CN117641065A - Self-adaptive image transmission method of intelligent network monitoring sensor - Google Patents
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Abstract
The invention discloses a self-adaptive image transmission method of an intelligent network monitoring sensor, belonging to the technical field of image transmission; step S1, network condition data are obtained in real time through an intelligent network monitoring sensor; step S2, storing and calculating an average value of the network condition data, and comparing the average value with a set threshold value of the intelligent network monitoring sensor to obtain a network state corresponding to the network condition data; step S3, self-adaptively adjusting image data according to the network state to formulate a transmission sequence; s4, preprocessing and optimizing the image data to obtain an image to be transmitted; and S5, carrying out self-adaptive transmission on the image to be transmitted according to the transmission sequence. The beneficial effects of the technical scheme are as follows: network conditions can be monitored in real time, an image transmission strategy can be intelligently adjusted, and quality, stability and instantaneity of image transmission in palm ultrasonic equipment are guaranteed.
Description
Technical Field
The invention relates to the technical field of image transmission, in particular to a self-adaptive image transmission method of an intelligent network monitoring sensor.
Background
With the rapid development of mobile medical technology, palm ultrasonic equipment gradually becomes an important tool for medical diagnosis and monitoring, however, under different network environments, the real-time performance and the image quality of image transmission are challenged, at present, a network sensor is integrated on the palm ultrasonic equipment, an image transmission method is usually a fixed transmission strategy, self-adaptive adjustment cannot be carried out according to the change of the network environment or the application requirement, and the accuracy of clinical application is influenced.
In the prior art, the sensor technology and the image transmission method often cannot adapt to the image transmission requirements under different network conditions, and the traditional image transmission method is too static and cannot be dynamically adjusted according to the actual network conditions, so that the image transmission quality is unstable.
Disclosure of Invention
The invention aims to provide a self-adaptive image transmission method of an intelligent network monitoring sensor, which solves the technical problems;
an adaptive image transmission method of an intelligent network monitoring sensor comprises the following steps,
step S1, acquiring network condition data in real time through an intelligent network monitoring sensor;
step S2, storing and calculating an average value of the network condition data, and comparing the average value with a set threshold value of the intelligent network monitoring sensor to obtain a network state corresponding to the network condition data;
step S3, self-adaptively adjusting image data according to the network state to formulate a transmission sequence;
s4, preprocessing and optimizing the image data to obtain an image to be transmitted;
and S5, carrying out self-adaptive transmission on the image to be transmitted according to the transmission sequence.
Preferably, in step S1, the intelligent network monitoring sensor monitors and obtains the network condition data every other set period of time;
the network condition data includes network bandwidth, round trip delay and packet loss rate.
Preferably, step S2 comprises,
step S21, storing the network condition data through a data storage module;
step S22, reading the data storage module and calculating the average value of the network condition data;
step S23, comparing the average value with the set threshold value of the intelligent network monitoring sensor, if the average value is greater than the set threshold value, the intelligent network monitoring sensor is in a first network state, if the average value is equal to the set threshold value, the intelligent network monitoring sensor is in a second network state, and if the average value is less than the set threshold value, the intelligent network monitoring sensor is in a third network state.
Preferably, the image data in step S3 includes an image compression rate, an image resolution, and a transmission priority.
Preferably, the transmission sequence includes,
a first priority transmission corresponding to the first network state;
a second priority transmission corresponding to the second network state;
and transmitting a third priority, wherein the third priority corresponds to the third network state.
Preferably, step S4 comprises,
step S41, denoising and smoothing the image data to obtain preprocessed image data;
step S42, compressing the preprocessed image data according to the transmission sequence to obtain image data to be optimized;
and step S43, detecting whether the image data to be optimized is missing a data segment according to the network condition data, if so, retransmitting the missing data segment and then executing step S5, and if not, directly executing step S5.
Preferably, the adaptive transmission in step S5 includes a real-time transmission for immediate response and a buffered transmission for temporary storage of data.
Preferably, the network bandwidth is controlled by a timer to record the time of packet transmission and reception.
Preferably, the round trip delay is the difference in time between the intelligent network monitoring sensor sending a message to a target server.
Preferably, the intelligent network monitoring sensor is arranged on a probe of the palm ultrasonic equipment.
The beneficial effects of the invention are as follows: by adopting the technical scheme, the network condition can be monitored in real time, the image transmission strategy can be intelligently adjusted, and the quality, stability and instantaneity of image transmission in the palm ultrasonic equipment are ensured.
