CN112036223B - Long-distance driving massage supporting method, service end and front end - Google Patents
Long-distance driving massage supporting method, service end and front end Download PDFInfo
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Abstract
A long-distance driving massage supporting method, a service end and a front end comprise: initializing communication parameters and equipment parameters; receiving audio-video data and gesture duration information, and storing the audio-video data and the gesture duration information as gesture analysis samples; extracting control characteristic information in current control data, constructing a gesture model according to the control characteristic information, and updating the gesture model according to a control analysis sample; acquiring a real-time motion vector, and comparing the real-time motion vector with a gesture analysis sample according to a gesture model to obtain fatigue type information; and acquiring a massage adjustment data set, and sending massage support data according to the massage adjustment data set and the massage support data corresponding to the fatigue type information. The invention solves the technical problems of dependence on manual operation, low intelligent degree, poor applicability, low use safety and lack of flexibility in the prior art.
Description
Technical Field
The invention relates to an upgrade package management method, in particular to a long-distance driving massage supporting method, a service end and a front end.
Background
With the increasing improvement of national living standard, motor vehicles are rapidly popularized in the whole society, the quantity of motor vehicles in China is continuously increased, and people drive and travel are increasingly frequent. In the running process of the vehicle, various vehicles can encounter problems caused by partial limb ischemia and lack of activity due to long-term fixed driving postures such as waist and leg numbness, joint pain and the like when the vehicles are congested on a specific running application scene such as a highway and have long running distance, meanwhile, the spirit of the driver is highly concentrated in the running process, the limbs except hands and elbows can move when the steering wheel is driven, other parts of the body are fixed in the driver seat for a long time, necessary measures such as a safety belt can generate the situation that the blood circulation is not feasible, and the driver seat and cabin space are limited by the occupation of necessary vehicle-mounted equipment such as the steering wheel, an instrument panel and the like, so that the driving comfort of the driver is reduced. How to perfect the vehicle-mounted equipment and improve the comfort and the body blood circulation of the driver becomes an important direction for developing vehicle technology increasingly. Because the existing technology and equipment for relieving the numbness of joints and limbs of the driver of the vehicle are single, the fixing support piece which is mainly prefabricated for manufacturers and the driver support or massage the limbs by adopting temporary tools, the use effect is poor, the operation mode is single, and the use safety is low.
In summary, the device in the vehicle of the conventional technology lacks of adjusting flexibility, relies on operations such as manual pulling, and is not high in applicability, and the manual adjustment of the driver easily leads to the increase of the probability of occurrence of traffic accidents. Driver comfort level adjusting equipment in the prior art generally needs manufacturer prefabrication and installation, and degree of automation is low, and there are the technical problems that rely on manual operation, intelligent degree is low, the suitability is poor, the safety in utilization is low and lack flexibility in the prior art.
Disclosure of Invention
In view of the above drawbacks of the prior art, the present invention aims to provide a long-distance driving massage supporting method, a server side and a front end, which are applied to upgrading of vehicle-mounted equipment, and in order to solve the technical problems of dependence on manual operation, low intelligent degree, poor applicability, low use safety and lack of flexibility in the prior art, the invention provides a long-distance driving massage supporting method, a server side and a front end, and the method comprises the following steps: initializing communication parameters and equipment parameters; acquiring audio-video data and gesture duration information, and processing the audio-video data and the gesture duration information into gesture analysis samples; extracting control characteristic information in the current control data, constructing a gesture model according to the control characteristic information, and updating the gesture model according to a gesture analysis sample; acquiring a real-time motion vector, and comparing the real-time motion vector with a gesture analysis sample according to the updated gesture model to acquire fatigue type information; and acquiring a massage adjustment data set, acquiring massage support data corresponding to the fatigue type information according to the massage adjustment data set, and performing massage support work according to the massage support data.
In one embodiment of the present invention, receiving audio-visual data and gesture duration information, storing the audio-visual data and the gesture duration information as gesture analysis samples, includes: extracting and storing gesture characteristic information according to audio-video data; judging whether the gesture duration information is larger than a preset time threshold value or not; if the gesture feature information is larger than the gesture duration information, gathering gesture feature information and gesture duration information to obtain a gesture analysis sample; otherwise, filtering the current gesture characteristic information and the current gesture duration information, and continuously judging whether the gesture duration information acquired at the next moment is larger than a preset time threshold.
