B CN 109677324B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q9/00—Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling
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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]
- H04W4/46—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
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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
- H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]
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Abstract
The invention provides a parking vehicle collision alarm method based on NB-IoT technology. A model database is established in advance, collision amplitude data are analyzed and compared, so that the position, type and degree of collision are obtained, and the data are judged to be true or false through a cloud computing server, so that the problems of false alarm, missing report and the like are solved.
Description
Technical Field
The invention belongs to the technical field of parking alarm, and particularly relates to a parking vehicle collision alarm method based on an NB-IoT technology.
Background
In the prior art, after the vehicle is collided by other vehicles, falling objects, foreign objects and the like, the registration alarm system judges whether the collision data is greater than a threshold value or not after acquiring the collision data, and gives a warning to a vehicle owner if the collision data is greater than the threshold value. However, the prior art has the following problems: the existing 3G, 4G and other data communication modes have high cost, large occupied bandwidth resources and short standby time. In addition, the existing judgment process is simple, and the false alarm rate and the missing report rate are high.
Disclosure of Invention
In order to solve the technical problem, the invention provides a parking vehicle collision alarm method based on NB-IoT technology. The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
The invention adopts the following technical scheme:
in some optional embodiments, there is provided a parking vehicle collision warning method based on NB-IoT technology, comprising: establishing a model algorithm;
the process of establishing the model algorithm comprises the following steps:
establishing an independent contact collision database for each vehicle type, wherein each vehicle type data field comprises: vehicle type ID, damage position, damage degree;
establishing an independent environment factor database for each vehicle type;
and establishing an experience algorithm database, wherein the data acquisition method is used for acquiring error records uploaded by a user through a mobile intelligent terminal aiming at single false alarm.
In some optional embodiments, when establishing the independent contact collision database of each vehicle type, the acquisition process of the simulation data comprises: the vibration data collector arranged in the vehicle is used for collecting data, a simulation collision test is carried out in each divided area of the vehicle, the amplitude of the damaged vehicle paint is used as a sample collection standard, and the grade is calibrated according to the damage degree.
In some optional embodiments, when the environmental factor database of each vehicle model is established, the acquisition process of the simulation data includes: acquiring amplitude data of damage to the vehicle caused by environmental factors through a vibration data acquisition unit arranged in the vehicle; the environmental factors include: wind, rain, noise, earthquake, and large objects passing through.
In some optional embodiments, the vehicle is divided into seven zones, namely, left front, right front, left center, right center, left rear, right rear and top of the vehicle.
In some optional embodiments, the NB-IoT technology-based parking vehicle collision warning method further includes:
the vehicle-mounted data acquisition terminal acquires collision amplitude data through the composite sensor and judges the truth of a collision event;
when the vehicle-mounted data acquisition terminal judges that the collision event is effective, uploading alarm information to a client management server cluster;
the customer management server cluster automatically matches the vehicle type ID of the current vehicle and the bound intelligent mobile terminal according to the equipment ID in the alarm information, and sends the collision amplitude data and the vehicle type ID to a cloud computing server;
the cloud computing server judges whether the data is true or false through a model algorithm, and compares the collision amplitude data through the model algorithm to obtain the position, type and degree of collision;
and when the cloud computing server judges that the data is real, the alarm information and the position, the type and the degree of the collision are sent to the mobile intelligent terminal bound with the equipment ID through the customer management server cluster.
In some optional embodiments, the process of determining whether the collision event is true or false by the vehicle-mounted data acquisition terminal includes: and if the vehicle is in a moving state or a person or a pet is in the vehicle, judging that the collision event is invalid.
In some optional embodiments, the alert information comprises: collision amplitude data, device ID, vehicle position coordinates, and collision occurrence time.
In some optional embodiments, the NB-IoT technology-based parking vehicle collision warning method further includes: and the mobile intelligent terminal compares the position coordinates of the vehicle in the alarm information with the current position coordinates of the home terminal, judges whether the vehicle is overlapped, and displays the alarm information and the position, type and degree of collision if the vehicle is not overlapped.
The invention has the following beneficial effects: a model database is established in advance, collision amplitude data are analyzed and compared, so that the position, type and degree of collision are obtained, and the data are judged to be true or false through a cloud computing server, so that the problems of false alarm, missing report and the like are solved.
For the purposes of the foregoing and related ends, the one or more embodiments include the features hereinafter fully described and particularly pointed out in the claims. The following description and the annexed drawings set forth in detail certain illustrative aspects and are indicative of but a few of the various ways in which the principles of the various embodiments may be employed. Other benefits and novel features will become apparent from the following detailed description when considered in conjunction with the drawings and the disclosed embodiments are intended to include all such aspects and their equivalents.
Drawings
FIG. 1 is a schematic diagram of a parking vehicle collision warning method of the present invention based on NB-IoT technology;
FIG. 2 is a flow diagram of a parking vehicle collision warning method of the present invention based on NB-IoT technology;
FIG. 3 is a schematic diagram of the model algorithm of the present invention.