Drawings
FIG. 1 is a step diagram of an adaptive image transmission method of an intelligent network monitoring sensor of the present invention;
FIG. 2 is a schematic diagram of step S2 of the present invention;
fig. 3 is a schematic diagram of step S4 of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
The invention is further described below with reference to the drawings and specific examples, which are not intended to be limiting.
An adaptive image transmission method of an intelligent network monitoring sensor, as shown in fig. 1, comprises,
step S1, acquiring network condition data in real time through an intelligent network monitoring sensor;
step S2, storing and calculating an average value of the network condition data, and comparing the average value with a set threshold value of the intelligent network monitoring sensor to obtain a network state corresponding to the network condition data;
step S3, self-adaptively adjusting image data according to the network state to formulate a transmission sequence;
s4, preprocessing and optimizing the image data to obtain an image to be transmitted;
and S5, carrying out self-adaptive transmission on the image to be transmitted according to the transmission sequence.
The invention provides a self-adaptive image transmission method of an intelligent network monitoring sensor, which is mainly used for image transmission, can monitor network conditions in real time, and intelligently adjusts an image transmission strategy according to the current network conditions so as to ensure that the image transmission in palm ultrasonic equipment has stable instantaneity and ensure the quality of images.
In a preferred embodiment, in step S1, the intelligent network monitoring sensor monitors and obtains network condition data every other set period of time;
the network condition data includes network bandwidth, round trip delay, and packet loss rate.
Specifically, the intelligent network monitoring sensor integrates a bandwidth measuring module, a delay testing module and a packet loss rate monitoring module, and is used for periodically measuring network bandwidth, round trip delay and packet loss rate respectively so as to acquire real-time network condition data.
Further specifically, the bandwidth measurement module integrates a network interface module (Wi-Fi module) for data transmission on hardware, adopts a microcontroller or an embedded processor, and is equipped with a timer for controlling a transmission time interval and GPIO (general purpose input/output); a bandwidth measurement software program is developed on the software, the program firstly sets the size of a transmitted test data packet, then periodically transmits the data packet to a server, uses a timer to perform interval control, and records the time of data packet transmission and reception.
More specifically, the delay test module also uses a microcontroller or embedded processor in hardware as a network interface module, introducing a timer to measure round trip time; programming a software program for delay test on the software, performing Ping test on the sensor, and sending: ICMP Echo Request to the destination server, the transmission and reception times are recorded, and the Round-Trip Time (RTT), i.e. the difference between the transmission Time and the reception Time, is calculated.
Still more specifically, the packet loss rate monitoring module needs a network interface module on hardware, i.e. a microcontroller or an embedded processor, develops a software program for monitoring the packet loss rate on software, and the sensor sends a large number of test data packets to the server, records the number of the sent and received data packets, and calculates the packet loss rate by comparing the number of the sent data packets with the number of the received data packets.
In a preferred embodiment, as shown in fig. 2, step S2 includes,
step S21, storing network condition data through a data storage module;
step S22, reading a data storage module and calculating the average value of network condition data;
step S23, comparing the average value with a set threshold value of the intelligent network monitoring sensor, if the average value is larger than the set threshold value, the intelligent network monitoring sensor is in a first network state, if the average value is equal to the set threshold value, the intelligent network monitoring sensor is in a second network state, and if the average value is smaller than the set threshold value, the intelligent network monitoring sensor is in a third network state.
Specifically, a data storage module is integrated in the sensor and is used for storing network condition data, including bandwidth measurement results, delay test results and packet loss rate data; and then reading network condition data, and calculating the average value of the multiple bandwidth measurement, the delay test module Ping test and the packet loss rate monitoring result so as to obtain more accurate network condition data.
Further specifically, according to the measurement results of the continuous multiple times, calculating the fluctuation of the network condition, for example, calculating the standard deviation of the bandwidth to measure the fluctuation of the bandwidth; the threshold value of network performance evaluation is preset in the sensor, and can be based on actual requirements, such as minimum bandwidth requirements, maximum delay tolerance and the like; and comparing the average processed network condition data with a set threshold value, and guiding the adjustment of a subsequent image transmission strategy by the obtained network state.
In a preferred embodiment, the image data in step S3 includes an image compression rate, an image resolution, and a transmission priority.
Specifically, an adaptive image transmission strategy is formulated based on the network state, and parameters such as an image compression rate, resolution, transmission priority and the like are determined so as to optimize the image transmission effect.
Further specifically, step S3 includes:
a parameter adjustment module that will adjust parameters of the image transmission, such as image compression rate, resolution, and transmission priority, according to the network status; transmission policy settings including transmission parameter settings under various network conditions; depending on the network state, the transmission policy formulation module will select the appropriate policy.