In one embodiment of the present invention, extracting control feature information in current audio-video data, constructing a gesture model according to the control feature information, and updating the gesture model according to a control analysis sample, includes: extracting motion vector data in the image data; converting the motion vector data into feature data, and calculating feature vectors according to the feature data; obtaining model increment information according to the characteristic comparison result; the gesture model is updated according to the model delta information.
In one embodiment of the present invention, obtaining a massage adjustment data set, so as to match massage support data corresponding to fatigue type information, and transmitting the massage support data includes: obtaining a massage adjustment data set from a preset massage database; acquiring posture data and duration data corresponding to each massage support data in the massage adjustment data set; judging whether the massage support data corresponds to the fatigue type information traversal according to the gesture data and the duration data; if so, acquiring and transmitting massage support data corresponding to the fatigue type information; otherwise, the judging step is circularly executed until the massage support data corresponding to the fatigue type information is obtained.
In one embodiment of the present invention, a long-distance driving massage support intelligent server includes: the device comprises an initial module, a sample module, a model updating module, a fatigue type module and a massage data sending module; the initial module is used for initializing the communication parameters and the equipment parameters of the massage supporting equipment; the sample module is used for obtaining audio-video data and gesture duration information, processing the audio-video data and the gesture duration information into gesture analysis samples, and connecting the sample module with the initial module; the model updating module is used for extracting control characteristic information in the current control data, constructing a gesture model according to the control characteristic information, updating the gesture model according to a gesture analysis sample, and connecting the model updating module with the sample module; and the fatigue type module is used for acquiring a real-time motion vector, and comparing the real-time motion vector with the gesture analysis sample according to the updated gesture model to acquire fatigue type information. The fatigue type module is connected with the model updating module; the massage data transmitting module is used for acquiring a massage adjustment data set, acquiring massage supporting data corresponding to the fatigue type information according to the massage adjustment data set, and carrying out massage supporting work according to the massage supporting data, and is connected with the fatigue type module.
In one embodiment of the present invention, a sample module includes: the device comprises a feature extraction module, a feature storage module, a duration judgment module, a sample aggregation module and a data filtering module; the feature extraction module is used for extracting and storing gesture feature information according to the audio-video data; the feature preservation module is used for preserving gesture feature information and is connected with the feature extraction module; the time length judging module is used for judging whether the gesture time length information is larger than a preset time threshold value or not, and is connected with the feature storage module; the sample aggregation module is used for aggregating the gesture characteristic information and the gesture duration information to obtain a gesture analysis sample when the gesture duration information is larger than a preset time threshold value, and the sample aggregation module is connected with the duration judgment module; the data filtering module is used for filtering the current gesture characteristic information and the current gesture duration information when the gesture duration information is not greater than the preset time threshold value, and continuously judging whether the gesture duration information acquired at the next moment is greater than the preset time threshold value or not, and is connected with the duration judging module.
In one embodiment of the present invention, the model updating module includes: the device comprises a vector calculation module, a model construction module, a comparison module, an incremental information module and an updating module; the vector calculation module is used for extracting characteristic data in the audio-video data and calculating characteristic vectors according to the characteristic data; the model construction module is used for constructing a gesture model according to the feature vector, and is connected with the vector calculation module; the comparison module is used for extracting a gesture analysis sample, comparing the gesture analysis sample with the feature vector to obtain a feature comparison result, and is connected with the vector calculation module; the incremental information module is used for obtaining model incremental information according to the characteristic comparison result, and is connected with the comparison module; and the updating module is used for updating the gesture model according to the model increment information and is connected with the increment information module.
In one embodiment of the present invention, a massage data transmission module includes: the device comprises a massage data set module, a gesture duration module, a corresponding judging module, an acquisition and transmission module and a judging and circulating module; the massage data set module is used for acquiring a massage adjustment data set from a preset massage database; the gesture duration module is used for acquiring gesture data and duration data corresponding to each massage supporting data in the massage adjustment data set, and is connected with the massage data set module; the corresponding judging module is used for judging whether the massage support data corresponds to the fatigue type information traversal according to the gesture data and the duration data, and is connected with the gesture duration module; the acquisition and transmission module is used for acquiring and transmitting the current massage support data when the massage support data corresponds to the fatigue type information traversal, and is connected with the corresponding judgment module; and the judging and circulating module is used for circularly executing the judging steps until the massage supporting data is obtained when the massage supporting data and the fatigue type information traversal are not corresponding, and is connected with the corresponding judging module.
