Tire ignition detection method, electronic equipment and medium

Abstract

The invention discloses a tire ignition detection method, electronic equipment and a medium, and relates to the technical field of tire detection. According to the specific implementation scheme, the method comprises the steps of obtaining driving data of a driving vehicle, wherein the driving data comprises a vehicle state and a vehicle environment; the vehicle state at least comprises the tire state of each tire in the vehicle; the driving data is uploaded to a server; and receiving the ignition detection result of each tire in the vehicle fed back by the server. The embodiment of the invention can improve the running safety of the vehicle.

Description

Technical Field

[0001] The present invention relates to the field of tire detection and identification, and particularly to a tire fire detection method, an electronic device, and a medium. Background Art

[0002] With the rapid development of the commercial vehicle transportation industry, vehicle safety issues have received increasing attention. During long-distance transportation of commercial vehicles, due to factors such as long-term friction of tires and overheating of braking systems, wheel-end fire accidents occur from time to time, posing a serious threat to people's lives and property safety.

[0003] Currently, the vehicle fire prevention systems mainly focus on alarm and fire extinguishing after a fire occurs. This method may lead to the inability to extinguish the fire in time, resulting in danger. Summary of the Invention

[0004] The present invention provides a tire fire detection method, an electronic device, and a medium, which can improve the safety of vehicle operation.

[0005] In a first aspect, the present invention provides a tire fire detection method, including:

[0006] Obtaining driving data of a vehicle in motion, where the driving data includes: vehicle status and vehicle environment; the vehicle status at least includes the tire status of each tire in the vehicle;

[0007] Uploading the driving data to a server;

[0008] Receiving the tire fire detection results of each tire in the vehicle fed back by the server.

[0009] In a second aspect, the present invention further provides a tire fire detection method, including:

[0010] Receiving driving data sent by a vehicle, where the driving data includes: vehicle status and vehicle environment; the vehicle status at least includes the tire status of each tire in the vehicle;

[0011] Determining the tire fire detection results of each tire in the vehicle according to the driving data;

[0012] Feeding back the fire detection results to the vehicle.

[0013] In a third aspect, the present invention further provides a tire fire detection device, which is characterized by including:

[0014] A driving data acquisition module, configured to acquire driving data of a vehicle in motion, where the driving data includes: vehicle status and vehicle environment; the vehicle status at least includes the tire status of each tire in the vehicle;

[0015] A driving data uploading module, configured to upload the driving data to a server;

[0016] A fire safety detection module, configured to receive the fire detection results of each tire in the vehicle fed back by the server.

[0017] Fourthly, the present invention further provides a tire fire detection device, which is characterized by comprising:

[0018] A driving data receiving module, configured to receive driving data sent by a vehicle, where the driving data includes: vehicle status and vehicle environment; the vehicle status at least includes the tire status of each tire in the vehicle;

[0019] A fire prediction module, configured to determine the fire detection results of each tire in the vehicle according to the driving data;

[0020] A result feedback module, configured to feedback the fire detection results to the vehicle.

[0021] Fifthly, the present invention further provides an electronic device, where the electronic device includes:

[0022] At least one processor; and

[0023] A memory communicatively connected to the at least one processor; wherein,

[0024] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the tire fire detection method according to any embodiment of the present invention.

[0025] Sixthly, the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the tire fire detection method according to any embodiment of the present invention is implemented.

[0026] In the embodiments of the present invention, by obtaining the driving data of a running vehicle and predicting the fire detection results of each tire by a server according to the driving data, it is possible to predict whether there is a potential fire risk in the tire, solve the problem in the prior art that only warning can be given after a fire occurs, which causes danger, and can remind a driver to drive in a standard manner from the perspective of early warning to avoid a fire, thereby reducing the probability of tire fire and improving the driving safety of the vehicle.