Detailed Description
The following description and the drawings sufficiently illustrate specific embodiments of the invention to enable those skilled in the art to practice them. Other embodiments may incorporate structural, logical, electrical, process, and other changes. The examples merely typify possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in or substituted for those of others. The scope of embodiments of the invention encompasses the full ambit of the claims, as well as all available equivalents of the claims.
As shown in fig. 1 and 2, in some demonstrative embodiments, there is provided a parking vehicle collision alert method based on NB-IoT technology, including:
101: the vehicle-mounted data acquisition terminal senses that the vehicle is collided, and the vehicle-mounted data acquisition terminal acquires collision amplitude data through the composite sensor.
The composite sensor includes, but is not limited to, various sensor combinations such as acoustic, vibration, infrared, microwave, etc. Specifically, the composite sensor may include: g-sensor, infrared detector, microphone, GPS module, etc.
G-sensor: through a large number of collision tests performed on different positions of the vehicle, the sensitivity of the G-sensor is adjusted to a reasonable range so as to collect data such as the strength of amplitude generated by collision, the collision position and the like.
Infrared detector and microphone: for detecting whether a person or a pet is in the vehicle.
A GPS module: to obtain vehicle position data.
102: when the vehicle-mounted data acquisition terminal senses that the vehicle is collided, the vehicle-mounted data acquisition terminal preliminarily judges the authenticity of the collision event through the data acquired by the composite sensor. The judgment process is completed by the MCU of the vehicle-mounted data acquisition terminal so as to judge the authenticity of the data.
The specific process for preliminarily judging the authenticity of the collision event comprises the following steps:
if the vehicle is in a moving state or a person or a pet is in the vehicle, the collision event is judged to be invalid, namely the collision event is not real.
When the vehicle is in a static state and no person or pet is in the vehicle, if the vehicle is collided, the collision event can be judged to be effective, and the collision event is not caused by the operation of the vehicle owner. If the vehicle is in a moving state or a person or a pet is in the vehicle, if a collision occurs, the collision is caused to the operation of the owner, and the collision event can be judged to be invalid. The preliminary judgment can filter out part of false alarms, reduce the occupation of analysis resources and ensure that the flow is more accurate and optimized.
103: and the vehicle-mounted data acquisition terminal uploads the alarm information to the client management server cluster.
The alarm information includes: collision amplitude data, device ID, vehicle position coordinates, and collision occurrence time.
And the vehicle-mounted data acquisition terminal calls the NB-IoT communication module and uploads the alarm information to the customer management server cluster through the narrowband IoT communication technology. The novel NB-IoT communication technology is utilized to replace the existing 2\3\4G and subsequent 5G mobile communication modes, and the method has the advantages of low power consumption, high efficiency, less occupied bandwidth resources, low use cost, capability of providing comprehensive indoor cellular data connection coverage and the like.
104: the customer management server cluster automatically matches the model ID of the current vehicle and the bound intelligent mobile terminal according to the equipment ID in the alarm information, and specifically can match the APP on the intelligent mobile terminal.
And the client management server cluster sends the collision amplitude data and the vehicle type ID to the cloud computing server. And the distinctive analysis and calculation are carried out according to different vehicle types, so that the calculation result is more accurate.
105: and the cloud computing server judges whether the data is true or false through a model algorithm, if the data is judged to be valid, the step 106 is carried out, and if the data is judged to be invalid, the process is ended. And the cloud computing server compares the collision amplitude data through a model algorithm, and if the uploaded collision amplitude data is found to be in accordance with the amplitude data in the model, the data is judged to be valid, namely the data is real.
106: and the cloud computing server compares the collision amplitude data through a model algorithm to obtain the position, type and degree of the collision. And the cloud computing server compares the collision amplitude data with data in a pre-established algorithm model database through a model algorithm, and when the collision amplitude data are in accordance with the data in the pre-established algorithm model database, the position, the type and the degree of the collision can be correspondingly identified.
107: and when the cloud computing server judges that the data is real, issuing the alarm information and the position, type and degree of collision to the mobile intelligent terminal bound with the equipment ID through the client management server cluster. Specifically, the position, type and degree of the alarm information and the collision can be issued to the APP bound with the equipment ID through the client management server cluster, and the APP is installed on the mobile intelligent terminal.
The mobile intelligent terminal is one or more of a mobile phone, a tablet personal computer and a computer.
108: after the mobile intelligent terminal receives the alarm information, comparing the vehicle position coordinates in the alarm information with the current position coordinates of the home terminal, judging whether the vehicle position coordinates coincide with the current position coordinates of the home terminal, and if the vehicle position coordinates do not coincide with the current position coordinates of the home terminal, performing step 109; if the collision information is coincident with the alarm information, judging that the collision is the arrival of the vehicle owner and the motor vehicle, and ignoring the alarm information.
109: the mobile intelligent terminal displays alarm information and the position, type and degree of collision. Specifically, the alarm information can be popped up through the APP installed on the mobile intelligent terminal, and the position, the type and the degree of collision are displayed.
The invention also includes: and establishing a model algorithm.
The process of establishing the model algorithm comprises the following steps:
s1: and establishing an independent contact collision database for each vehicle type, and updating and maintaining the data.