In one embodiment of the invention, the method for realizing the front end of the intelligent massage support for long-distance driving comprises the following steps: receiving processing trigger information, and starting audio and video acquisition equipment according to the processing trigger information; acquiring audio and video signals in real time by audio and video acquisition equipment; extracting audio-video data according to the audio-video signals, and acquiring gesture duration information; sending audio-video data and gesture duration information to a server; and receiving the massage supporting data, and controlling the servo motor to drive the massage supporting part according to the massage supporting data.
In one embodiment of the present invention, a long distance driving massage support front end comprises: the device comprises an initial module, a sample module, a model updating module, a fatigue type module and a massage data sending module; the receiving module is used for receiving the processing trigger information and starting the audio-video acquisition equipment according to the processing trigger information; the acquisition module is used for acquiring audio and video signals in real time by audio and video acquisition equipment; the data duration acquisition module is used for extracting audio-video data according to the audio-video signals and acquiring gesture duration information, and is connected with the acquisition module; the data transmission module is used for transmitting audio-video data and gesture duration information to the server, and is connected with the acquisition module and the data duration acquisition module; the massage drive control module is used for receiving the massage support data and controlling the servo motor to drive the massage support component according to the massage support data.
As described above, the long-distance driving massage supporting method, the service end and the front end provided by the invention have the following beneficial effects: the long-distance driving massage supporting method, the service end and the front end provided by the invention avoid the technical problems of dependence on manual operation, low intelligent degree, poor applicability, low use safety and lack of flexibility in the prior art. The long-distance driving massage supporting method, the service end and the front end provided by the invention avoid the condition that the existing technology and equipment for relieving the joint and limb numbness of the driver of the vehicle are single, improve the use effect of massage and supporting functions, adopt an automatic control operation mode, avoid excessively depending on a manual switch when the driver uses the vehicle, and improve the use safety. According to the invention, the flexibility is dynamically adjusted according to the sound control information and the video data acquired in real time, and the system is not dependent on manual pulling and other operations, so that the applicability of the system is improved. The automation degree of the system is improved.
In summary, the invention solves the technical problems of dependence on manual operation, low intelligent degree, poor applicability, low use safety and lack of flexibility in the prior art.
Drawings
Fig. 1 shows a schematic diagram of the steps of the intelligent massage supporting method for long distance driving of the present invention.
Fig. 2 is a flowchart showing step S2 in fig. 1 in an embodiment.
Fig. 3 is a flowchart showing the step S3 in fig. 1 in an embodiment.
Fig. 4 is a flowchart showing step S5 in fig. 1 in an embodiment.
Fig. 5 shows a schematic diagram of a long-distance driving intelligent massage support service end module according to the present invention.
Fig. 6 is a schematic diagram of a specific module of the sample module in fig. 5 in an embodiment.
FIG. 7 is a schematic diagram of the model update module of FIG. 5 in one embodiment.
Fig. 8 is a schematic diagram of a specific module of the massage data transmission module in fig. 5 in an embodiment.
Fig. 9 shows a schematic diagram of the implementation method of the intelligent massaging support front end for long distance driving.
Fig. 10 shows a schematic diagram of a front end module of the intelligent massaging support for long distance driving of the present invention.
Description of element reference numerals
1. Intelligent service end for long-distance driving massage support
11. Initial module
12. Sample module
13. Model updating module
14. Fatigue type module
15. Massage data transmitting module
121. Feature extraction module
122. Feature preservation module
123. Duration judging module
124. Sample aggregation module
125. Data filtering module
131. Vector calculation module
132. Model building module
133. Contrast module
134. Incremental information module
135. Update module
151. Massage data set module
152. Gesture duration module
153. Correspondence judging module
154. Acquisition and transmission module
155. Judgment circulation module
Front end of 1' long-distance driving massage support
11' initial module
12' sample module
13' model update module
14' fatigue type module
15' massage data transmitting module
Description of step reference numerals
FIGS. 1 S1 to S3
FIGS. 2S 21 to S25
FIGS. 3S 31 to S35
FIGS. 4S 51 to S55
FIGS. 9 S1 'to S5'
Detailed Description
Further advantages and effects of the present invention will become apparent to those skilled in the art from the disclosure of the present invention, which is described by the following specific examples.