[0027] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Description of the Drawings

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0029] Figure 1 is a flowchart of a tire fire detection method provided according to an embodiment of the present invention;

[0030] Figure 2 is a flowchart of a tire fire detection method provided according to an embodiment of the present invention;

[0031] Figure 3 is an application scenario diagram of a tire fire detection system provided according to an embodiment of the present invention;

[0032] Figure 4 is an application scenario diagram of a fire probability detection model provided according to an embodiment of the present invention;

[0033] Figure 5 is a schematic structural diagram of a tire fire detection device provided according to an embodiment of the present invention;

[0034] Figure 6 is a schematic structural diagram of a tire fire detection device provided according to an embodiment of the present invention;

[0035] Figure 7 is a schematic structural diagram of an electronic device for implementing the tire fire detection method of the embodiments of the present invention. Detailed implementation manners

[0036] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0037] It should be noted that in the description and claims of the present invention and the above-mentioned drawings, terms such as "first" and "second" are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0038] In the technical solution of the embodiment of the present invention, the acquisition, storage, and application of user information and the like all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0039] Figure 1 The figure is a flowchart of a tire fire detection method provided by an embodiment of the present invention. This embodiment is applicable to predicting whether there is a fire risk in the tires of a moving vehicle. This method can be executed by a tire fire detection device, which can be implemented in the form of hardware and / or software and is specifically configured in an electronic device. The electronic device can be a terminal device, and the terminal device can include: a mobile phone, a computer, a car machine, or a wearable device, etc. The wearable device can be a smart glasses or a smart watch, etc.

[0040] See Figure 1 the tire fire detection method shown in the figure, including:

[0041] S101. Obtain the driving data of a moving vehicle, where the driving data includes: vehicle status and vehicle environment; the vehicle status at least includes the tire status of each tire in the vehicle.

[0042] Among them, the driving data can be data that can be obtained during the driving process of the vehicle. The vehicle status can refer to the data of the vehicle's own status, and the vehicle status affects whether the tire catches fire. The vehicle environment can be data related to the environment in which the vehicle travels, and this vehicle environment affects whether the tire catches fire. In the embodiment of the present invention, in order to detect whether there is a fire risk in each tire, correspondingly, the vehicle status needs to include the tire status of each tire. The tire status can refer to the status of the tire that affects catching fire. The driving data can be data obtained by the vehicle within a period of time. The vehicle can periodically obtain the driving data and perform fire prediction. The data of the historical period can be used as the context of the driving data and participate in the fire prediction together with the driving data of the current period, or the fire prediction can be performed only for the driving data of the current period.

[0043] S102. Upload the driving data to the server.

[0044] For a moving vehicle, the process of fire prediction can be executed in the service, which can reduce the resource consumption of the vehicle. Moreover, the server has sufficient computing power and can deploy algorithms with a larger capacity to detect whether there is a fire risk in the tires. This can reduce the adjustment and maintenance of the vehicle itself, and thus improve the implementation efficiency of the fire prediction function.

[0045] S103. Receive the fire detection results of each tire in the vehicle fed back by the server.

[0046] The server is used to process the driving data to obtain the fire detection results of each tire. The fire detection result of a tire can include on fire or not on fire.

[0047] In the embodiment of the present invention, by obtaining the driving data of a moving vehicle and having the server predict the fire detection results of each tire according to the driving data, it is possible to predict whether there is a potential fire risk in the tires, solving the problem in the prior art that warnings can only be given after a fire occurs, which is dangerous. From the perspective of early warning, the driver can be reminded to drive in a standard manner to avoid fires, thereby reducing the probability of tire fires and improving the driving safety of the vehicle.

[0048] In an optional embodiment, the tire state of the tire includes at least one of the following: the tire pressure, tire temperature, and wear degree of the tire; the vehicle state further includes: vehicle speed, braking frequency, and braking force; the vehicle environment includes at least one of the following: weather, climate, and road surface friction state.

[0049] Among them, when the tire pressure of the tire is relatively low, heat will be generated by friction, causing the temperature of the tire to be relatively high, and then causing a fire. Or when the tire pressure is relatively high, micro-cracks are likely to appear. When the vehicle is driving at a high speed or braking suddenly, the cracks may generate high-temperature fire points due to friction. And a high-temperature road surface will cause the tire temperature to rise while increasing the tire pressure. Therefore, the increase in tire pressure may represent an increase in tire temperature.

[0050] Excessive tire temperature will cause a fire. A tire with a serious wear degree has a relatively high local temperature, which causes the temperature of the tire to be relatively high and causes a fire.