Algorithm logic adjusts parameters according to network conditions, for example, selecting image compression rate based on bandwidth and delay, or reducing image resolution in case of high packet loss rate.
The compression rate is set, the image compression rate is adjusted to be a proper level according to the network state, a lower compression rate can be selected to maintain the image quality under the better network condition, and the compression rate can be moderately increased to reduce the bandwidth required for transmission under the worse network condition.
Resolution adjustment, which can adjust image resolution in due time according to network state, and can reduce resolution when network quality is poor, so as to reduce data volume and transmission time.
Transmission priority setting, which sets transmission priorities for different images according to network states, for example, for an image with strong immediacy, transmission may be prioritized, and for an image with lower priority, buffer transmission may be performed.
More specifically, the method can realize dynamic adjustment of parameters, the transmission strategy making module is embedded into the transmission control process to update the transmission parameters according to network conditions in real time, the sensor can evaluate network conditions regularly, and then the transmission strategy is adjusted according to the latest evaluation result.
In a preferred embodiment, the transmission sequence comprises,
first priority transmission corresponding to a first network state;
a second priority transmission corresponding to a second network state;
and transmitting the third priority, wherein the third priority corresponds to a third network state.
Specifically, the first priority transmission is a high-quality transmission strategy, and the corresponding network state is good; the second priority transmission is balanced transmission strategy, corresponding to network state and the like; and the third priority transmission is a buffer transmission strategy, and the corresponding network state is unstable.
Further specifically, the tolerance of the transmission of the real-time ultrasonic image to the packet loss rate is lower, and the set thresholds are respectively: a high bandwidth threshold of 4Mbps, a low delay threshold of 50ms, a low packet loss rate threshold of 1%.
In a preferred embodiment, as shown in fig. 3, step S4 includes,
step S41, denoising and smoothing the image data to obtain preprocessed image data;
step S42, compressing the preprocessed image data according to the transmission sequence to obtain the image data to be optimized;
step S43, whether the image data to be optimized lose the data segment is detected according to the network condition data, if yes, the step S5 is executed after the lost data segment is retransmitted, and if no, the step S5 is directly executed.
Specifically, an image data processing module is designed for preprocessing and optimizing an ultrasonic image; an image compression algorithm is applied to ensure that the amount of data is minimized during transmission while maintaining image quality.
Further specifically, an image data receiving module is designed and is responsible for processing the image data received from the sensor; the preprocessing operation utilizes the development of an image preprocessing algorithm, and denoising, enhancement, smoothing and the like are realized based on a digital signal processing technology so as to improve the image quality; the higher the compression rate, the lower the bandwidth required for transmission, but the image quality will be correspondingly degraded.
More specifically, the segmented transmission is needed in the transmission process, the data segmentation is to divide the image data into data segments with proper sizes, and the transmission success rate is improved under the condition of poor network conditions, wherein the data transmission is to transmit the preprocessed and compressed image data segments to the mobile device.
Still further specifically, during the data transmission process, the transmission monitoring module monitors the transmission delay and the packet loss rate in real time; and the data integrity check is carried out at the data receiving end, and whether the lost data segment exists or not is checked according to the monitoring data in the transmission process, and the necessary retransmission is carried out.
In a preferred embodiment, the adaptive transmission in step S5 includes a real-time transmission for immediate response and a buffered transmission for temporary storage of data.
Specifically, the adaptive transmission further comprises transmission queue management and transmission control logic for managing the transmission sequence of the image data; adding image data into a transmission queue according to the transmission priority of the images in proper sequence; and the transmission control logic is responsible for deciding when to start transmitting the image data according to the transmission strategy and the transmission queue.
Further specifically, in the case of good network conditions, the real-time transmission is to immediately start transmitting the image data to a remote server or a mobile device, and in the transmission process, the transmission delay is monitored in real time by recording the sending time and the receiving time; under the condition of poor network conditions, the buffer transmission temporarily stores the image data into the local storage equipment, and waits for the transmission after the network condition is improved, so that the transmission failure in an unstable network environment is avoided.
More specifically, the transmission delay is monitored in the transmission process, the time stamp of sending the image data and the time stamp of receiving the image data are recorded, the difference value between the two is calculated, namely the transmission delay, and whether the current delay is within an acceptable range is judged according to the previous network state; and monitoring the packet loss rate in the transmission process, recording the number of the sent image data packets and the number of the received image data packets, calculating the packet loss rate, and judging whether the current packet loss rate is in an acceptable range according to the previous network state.