Referring to fig. 1 to 10, it should be understood that the structures shown in the drawings are only for understanding and reading by those skilled in the art, and are not intended to limit the applicable scope of the present invention, and that any structural modifications, proportional changes or size adjustments should fall within the scope of the present invention without affecting the efficacy and achievement of the present invention. Also, the terms such as "upper," "lower," "left," "right," "middle," and "a" and the like recited in the present specification are merely for descriptive purposes and are not intended to limit the scope of the invention, but are intended to provide relative positional changes or modifications without materially altering the technical context in which the invention may be practiced.
Referring to fig. 1, a schematic diagram of steps of the long-distance driving intelligent massage supporting method of the present invention is shown, and as shown in fig. 1, the long-distance driving intelligent massage supporting method includes:
s1, initializing communication parameters and equipment parameters, initializing a camera, presetting information processing logic, automatically performing installation detection and setting by a system, and initializing hardware equipment such as the camera, a sensor and a storage disk;
s2, obtaining audio-video data and gesture duration information, processing the audio-video data and the gesture duration information into gesture analysis samples, and optionally, collecting image information by a camera, extracting single-frame picture information in the image information and storing the single-frame picture information as the gesture analysis samples;
s3, extracting control characteristic information in the current control data, constructing a gesture model according to the control characteristic information, updating the gesture model according to a gesture analysis sample, constructing an intelligent analysis model such as a deep neural network model and the like according to the gesture and action characteristic information contained in the picture information to serve as the gesture model, and training the gesture model by using the gesture analysis sample;
s4, acquiring a real-time motion vector, comparing the real-time motion vector with a gesture analysis sample according to the updated gesture model to acquire fatigue type information, acquiring the real-time motion vector, taking each component of the real-time motion vector as input data of the gesture model to acquire various characteristic information of the real-time motion vector, and optionally, summarizing the information into the fatigue type information;
s5, a massage adjustment data set is obtained, massage supporting data corresponding to the fatigue type information is obtained according to the massage adjustment data set, and massage supporting work is carried out according to the massage supporting data, and optionally, massage control data aiming at all parts of the body of a driver are stored in the massage adjustment data set, and corresponding massage control data are called according to the fatigue type information so as to realize massage according to real-time requirements of the driver.
Referring to fig. 2, which is a specific flowchart of step S2 in fig. 1 in an embodiment, as shown in fig. 2, step S2 of receiving audio-video data and gesture duration information, and storing the audio-video data and the gesture duration information as gesture analysis samples includes:
s21, extracting gesture characteristic information according to audio-video data, wherein optionally, the video data comprises voice control instruction data of a driver, and the control instruction data comprises various gesture data of the driver;
s22, saving posture characteristic information, wherein the posture characteristic information comprises posture characteristic information such as sedentary judgment data, waist compression judgment data, leg compression judgment data and the like, and is used for judging real-time requirements of a driver on automatic massage;
s23, judging whether the gesture duration information is larger than a preset time threshold, optionally, controlling the preset time threshold through self experience by voice input so as to adapt to the specific conditions of different drivers, and when the time for keeping a specific gesture feature of the driver reaches the preset time threshold, further acquiring the position to be massaged corresponding to the gesture feature;
s24, if the gesture feature information is larger than the time-out data, gathering the gesture feature information and the gesture duration information to obtain a gesture analysis sample, and collecting gesture feature information corresponding to each gesture and timeout data corresponding to the gesture features as the gesture analysis sample;
s25, otherwise, filtering the current gesture characteristic information and the current gesture duration information, and continuously judging whether the gesture duration information acquired at the next moment is larger than a preset time threshold.
Referring to fig. 3, which is a specific flowchart of step S3 in fig. 1 in an embodiment, as shown in fig. 3, step S3 extracts control feature information in current audio-video data, constructs a gesture model according to the control feature information, and updates the gesture model according to a control analysis sample, including:
s31, extracting motion vector data in the image data, optionally, converting the received audio-video data into data information and serializing the data information to obtain a feature sequence, and normalizing the hash feature data in the feature sequence into feature vectors through each gesture feature attribute;
s32, constructing a gesture model according to the feature vector, and performing deep learning of the gesture of the driver according to the gesture analysis sample of the driver to obtain a result set, action features, action maintaining features and the like of the driver;
s33, extracting a gesture analysis sample, comparing the gesture analysis sample with the feature vector to obtain a feature comparison result, and taking each component of the real-time motion vector as input data of a gesture model to obtain various feature information of the real-time motion vector;
s34, obtaining model increment information according to the characteristic comparison result;
and S35, updating the gesture model according to the model increment information.