[0051] When the vehicle speed is too fast, the heat accumulation speed generated by the tire rolling resistance is too fast, causing the temperature of the tire to be relatively high and causing the tire to catch fire.

[0052] Both too high a braking frequency and too large a braking force will increase the heat generated by braking, causing the temperature of the tire to be relatively high and causing the tire to catch fire.

[0053] An increase in the temperature of the weather can cause the temperature of the tire to rise, leading to tire fires. While a too low temperature of the weather can cause the elasticity of the rubber to decrease, increasing the effect of heat generation due to frictional deformation, resulting in an increase in the temperature of the tire and causing tire fires. A decrease in the humidity of the weather can increase the effect of heat generation due to friction, leading to an increase in the temperature of the tire and causing tire fires.

[0054] Higher temperatures in summer can cause the temperature of the tire to rise, leading to tire fires. Lower temperatures in winter can cause the elasticity of the rubber to decrease, increasing the effect of heat generation due to frictional deformation, resulting in an increase in the temperature of the tire and causing tire fires. Continuous high temperatures or dry and windy climates can both cause the temperature of the tire to rise, leading to tire fires.

[0055] An increase in road surface friction can cause the tire to overheat, leading to tire fires. Or if the road surface friction is too low, resulting in frequent skidding of the tire and an increase in the heat generated by instantaneous friction, it can cause the tire to overheat, leading to tire fires.

[0056] It can be seen that by using state data from multiple dimensions that affect the tire temperature to detect whether there is a fire risk in the vehicle's tires, the content of the input data can be enriched, the representativeness of the input data can be improved, the accuracy of fire detection can be enhanced, and the state data is real-time related to the vehicle's driving, enabling accurate prediction of the fire probability as the vehicle drives and changes.

[0057] In an optional embodiment, after determining the fire detection results of each tire in the vehicle, at least one of the following is further included: when the fire detection result is a fire, controlling the display screen to display a fire warning message; controlling the seat to vibrate; and controlling or prompting the vehicle to stop driving.

[0058] Among them, a fire detection result of a fire indicates that there is a relatively high probability of a fire in the vehicle's tires. At this time, a fire warning can be given to the users inside the vehicle. The fire warning message can include text, images, videos, etc. Displaying the fire warning message on the display screen realizes visual dimension warning to the users inside the vehicle about the tire fire. The seat vibration realizes tactile dimension warning to the users inside the vehicle about the tire fire. It is possible to vibrate only the driver's seat or all seats. In addition, a fire warning can also be given to the users by means of voice or flashing lights, etc. Controlling the vehicle to decelerate and drive can provide a quick response strategy for the users from the dimension of fire response. In the case where the vehicle is an autonomous vehicle, in the autonomous driving mode, the vehicle can be controlled to decelerate and stop to avoid a real fire caused by continued driving. Or the user can be prompted to decelerate and stop by means of the display screen or voice, etc.

[0059] In some embodiments, images of tires with a fire detection result of on fire can also be collected and used as fire warning information to be displayed on a display screen, so as to help the users in the vehicle better and more comprehensively understand the situation of the tires with fire warnings. Among them, images of tires with a fire detection result of not on fire may not be collected or displayed.

[0060] It can be seen that after determining the fire detection result of the tire, by displaying fire warning information, vibrating the seat, controlling or prompting the vehicle to stop, early warning and reminder for the users in the vehicle can be realized, and the driving users can be reminded to drive in a standardized manner from the perspective of early warning, reducing the probability of tire fire.

[0061] In an alternative embodiment, the vehicle includes a goods transportation vehicle, and the vehicle state further includes: the goods weight.

[0062] In fact, goods transportation vehicles usually operate overloaded for a long time, and there is often a risk of modification, resulting in a higher risk of fire. Moreover, the fire of goods transportation vehicles will cause a large amount of personal and property losses. A large goods weight will cause the contact area between the tire and the ground to increase, enhancing the effect of heat generation by friction. In addition, the braking system of an overloaded vehicle is overloaded, resulting in too high a temperature of the brakes, which causes the tire to burst through heat conduction. Therefore, the goods weight is a factor for detecting whether there is a fire.