Still more specifically, during image data transmission, a transmission check bit is set so that a receiving end can detect errors in the transmission process, if errors or data loss occur in data transmission is detected, a transmission retransmission mechanism is started, and a sensor retransmits the lost data segment to ensure the integrity of the data.
In a preferred embodiment, the network bandwidth is controlled by a timer to record the time of packet transmission and reception; the round trip delay is the difference in time between the intelligent network monitoring sensor sending a message to a target server.
Specifically, the network bandwidth refers to the maximum capacity of the network to transmit data in a unit time, and is generally measured in bits per second (Bps) or bytes per second (Bps), and the control of the network bandwidth may be performed by a timer, and the sending and receiving time of the data packet is recorded, so as to ensure the stable operation of the network.
More specifically, the round trip delay refers to the time required for a packet to be transmitted from a sender to a receiver and then back to the sender, and this time difference can be used to evaluate the performance and stability of the network; in intelligent network monitoring, RTT can reflect real-time conditions of the network, thereby optimizing the network.
The Packet Loss Rate (Packet Loss Rate) refers to the proportion of the data packets which are transmitted from the transmitting end to the receiving end and not successfully received by the receiving end to the total number of the transmitted data packets, and the calculation formula of the Packet Loss Rate is as follows,
packet loss rate = number of lost packets/total number of packets transmitted
The packet loss rate directly affects the transmission efficiency and quality of the network, and if the packet loss rate is too high, the network transmission speed is possibly slow, even normal communication cannot be performed, the stable operation of the network is ensured, and the network performance is improved.
In a preferred embodiment, the intelligent network monitoring sensor is provided on the probe of the palm ultrasound device.
Specifically, the intelligent network monitoring sensing equipment can monitor the working state of the palm ultrasonic equipment in real time, evaluate the network condition, ensure that the image can be adaptively transmitted according to the network state, and ensure the accuracy and stability of the image transmission.
In the first embodiment, the set threshold of the intelligent network monitoring sensor is a high bandwidth threshold of 4Mbps, a low delay threshold of 50ms and a low packet loss rate threshold of 1%, respectively, when the average value of the network condition data is an average bandwidth of 4.5Mbps, an average delay of 45ms and an average packet loss rate of 0.5%, the network condition is determined to be good, the sensor will adjust the transmission strategy, improve the image quality, increase the resolution or reduce the compression rate, so as to utilize the available bandwidth to the maximum extent, and at the same time keep the lower transmission priority; when the average value of the network condition data is the average bandwidth of 4Mbps, the average delay of 50ms and the average packet loss rate of 1%, the network condition is better, the sensor keeps the current transmission strategy, and the stability and quality of image transmission are maintained; when the average value of the network condition data is 3Mbps average bandwidth, 60ms average delay and 2% average packet loss rate, the network condition is determined to be worse, the sensor adjusts the transmission strategy according to the situation, reduces the resolution, increases the compression rate, and adjusts the transmission priority to be medium so as to ensure the stability and instantaneity of image transmission and optimize the image transmission effect to the greatest extent.
In a second embodiment, the image parameters of the high quality transmission strategy include 0.1 image compression rate, 2560x1440 image resolution, high transmission priority; the high-quality transmission strategy is suitable for the condition of good network conditions, has sufficient bandwidth, low delay, less packet loss rate and highest image quality, and is suitable for the scene with higher requirement on image quality in the medical field.
The image parameters of the balanced transmission strategy comprise 0.3 image compression rate, 1920x1080 image resolution and medium transmission priority; the balanced transmission strategy is suitable for the network condition, the bandwidth and delay are in a medium range, the packet loss rate is low, the image quality is high, and meanwhile, the transmission stability can be kept better when the network slightly fluctuates.
The image parameters of the buffer transmission strategy comprise 0.5 image compression rate, 1280x720 image resolution and low transmission priority; the buffer transmission strategy is suitable for the conditions of relatively unstable network conditions, lower bandwidth, higher delay or increased packet loss rate, and the image quality is reduced, but the transmission stability is more important, so that the buffer transmission strategy is suitable for real-time monitoring and diagnosis.