Referring to fig. 4, which is a specific flowchart of step S5 in fig. 1 in an embodiment, as shown in fig. 4, step S5 is to obtain a massage adjustment data set, and send massage support data according to the massage support data corresponding to the fatigue type information, where the sending massage support data includes:
s51, a massage adjustment data set is obtained from a preset massage database, wherein the massage database contains massage mode data and evaluation rate data aiming at uncomfortable feeling such as hemp and the like at different parts generated by different postures;
s52, acquiring posture data and duration data corresponding to each massage support data in the massage adjustment data set, wherein different degrees of numbness or pain can be caused to different parts of a driver due to different postures and different holding time of the same posture, and the massage data corresponding to the parts can be used for determining a support mode and amplitude frequency data of massage and support through experiments at a background of a service end;
s53, judging whether the massage support data corresponds to the fatigue type information traversal according to the gesture data and the duration data;
s54, if the information is corresponding to the fatigue type information, massage support data corresponding to the fatigue type information is acquired and sent, and optionally, the massage support data can be sent from a service end to a support part and a massage part at the front end control front end through a wireless network to support limbs of a driver and intelligently massage the driver;
and S55, otherwise, the judging step is circularly executed until massage support data corresponding to the fatigue type information is obtained.
Referring to fig. 5, a schematic diagram of a long-distance driving intelligent massage support service end module according to the present invention is shown, as shown in fig. 4, a long-distance driving intelligent massage support service end 1 includes: an initial module 11, a sample module 12, a model update module 13, a fatigue type module 14, and a massage data transmission module 15; the initial module 11 is used for initializing communication parameters and equipment parameters, initializing a camera, presetting information processing logic, automatically performing installation detection and setting by a system, and initializing hardware equipment such as the camera, a sensor, a storage disk and the like; the sample module 12 is configured to obtain audio-video data and gesture duration information, process the audio-video data and the gesture duration information into gesture analysis samples, and optionally, collect image information by using a camera, extract single-frame picture information in the image information and store the single-frame picture information as the gesture analysis samples, where the sample module 12 is connected with the initial module 11; a model updating module 13, configured to extract control feature information in current control data, construct a gesture model according to the control feature information, update the gesture model according to a gesture analysis sample, construct an intelligent analysis model such as a deep neural network model according to gesture and motion feature information included in picture information as a gesture model, and train the gesture model using the gesture analysis sample, where the model updating module 13 is connected to the sample module 12; the fatigue type module 14 is configured to obtain a real-time motion vector, compare the real-time motion vector with a gesture analysis sample according to a gesture model to obtain fatigue type information, obtain the real-time motion vector, and use each component of the real-time motion vector as input data of the gesture model to obtain various feature information of the real-time motion vector, and optionally, aggregate the information into fatigue type information, where the fatigue type module 14 is connected with the model update module 13; the massage data sending module 15 is configured to obtain a massage adjustment data set, and send massage support data according to the massage support data corresponding to the fatigue type information, and optionally, the massage adjustment data set stores massage control data for each part of the body of the driver, and according to the fatigue type information, the corresponding massage control data is called to implement massage according to real-time requirements of the driver, and the massage data sending module 15 is connected with the fatigue type module 14.
Referring to fig. 6, a schematic diagram of a sample module in fig. 5 is shown, and as shown in fig. 6, the sample module 12 includes: a feature extraction module 121, a feature preservation module 122, a duration judgment module 123, a sample aggregation module 124, and a data filtering module 125; the feature extraction module 121 is configured to extract gesture feature information according to audio-video data, and optionally, the video data includes voice control instruction data of the driver, where the control instruction data includes various gesture data of the driver; the feature preservation module 122 is configured to preserve pose feature information, where the pose feature information includes pose feature information such as sedentary determination data, lumbar compression determination data, leg compression determination data, etc., and is configured to determine a real-time requirement of a driver for automatic massage, and the feature preservation module 122 is connected to the feature extraction module 121; the duration judging module 123 is configured to judge whether the gesture duration information is greater than a preset time threshold, optionally, the preset time threshold may be controlled through voice input through self experience to adapt to specific situations of different drivers, when the time of the driver maintaining a specific gesture feature reaches the preset time threshold, a part to be massaged corresponding to the gesture feature may be further acquired, and the duration judging module 123 is connected with the feature saving module 122; the sample aggregation module 124 is configured to aggregate the gesture feature information and the gesture duration information to obtain a gesture analysis sample when the gesture duration information is greater than a preset time threshold, aggregate the gesture feature information corresponding to each gesture and the timeout data corresponding to the gesture features into the gesture analysis sample, and connect the sample aggregation module 124 with the duration judgment module 123; the data filtering module 125 is configured to filter the current gesture feature information and the gesture duration information when the gesture duration information is not greater than the preset time threshold, where the data filtering module 125 is connected to the duration judging module 123.