[0063] It can be seen that by adding the goods weight as a vehicle state for predicting whether there is a fire in the scenario of tire fire detection for goods transportation vehicles, the input data for predicting fire can be enriched, the representativeness of the basis content for predicting fire can be increased, and then the accuracy of the fire prediction result can be improved. Moreover, it can better adapt to the scenario of goods transportation vehicles and improve the driving safety of goods transportation vehicles.

[0064] In an example, the vehicle includes an on-vehicle terminal, a collection module, and a display module. The collection module sends the collected driving data to the on-vehicle terminal, and the on-vehicle terminal uploads it to the server. The server determines the fire detection result based on the driving data and feeds it back to the on-vehicle terminal. The on-vehicle terminal controls the display module to display the image of the predicted tire on fire and issue an early warning. The server and the on-vehicle terminal are communicatively connected through a 4G network; the on-vehicle terminal is communicatively connected to the collection module and the display module through a Controller Area Network (CAN). The collection module is used to collect driving data. The display module is used to receive the image of the predicted tire on fire, display the image, and can also display fire warning information. When the display module displays the image of the predicted tire on fire, it can focus on the tire with a fire risk. The display module can also control the display screen to display fire warning information. In some embodiments, the display module can also control the instrument panel to display fire warning information.

[0065] In addition, the vehicle may further include a seat control module, which controls the seat to vibrate when receiving the fire detection result of a fire. The seat control module and the vehicle-mounted terminal can be communicatively connected via CAN.

[0066] Figure 2 FIG. 4 is a flowchart of a tire fire detection method provided by an embodiment of the present invention. This embodiment is applicable to the situation of predicting whether there is a fire risk for the tires of a vehicle in motion. This method can be executed by a tire fire detection device, which can be implemented in the form of hardware and / or software and is specifically configured in an electronic device, and the electronic device can be a server.

[0067] See Figure 2 The tire fire detection method shown in FIG. 4 includes:

[0068] S201. Receive the driving data sent by the vehicle, where the driving data includes: vehicle status and vehicle environment; the vehicle status at least includes the tire status of each tire in the vehicle.

[0069] S202. Determine the fire detection result of each tire in the vehicle according to the driving data.

[0070] S203. Feed back the fire detection result to the vehicle.

[0071] By executing the task of determining the fire detection result of the tire according to the driving data in the server in the embodiment of the present invention, complex computing tasks can be executed by high-performance hardware devices, the processing time can be shortened, the processing efficiency can be improved, and the accuracy of fire detection can be improved. There is no need for the terminal device to bear excessive computing power requirements, and the configuration cost of the terminal device can be reduced.

[0072] In an optional embodiment, the determining the fire detection result of each tire in the vehicle according to the driving data includes: inputting the driving data into a pre-trained fire probability detection model for processing to obtain the fire probability of each tire output by the fire probability detection model; and determining the fire detection result of each tire according to the fire probability of each tire.

[0073] Among them, the fire probability detection model is used to process the input driving data and output the fire probability of each tire included in the vehicle. The fire probability model can be a deep learning model. The fire probability model can encode the driving data to obtain a feature vector, and decode the feature vector to obtain the fire probability of each tire. When the fire probability of a tire is greater than or equal to a preset probability threshold, it is determined that the fire detection result of the tire is on fire; when the fire probability of a tire is less than the preset probability threshold, it is determined that the fire detection result of the tire is not on fire.

[0074] Among them, the driving data at least includes the tire states of all tires, and the number of included tire states (i.e., the number of tires) is the same as the number of fire probabilities output by the fire probability model. In some embodiments, the order of the tires corresponding to the tire states in the driving data is the same as the order of the tires corresponding to the fire probabilities output by the fire probability model.

[0075] In an example, the driving data input to the fire probability model includes the tire states of tire 1, tire 2, tire 3, tire 4, tire 5, tire 6, etc. The fire probabilities output by the fire probability model include: the fire probability of tire 1, the fire probability of tire 2, the fire probability of tire 3, the fire probability of tire 4, the fire probability of tire 5, the fire probability of tire 6, etc.

[0076] It can be seen that the fire probability detection model can quickly and accurately detect tire fires, and the fire probability detection model can continuously self-learn to improve the accuracy of tire fire detection.