The individual vehicle type data fields include: vehicle type ID, damage location, damage level.
The acquisition process of the simulation data comprises the following steps: the vibration data collector arranged in the vehicle is used for collecting data, a simulation collision test is carried out in each divided area of the vehicle, the amplitude of the damaged vehicle paint is used as a sample collection standard, and the grade is calibrated according to the damage degree. The data in the contact collision database can be updated in real time according to the test, namely, the data is maintained, and the accuracy of the algorithm is ensured.
The vehicle is divided into seven areas, namely left front, right front, left middle, right middle, left rear, right rear and top of the vehicle.
S2: and establishing an independent environment factor database for each vehicle type, namely establishing an independent non-contact collision database for each vehicle type, and continuously improving.
The acquisition process of the simulation data comprises the following steps: the vehicle is placed in an actual environment, and the vibration amplitude data of the damage of the vehicle caused by the environmental factors are collected through a vibration data collector placed inside the vehicle.
Environmental factors include: wind, rain, noise, earthquakes, large objects such as vehicles.
S3: and establishing an empirical algorithm database. The data acquisition method comprises the steps of acquiring an error record uploaded by a user through a mobile intelligent terminal aiming at single false alarm so as to continuously perfect a model algorithm. Specifically, data can be uploaded through an APP on the mobile intelligent terminal, so that a model algorithm is perfected.
As shown in fig. 3, the cloud computing server compares the collision amplitude data with the model algorithm to obtain the position, type, and degree of the collision, and first inputs the collision amplitude data and the vehicle type ID, and searches an adaptive algorithm model database according to the vehicle type ID; judging whether the collision amplitude data is in accordance with the data in the environmental factor database, if so, judging whether the collision is caused by the environmental factors, neglecting the current collision amplitude data, if not, judging whether the collision amplitude data is in accordance with the data in the contact collision database, if so, outputting alarm confirmation data, and issuing alarm information and the position, type and degree of the collision through the customer management server cluster.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
Claims (5)
1. The parking vehicle collision alarm method based on the NB-IoT technology is characterized by comprising the following steps: establishing a model algorithm;
the process of establishing the model algorithm comprises the following steps:
establishing an independent contact collision database for each vehicle type, wherein each vehicle type data field comprises: vehicle type ID, damage position, damage degree;
establishing an independent environment factor database for each vehicle type;
establishing an experience algorithm database, wherein the data acquisition method is to acquire an error record of a user for single false alarm uploading through a mobile intelligent terminal; the process of judging the authenticity of the collision event by the vehicle-mounted data acquisition terminal comprises the following steps:
if the vehicle is in a moving state or a person or a pet is in the vehicle, judging that the collision event is invalid; the alarm information includes: collision amplitude data, device ID, vehicle position coordinates, collision occurrence time; further comprising: and the mobile intelligent terminal compares the position coordinates of the vehicle in the alarm information with the current position coordinates of the home terminal, judges whether the vehicle is overlapped, and displays the alarm information and the position, type and degree of collision if the vehicle is not overlapped.
2. The NB-IoT technology-based parking vehicle collision warning method as claimed in claim 1, wherein the simulation data collection process comprises: the vibration data collector arranged in the vehicle collects data, the simulation collision test is carried out in each divided area of the vehicle, the amplitude of the damaged vehicle paint is taken as a sample collection standard, and the grade is calibrated according to the damage degree.
3. The NB-IoT technology-based parking vehicle collision warning method as claimed in claim 1 or 2, wherein the simulation data collection process comprises: acquiring amplitude data of damage to the vehicle caused by environmental factors through a vibration data acquisition unit arranged in the vehicle; the environmental factors include: wind, rain, noise, earthquake, and large objects passing through.
4. The NB-IoT technology-based parking vehicle collision warning method as recited in claim 2, wherein the vehicle is divided into seven zones, namely, left front, right front, left center, right center, left rear, right rear and top of the vehicle.
5. The NB-IoT technology-based parking vehicle collision warning method as recited in claim 1, further comprising:
the vehicle-mounted data acquisition terminal acquires collision amplitude data through the composite sensor and judges the truth of a collision event;
when the vehicle-mounted data acquisition terminal judges that the collision event is effective, uploading alarm information to a client management server cluster;
the customer management server cluster automatically matches the current vehicle type ID and the bound intelligent mobile terminal according to the equipment ID in the alarm information, and sends the collision amplitude data and the vehicle type ID to a cloud computing server;
the cloud computing server judges whether the data is true or false through a model algorithm, and compares the collision amplitude data through the model algorithm to obtain the position, type and degree of collision;
and when the cloud computing server judges that the data is real, the alarm information and the position, the type and the degree of the collision are sent to the mobile intelligent terminal bound with the equipment ID through the customer management server cluster.
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| CN114179745A (en) * | 2020-09-15 | 2022-03-15 | 郑州宇通客车股份有限公司 | Vehicle accident identification method and device and vehicle |
| CN114866999B (en) * | 2022-04-22 | 2024-04-16 | 中国第一汽车股份有限公司 | Positioning vehicle-mounted emergency rescue system and rescue method |
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