Referring to fig. 7, a schematic diagram of a specific module of the model update module in fig. 5 in one embodiment is shown, and as shown in fig. 7, the model update module 13 includes: a vector calculation module 131, a model construction module 132, a comparison module 133, an incremental information module 134, and an update module 135; the vector calculation module 131 is configured to extract feature data in audio-video data, and calculate feature vectors according to the feature data, and optionally, convert received audio-video data into data information and serialize the data information to obtain feature sequences, and normalize hashed feature data in the feature sequences into feature vectors through each gesture feature attribute; the model building module 132 is configured to build a gesture model according to the feature vector, perform driver gesture deep learning according to the driver gesture analysis sample to obtain a result set, a driver action feature, an action retention feature, and the like, and the model building module 132 is connected to the vector calculating module 131; the comparison module 133 is configured to extract a gesture analysis sample, compare the gesture analysis sample with a feature vector to obtain a feature comparison result, and use each component of the real-time motion vector as input data of the gesture model to obtain various feature information of the real-time motion vector, where the comparison module 133 is connected with the vector calculation module 131; the incremental information module 134 is configured to obtain model incremental information according to the feature comparison result, where the incremental information module 134 is connected to the comparison module 133; and the updating module 135 is used for updating the gesture model according to the model increment information, and the updating module 135 is connected with the increment information module 134.
Referring to fig. 8, a schematic diagram of a specific module of the massage data transmission module in fig. 5 in an embodiment is shown, and as shown in fig. 8, the massage data transmission module 15 includes: a massage data set module 151, a gesture duration module 152, a correspondence judgment module 153, an acquisition transmission module 154, and a judgment circulation module 155; the massage data set module 151 is configured to obtain a massage adjustment data set from a preset massage database, where the massage database includes massage mode data and evaluation rate data for discomfort such as hemp and the like at different positions generated by different postures; the gesture duration module 152 is configured to obtain gesture data and duration data corresponding to each massage support data in the massage adjustment data set, because different gestures and different time for maintaining the same gesture may cause different degrees of numbness or pain to different parts of the driver, the massage data corresponding to the parts may determine the support mode and amplitude frequency data of the massage and support through experiments in the background of the server, and the gesture duration module 152 is connected with the massage data set module 151; the correspondence judging module 153 is configured to judge whether the massage support data corresponds to the fatigue type information traversal according to the gesture data and the duration data, and the correspondence judging module 153 is connected to the gesture duration module 152; the acquiring and transmitting module 154 is configured to acquire and transmit current massage support data when the massage support data corresponds to the fatigue type information traversal, and optionally, the massage support data may be transmitted from the service end to the support component and the massage component at the front end control front end through the wireless network to support the limbs of the driver and perform intelligent massage, where the acquiring and transmitting module 154 is connected to the corresponding judging module 153; and a judging and circulating module 155, configured to, when the massage support data and the fatigue type information traversal do not correspond, circulate and execute the foregoing judging steps until the massage support data is obtained, where the judging and circulating module 155 is connected to the corresponding judging module 153.