[0077] In an alternative embodiment, the fire probability detection model is trained in the following manner: obtaining the driving data of vehicles and the corresponding tire fire information in multiple fire experiments; obtaining the driving data of multiple historically burned vehicles and the corresponding tire fire information; generating a training dataset according to the driving data, the corresponding tire fire information in each fire experiment, and the driving data and the corresponding tire fire information of each historically burned vehicle, where the training dataset includes training samples, and the training samples include the driving data of the vehicle and the corresponding tire fire labels; using the training dataset to train the fire probability detection model.

[0078] Among them, the fire experiment can be a safety test on the vehicle before the vehicle is released or sold. Multiple fire experiments can be carried out on the vehicle to collect the driving data of the vehicle during a period of time when the tire catches fire and before the fire occurs, and to collect the driving data of the vehicle during a period of time when the tire does not catch fire and before the fire does not occur. The driving data of a vehicle when a fire occurs or does not occur, and the driving data of the vehicle in the previous period of time are used as a training sample, and according to the tire fire information of whether the tire catches fire or does not catch fire, the tire fire label of the corresponding training sample is generated. Specifically, the tire fire label includes the result of whether each tire included in the vehicle catches fire, and is a binary classification label of fire or no fire. During the process of carrying out multiple fire experiments on the vehicle, a large number of training samples and the tire fire labels of each training sample are generated and determined as the training dataset.

[0079] The driving data of a vehicle with a historical fire can be the driving data of the vehicle during a period of time before and at the time of a fire incident in a collected fire incident. The tire fire information corresponding to this driving data is usually a fire, that is, the tire fire label of this driving data is a fire. A fire incident can generate a training sample and determine that the tire fire label of this training sample is a fire. In addition, the driving data of a vehicle that is operating normally without a fire can be obtained, and the tire fire label of this driving data is determined to be no fire. Select the driving data within a period of time to generate a training sample and determine that the tire fire label of this training sample is no fire.

[0080] According to a large number of training samples and the tire fire labels of the training samples, train the fire probability detection model. When the training meets the training completion condition, determine that the fire probability detection model is trained and can be applied.

[0081] In some embodiments, input the training sample into the fire probability detection model for processing, obtain the fire probabilities of each tire output by the fire probability detection model, calculate the difference between the fire probability of each tire and the label of the tire, and sum the differences of each tire to obtain a loss function. With the goal of minimizing the loss function or the convergence of the loss function, adjust the parameters of the fire probability detection model. Among them, in the label, the fire probability corresponding to a tire fire is 1, and the fire probability corresponding to a tire without a fire is 0.

[0082] In some embodiments, all training samples can be divided into a training set and a validation set. When the accuracy rate of the validation set is greater than or equal to a preset accuracy rate threshold, determine that the fire probability detection model is trained. Or when all training samples are trained or the number of iterations is greater than or equal to a preset number threshold, determine that the fire probability detection model is trained.

[0083] It can be seen that by obtaining the data of vehicle fire experiments and generating a training sample data set, training the fire probability detection model, a training sample with high representativeness can be constructed based on real fire data to train the model, and the fire detection accuracy of the fire probability detection model can be improved.

[0084] In an alternative embodiment, before determining the fire detection results of each tire in the vehicle according to the driving data, it further includes: determining the tire maintenance data of each tire in the vehicle according to the driving data; determining the service life of each tire according to the tire maintenance data of each tire in the vehicle; and adding the service life of each tire as the tire state of each tire to the driving data.

[0085] Among them, the vehicle can query the local tire repair data, add it to the driving data, and send it to the server. Or the server queries the tire repair data of the vehicle in the database or external network server according to the identification of the vehicle in the driving data after user authorization. The tire repair data can include the abnormal cause of the tire and the repair method, etc. The tire repair data can be the influence degree of the abnormal cause of the tire on the service life, whether the tire has been repaired, the repair method and the influence degree of the repair method on the service life, etc. The tire repair data can be input into a pre-trained life detection model for processing to obtain the service life of each tire. The service life of each tire is used as the tire state of each tire and added to the driving data.