Referring to fig. 9, a schematic step diagram of a method for implementing a front end of a long-distance driving intelligent massage support according to the present invention is shown, and as shown in fig. 9, the method for implementing a front end of a long-distance driving intelligent massage support includes:
s1', receiving processing trigger information, and starting audio and video acquisition equipment according to the processing trigger information, wherein the video acquisition equipment can select an industrial camera and a commonly used mobile equipment camera (connected with a vehicle machine system through an expansion interface);
s2', acquiring audio and video signals in real time by using audio and video acquisition equipment, wherein the sound control acquisition equipment can use a portable recording sound tube;
s3', extracting audio and video data according to the audio and video signals, and acquiring gesture duration information, wherein the gesture duration information can be acquired by combining with the system time of the vehicle;
s4', sending the audio-video data and the gesture duration information to a server, and optionally, transmitting the audio-video data and the gesture duration information in a message transmission mode;
s5', receiving massage support data, controlling a servo motor to drive a massage support component according to the massage support data, wherein the support component can be a telescopic support component fixedly arranged on a driver seat, dynamically supporting the waist and the legs of a driver, and the telescopic support component can be driven by a hydraulic rod or a screw rod.
Referring to fig. 10, a schematic diagram of a front end module of a long-distance driving intelligent massage support according to the present invention is shown, as shown in fig. 10, a front end 1' of a long-distance driving intelligent massage support includes: an initial module 11', a sample module 12', a model update module 13', a fatigue type module 14', and a massage data transmission module 15'; the receiving module 11' is used for receiving the processing trigger information, starting the audio-video acquisition equipment according to the processing trigger information, wherein the image acquisition equipment can select an industrial camera and a commonly used mobile equipment camera (connected with a vehicle machine system through an expansion interface); the acquisition module 12' is configured to acquire audio and video signals in real time by using an audio and video acquisition device, where the sound control acquisition device can use a portable recording sound tube; the data duration acquisition module 13' is used for extracting audio-video data according to audio-video signals and acquiring gesture duration information, and the gesture duration information can be acquired by combining with the system time of the vehicle, and the data duration acquisition module 13' is connected with the acquisition module 12 '; the data transmission module 14' is used for transmitting the audio-video data and the gesture duration information to the server, the data transmission module is connected with the acquisition module, and optionally, the audio-video data and the gesture duration information are transmitted in a message transmission mode, and the data transmission module 14' is connected with the data duration acquisition module 13 '; the massage drive control module 15 'is configured to receive massage support data, control the servo motor to drive the massage support member according to the massage support data, the support member may be a telescopic support member fixedly mounted on the driver's seat, dynamically support the waist and the legs of the driver, and the telescopic support member may be driven by a hydraulic rod or a screw rod.
In summary, the long-distance driving massage supporting method, the service end and the front end provided by the invention have the following beneficial effects: the long-distance driving massage supporting method, the service end and the front end provided by the invention avoid the technical problems of dependence on manual operation, low intelligent degree, poor applicability, low use safety and lack of flexibility in the prior art. The long-distance driving massage supporting method, the service end and the front end provided by the invention avoid the condition that the existing technology and equipment for relieving the joint and limb numbness of the driver of the vehicle are single, improve the use effect of massage and supporting functions, adopt an automatic control operation mode, avoid excessively depending on a manual switch when the driver uses the vehicle, and improve the use safety. According to the invention, the flexibility is dynamically adjusted according to the sound control information and the video data acquired in real time, and the system is not dependent on manual pulling and other operations, so that the applicability of the system is improved. The invention improves the automation degree of the system, solves the technical problems of dependence on manual operation, low intelligent degree, poor applicability, low use safety and lack of flexibility in the prior art, and has high commercial value and practicability.
Claims (6)
1. A long-distance driving massage supporting method is characterized in that,
comprising the following steps:
initializing communication parameters and equipment parameters of the massage supporting equipment;
acquiring audio-video data and gesture duration information, and processing the audio-video data and the gesture duration information into gesture analysis samples;
extracting control characteristic information in current control data, constructing a gesture model according to the control characteristic information, and updating the gesture model according to the gesture analysis sample;
acquiring a real-time motion vector, and comparing the real-time motion vector with the gesture analysis sample according to the updated gesture model to acquire fatigue type information;
acquiring a massage adjustment data set, acquiring massage support data corresponding to the fatigue type information according to the massage adjustment data set, transmitting the massage support data, and performing massage support work according to the massage support data;
extracting control characteristic information in current control data, constructing a gesture model according to the control characteristic information, and updating the gesture model according to the gesture analysis sample, wherein the method comprises the following steps:
extracting motion vector data in the audio-video data;
converting the motion vector data into feature data, and calculating feature vectors according to the feature data;
constructing the gesture model according to the feature vector;
extracting the gesture analysis sample, and comparing the gesture analysis sample with the feature vector to obtain a feature comparison result;
obtaining model increment information according to the characteristic comparison result;
and updating the gesture model according to the model increment information.
2. The method of claim 1, wherein the step of determining the position of the substrate comprises,
the obtaining audio-visual data and gesture duration information, processing the audio-visual data and the gesture duration information into gesture analysis samples, includes:
extracting and storing gesture characteristic information according to the audio-video data;
judging whether the gesture duration information is larger than a preset time threshold value or not;
if the gesture feature information is larger than the gesture duration information, aggregating the gesture feature information and the gesture duration information to obtain a gesture analysis sample;
otherwise, filtering the current gesture characteristic information and the current gesture duration information, and continuously judging whether the gesture duration information acquired at the next moment is larger than a preset time threshold.
3. The method of claim 1, wherein the step of determining the position of the substrate comprises,
the step of obtaining a massage adjustment data set, obtaining massage support data corresponding to the fatigue type information according to the massage adjustment data set, and sending the massage support data comprises the following steps:
obtaining a massage adjustment data set from a preset massage database;
acquiring posture data and duration data corresponding to each massage support data in the massage adjustment data set;
judging whether the massage support data corresponds to the fatigue type information according to the posture data and the duration data;
if so, acquiring and transmitting massage support data corresponding to the fatigue type information;
otherwise, the judging step is circularly executed until the massage supporting data corresponding to the fatigue type information is obtained.
4. An intelligent service end for long-distance driving massage support is characterized in that,
comprising the following steps:
the device comprises an initial module, a sample module, a model updating module, a fatigue type module and a massage data sending module;
the initial module is used for initializing communication parameters and equipment parameters of the massage supporting equipment;
the sample module is used for obtaining audio-video data and gesture duration information and processing the audio-video data and the gesture duration information into gesture analysis samples;
the model updating module is used for extracting control characteristic information in current control data, constructing a gesture model according to the control characteristic information, and updating the gesture model according to the gesture analysis sample;
the fatigue type module is used for acquiring a real-time motion vector, and comparing the real-time motion vector with the gesture analysis sample according to the updated gesture model to acquire fatigue type information;
the massage data transmitting module is used for transmitting massage support data, and the massage support data is obtained according to a massage adjustment data set and corresponds to the fatigue type information;
the model updating module comprises: the device comprises a vector calculation module, a model construction module, a comparison module, an incremental information module and an updating module;
the vector calculation module is used for extracting motion vector data in the audio-video data;
the model construction module is used for converting the motion vector data into characteristic data and calculating characteristic vectors according to the characteristic data;
the comparison module is used for extracting the gesture analysis sample and comparing the gesture analysis sample with the feature vector to obtain a feature comparison result;
the incremental information module is used for obtaining model incremental information according to the characteristic comparison result;
and the updating module is used for updating the gesture model according to the model increment information.
5. The intelligent server according to claim 4, wherein,
the sample module comprises: the device comprises a feature extraction module, a duration judgment module, a sample aggregation module and a data filtering module;
the feature extraction module is used for extracting and storing gesture feature information according to the audio-video data;
the duration judging module is used for judging whether the gesture duration information is larger than a preset time threshold value or not;
the sample aggregation module is used for aggregating the gesture characteristic information and the gesture duration information to obtain a gesture analysis sample when the gesture duration information is larger than a preset time threshold;
the data filtering module is used for filtering the current gesture characteristic information and the current gesture duration information when the gesture duration information is not greater than a preset time threshold value, and continuously judging whether the gesture duration information acquired at the next moment is greater than the preset time threshold value.
6. The intelligent server according to claim 4, wherein,
the massage data transmission module comprises: the device comprises a massage data set module, a gesture duration module, a corresponding judging module, an acquisition and transmission module and a judging and circulating module;
the massage data set module is used for acquiring a massage adjustment data set from a preset massage database;
the gesture duration module is used for acquiring gesture data and duration data corresponding to each massage supporting data in the massage adjustment data set;
the correspondence judging module is used for judging whether the massage support data corresponds to the fatigue type information traversal according to the gesture data and the duration data;
the acquisition and transmission module is used for acquiring and transmitting the massage support data corresponding to the fatigue type information when the massage support data corresponds to the fatigue type information in a traversing way;
and the judging and circulating module is used for circularly executing the judging steps until the massage support data corresponding to the fatigue type information is obtained when the massage support data does not correspond to the fatigue type information traversal.
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