[0086] In addition, the server can also query the log data of the vehicle according to the identification of the vehicle after user authorization, or obtain the log data sent by the vehicle. According to the log data combined with the tire repair data, the service life of each tire is obtained, and according to the service life of the tire and the standard life corresponding to the tire, the service life detection result of whether the tire is used abnormally is determined.

[0087] Among them, the log data can include the models of each tire of the vehicle, the usage and abnormal conditions of the vehicle's tires, etc. Among them, the model of the tire corresponds to the standard service life of the tire. The usage of the tire can be the service life of the tire, the road conditions traveled by the tire, the area traveled by the tire, and the total length traveled by the tire, etc. The abnormal condition can be whether the tire has problems and the duration of the abnormality, etc.

[0088] Among them, the service life detection result can include abnormal service life or normal service life, etc. The service life can be added to the driving data, and the service life detection result can also be used as the tire state of each tire and added to the driving data. In addition, the server can also feedback the service life detection result of each tire to the vehicle so that the vehicle can feedback the life detection result to the in-vehicle user. Or the server feedbacks the life detection result of the abnormal service life of each tire to the vehicle so that the vehicle can feedback the abnormal service life and the corresponding tire to the in-vehicle user, and issue a warning to the in-vehicle user in terms of life to prompt the user to maintain the tire.

[0089] In some embodiments, the tire repair data and the log data can be input into a preset life detection model to obtain the predicted service life of each tire.

[0090] It can be seen that by adding the service life determined by the tire repair data to the driving data, the driving data is enriched, and thus the accuracy of fire detection is improved.

[0091] In an example, such as Figure 3Structural diagram of a system for implementing a tire fire detection method. The tire fire detection system includes a vehicle and a server. Among them, the vehicle includes an on-vehicle terminal, a collection module, a display module, a display screen, and a seat control module, etc. Among them, the on-vehicle terminal is communicatively connected to the collection module, the display module, and the seat control module through CAN, and the on-vehicle terminal is communicatively connected to the server through a 4G network. A fire probability detection model runs in the server. The on-vehicle terminal is used to send driving data, receive fire detection results, and control the collection module, the display module, and the seat control module. The collection module is used to collect driving data and images of the tires, and upload the collected driving data to the server through the on-vehicle terminal. The display module is used to receive images of the predicted fire-prone tires, display the images on the display screen, and can also display fire warning information. The seat control module is used to vibrate the seat to prompt the in-vehicle user of the fire warning. The server can input the driving data sent by the vehicle into the fire probability detection model. Through continuous self-learning, the fire probability detection model can predict whether the vehicle tires will catch fire. The server obtains the fire probabilities of the tires of the vehicle, determines the fire detection results of the tires, and feeds them back to the vehicle. The vehicle determines whether to give a fire warning according to the fire detection results of the tires.

[0092] In one example, as Figure 4 Scene diagram of the training process and application process of the fire probability detection model in the server shown. Training samples and corresponding tire fire labels can be generated based on fire historical data and fire experiment data. Among them, the fire historical data includes: driving data of historical fire vehicles and tire fire information. The fire experiment data includes: driving data of vehicles in the fire experiment and corresponding tire fire information. According to the training samples and the corresponding tire fire labels, the fire probability detection model is trained. After training is completed, the vehicle state and vehicle environment in the driving data are input into the fire probability detection model for processing, and the fire probabilities of the tires in the vehicle are output.

[0093] The embodiments of the present invention can accurately predict the fire risk of commercial vehicle tires in real time, warn users in advance, thereby reducing the probability of wheel-end fires, improving the safety of commercial vehicle transportation, and reducing the occurrence of fire accidents.

[0094] Figure 5 Structural schematic diagram of a tire fire detection device provided by an embodiment of the present invention. The embodiments of the present invention are applicable to the situation of predicting whether there is a fire risk for the tires of a vehicle in motion. The device can execute a tire fire detection method. The tire fire detection device can be implemented in the form of hardware and / or software, and the device can be configured in an electronic device.

[0095] See Figure 5 The tire fire detection device shown includes:

[0096] A driving data acquisition module 501 is configured to acquire driving data of a vehicle in motion, where the driving data includes: vehicle status and vehicle environment; the vehicle status at least includes the tire status of each tire in the vehicle;

[0097] A driving data uploading module 502 is configured to upload the driving data to a server;

[0098] A fire safety detection module 503 is configured to receive the fire detection results of each tire in the vehicle feedback by the server.

[0099] In an embodiment of the present invention, by acquiring the driving data of a vehicle in motion and having the server predict the fire detection results of each tire based on the driving data, it is possible to predict whether there is a potential fire risk in the tire, solving the problem in the prior art that only early warnings can be given after a fire occurs, which may lead to danger. It can remind the driver to drive in a standard manner to avoid fires from the perspective of early warning, thereby reducing the probability of tire fires and improving the driving safety of the vehicle.

[0100] Optionally, the tire status of the tire includes at least one of the following: the tire pressure, tire temperature, and wear degree of the tire; the vehicle status further includes: vehicle speed, braking frequency, and braking force; the vehicle environment includes at least one of the following: weather, climate, and road surface friction status.

[0101] Optionally, the tire fire detection device further includes at least one of the following:

[0102] A fire warning module, configured to, after determining the fire detection results of each tire in the vehicle, control a display screen to display a fire warning message when the fire detection result is a fire;

[0103] A seat vibration module, configured to control the seat to vibrate; and

[0104] A driving warning module, configured to control or prompt the vehicle to stop driving.

[0105] Optionally, the vehicle includes a goods transportation vehicle, and the vehicle status further includes: goods weight.

[0106] The tire fire detection device provided in an embodiment of the present invention can execute the tire fire detection method provided in any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the tire fire detection method.

[0107] Figure 6Schematic diagram of a tire fire detection device provided by an embodiment of the present invention. The embodiment of the present invention is applicable to the situation of predicting whether there is a fire risk for the tires of a moving vehicle. The device can execute a tire fire detection method. The tire fire detection device can be implemented in the form of hardware and / or software, and the device can be configured in an electronic device.

[0108] Referring to Figure 6 the tire fire detection device shown in

[0109] a driving data receiving module 601, configured to receive driving data sent by a vehicle, where the driving data includes: vehicle status and vehicle environment; the vehicle status at least includes the tire status of each tire in the vehicle;

[0110] a fire prediction module 602, configured to determine a fire detection result of each tire in the vehicle according to the driving data;

[0111] a result feedback module 603, configured to feedback the fire detection result to the vehicle.

[0112] In the embodiment of the present invention, by executing the task of determining the fire detection result of the tire according to the driving data in the server, complex computing tasks can be executed by high-performance hardware devices, the processing time can be shortened, the processing efficiency can be improved, and the accuracy of fire detection can be improved. There is no need for the terminal device to bear excessive computing power requirements, and the configuration cost of the terminal device is reduced.

[0113] Optionally, the fire prediction module 602 includes:

[0114] a model prediction unit, configured to input the driving data into a pre-trained fire probability detection model for processing, and obtain the fire probability of each tire output by the fire probability detection model;

[0115] a fire detection unit, configured to determine the fire detection result of each tire according to the fire probability of each tire.

[0116] Optionally, the tire fire detection device further includes: a model training module, configured to:

[0117] obtain the driving data of the vehicle and the corresponding tire fire information in multiple fire experiments;

[0118] obtain the driving data of the vehicle and the corresponding tire fire information of multiple historically burning vehicles;

[0119] generate a training data set according to the driving data, the corresponding tire fire information in each fire experiment, the driving data of the vehicle and the corresponding tire fire information of each historically burning vehicle, where the training data set includes training samples, and the training samples include the driving data of the vehicle and the corresponding tire fire labels;

[0120] The fire probability detection model is trained using the training data set described above.

[0121] Optionally, the tire fire detection device further includes:

[0122] A maintenance data acquisition module, configured to determine the tire maintenance data of each tire in the vehicle according to the driving data before determining the fire detection result of each tire in the vehicle according to the driving data;

[0123] A service life determination module, configured to determine the service life of each tire according to the tire maintenance data of each tire in the vehicle;

[0124] A service life addition module, configured to add the service life of each tire as the tire state of each tire to the driving data.

[0125] The tire fire detection device provided by the embodiments of the present invention can execute the tire fire detection method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the tire fire detection method.

[0126] Figure 7 FIG. shows a schematic structural diagram of an electronic device 700 that can be used to implement an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as, for example, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, for example, a personal digital processor, a cellular phone, a smart phone, a wearable device (such as a helmet, glasses, a watch, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present invention described herein and / or claimed.

[0127] As Figure 7As shown, the electronic device 700 includes at least one processor 701 and a memory communicatively connected to the at least one processor 701, such as a read-only memory (ROM) 702, a random access memory (RAM) 703, etc. The memory stores a computer program executable by the at least one processor. The processor 701 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 702 or the computer program loaded from the storage unit 708 into the random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the electronic device 700 can also be stored. The processor 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0128] Multiple components in the electronic device 700 are connected to the I / O interface 705, including: an input unit 706, such as a keyboard, a mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a disk, an optical disc, etc.; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the electronic device 700 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0129] The processor 701 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 701 include but are not limited to a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 701 executes the various methods and processes described above, such as the tire fire detection method.

[0130] In some embodiments, the tire fire detection method can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as the storage unit 708. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded into the RAM 703 and executed by the processor 701, one or more steps of the tire fire detection method described above can be executed. Alternatively, in other embodiments, the processor 701 can be configured to execute the tire fire detection method by any other appropriate means (e.g., by means of firmware).

[0131] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems-on-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0132] The computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable tire fire detection device, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine, or entirely on the remote machine or server.

[0133] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0134] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0135] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0136] A computing system can include a client and a server. The client and the server are generally far from each other and usually interact through a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, solving the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS (Virtual Private Server) services.

[0137] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is imposed herein.

[0138] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub - combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A tire fire detection method, characterized in that, The method includes: Obtaining driving data of a vehicle in motion, where the driving data includes: vehicle status and vehicle environment; the vehicle status at least includes the tire status of each tire in the vehicle; Uploading the driving data to a server; Receiving the fire detection results of each tire in the vehicle fed back by the server.

2. The method according to claim 1, wherein The tire status of the tire includes at least one of the following: the tire pressure, tire temperature, and wear degree of the tire; the vehicle status further includes: vehicle speed, braking frequency, and braking force; the vehicle environment includes at least one of the following: weather, climate, and road surface friction status.

3. The method according to claim 1, wherein After determining the fire detection results of each tire in the vehicle, it further includes at least one of the following: When the fire detection result is a fire, controlling a display screen to display a fire warning message; Controlling the seat to vibrate; and Controlling or prompting the vehicle to stop driving.

4. The method according to claim 1, wherein The vehicle includes a goods transportation vehicle, and the vehicle status further includes: cargo weight.

5. A method for detecting tire fire, characterized in that, The method includes: Receiving driving data sent by a vehicle, where the driving data includes: vehicle status and vehicle environment; the vehicle status at least includes the tire status of each tire in the vehicle; Determining the fire detection results of each tire in the vehicle according to the driving data; Feeding back the fire detection results to the vehicle.

6. The method according to claim 5, wherein The determining the fire detection results of each tire in the vehicle according to the driving data includes: Inputting the driving data into a pre-trained fire probability detection model for processing to obtain the fire probabilities of each tire output by the fire probability detection model; Determining the fire detection results of each tire according to the fire probabilities of each tire.

7. The method according to claim 6, wherein The fire probability detection model is trained through the following method: Obtaining the driving data of the vehicle and the corresponding tire fire information in multiple fire experiments; Obtaining the driving data of multiple historically on-fire vehicles and the corresponding tire fire information; Generating a training data set according to the driving data, the corresponding tire fire information in each fire experiment, and the driving data and the corresponding tire fire information of each historically on-fire vehicle, where the training data set includes training samples, and the training samples include the driving data of the vehicle and the corresponding tire fire labels; Training the fire probability detection model using the training data set.

8. The method according to claim 5, characterized in that, Before determining the fire detection results of each tire in the vehicle according to the driving data, it further includes: Determining the tire maintenance data of each tire in the vehicle according to the driving data; Determining the service life of each tire according to the tire maintenance data of each tire in the vehicle; Taking the service life of each tire as the tire status of each tire and adding it to the driving data.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the tire fire detection method according to any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a processor to implement the tire fire detection method according to any one of claims 1-8 when executed.

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