In a third embodiment, the network condition data after the average processing is obtained from the step S2, including an average bandwidth of 4.5Mbps, an average delay of 45ms, and an average packet loss rate of 0.5%, and then compared with a preset threshold, the average bandwidth is higher than a high bandwidth threshold (4 Mbps), and meets the conditions; the average delay is below the low delay threshold (50 ms), eligible; the average packet loss rate is lower than the low packet loss rate threshold (1%), and meets the condition; and finally, selecting a proper transmission strategy according to the network state, obtaining a better network state according to a comparison result, selecting a high-quality transmission strategy, adjusting image parameters, adjusting the image compression rate to 0.1, adjusting the image resolution to 2560x1440, and adjusting the transmission priority to be high.
In the fourth embodiment, the network monitoring sensor of the palm ultrasonic probe performs network condition evaluation every 3 seconds to obtain bandwidth (4.5 Mbps), delay (35 ms) and packet loss rate (1%) data, the sensor starts to transmit high-quality images (1920 x1080 and compression rate 0.2) to the mobile phone, when the network quality is deteriorated, the bandwidth is reduced to 2Mbps, the delay is increased to 80ms, and the packet loss rate is increased to 5%; the sensor increases the compression ratio to 0.3 and reduces the resolution ratio to 1600x900 according to the network evaluation result, and adjusts the transmission priority to be medium, and the mobile phone receives and displays the real-time ultrasonic image transmitted by the sensor; while displaying real-time transmission delay (80 ms) and packet loss rate (5%) in a visual manner, assisting the doctor in viewing the ultrasound image.
In summary, the invention provides a self-adaptive image transmission method of an intelligent network monitoring sensor, which is mainly used for image transmission, and the sensor integrated on a palm ultrasonic probe dynamically adjusts an image transmission strategy according to different network conditions, so that the image transmission effect under different network conditions is ensured, real-time transmission or buffer memory transmission is selected according to the network conditions, the transmission delay and packet loss rate are monitored in real time, the integrity of a received image is ensured, the monitoring accuracy is ensured, and the quality, stability and instantaneity of image transmission in palm ultrasonic equipment are ensured.
The foregoing description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and those skilled in the art should appreciate that all applications are included in the scope of the present invention.
Claims (10)
1. An adaptive image transmission method of an intelligent network monitoring sensor is characterized by comprising the following steps of,
step S1, acquiring network condition data in real time through an intelligent network monitoring sensor;
step S2, storing and calculating an average value of the network condition data, and comparing the average value with a set threshold value of the intelligent network monitoring sensor to obtain a network state corresponding to the network condition data;
step S3, self-adaptively adjusting image data according to the network state to formulate a transmission sequence;
s4, preprocessing and optimizing the image data to obtain an image to be transmitted;
and S5, carrying out self-adaptive transmission on the image to be transmitted according to the transmission sequence.
2. The adaptive image transmission method of an intelligent network monitoring sensor according to claim 1, wherein in step S1, the intelligent network monitoring sensor monitors and obtains the network condition data every a set period of time;
the network condition data includes network bandwidth, round trip delay and packet loss rate.
3. The method for adaptive image transmission of an intelligent network monitoring sensor according to claim 1, wherein step S2 comprises,
step S21, storing the network condition data through a data storage module;
step S22, reading the data storage module and calculating the average value of the network condition data;
step S23, comparing the average value with the set threshold value of the intelligent network monitoring sensor, if the average value is greater than the set threshold value, the intelligent network monitoring sensor is in a first network state, if the average value is equal to the set threshold value, the intelligent network monitoring sensor is in a second network state, and if the average value is less than the set threshold value, the intelligent network monitoring sensor is in a third network state.
4. The adaptive image transmission method of an intelligent network monitoring sensor according to claim 1, wherein the image data in step S3 includes an image compression rate, an image resolution, and a transmission priority.
5. The method for adaptive image transmission of an intelligent network monitoring sensor according to claim 3, wherein the transmission sequence comprises,
a first priority transmission corresponding to the first network state;
a second priority transmission corresponding to the second network state;
and transmitting a third priority, wherein the third priority corresponds to the third network state.
6. The method for adaptive image transmission of an intelligent network monitoring sensor according to claim 1, wherein step S4 comprises,
step S41, denoising and smoothing the image data to obtain preprocessed image data;
step S42, compressing the preprocessed image data according to the transmission sequence to obtain image data to be optimized;
and step S43, detecting whether the image data to be optimized is missing a data segment according to the network condition data, if so, retransmitting the missing data segment and then executing step S5, and if not, directly executing step S5.
7. The method for adaptive image transmission of an intelligent network monitoring sensor according to claim 1, wherein the adaptive transmission in step S5 includes a real-time transmission for immediate response and a buffer transmission for temporary storage data.
8. The adaptive image transmission method of intelligent network monitoring sensor according to claim 2, wherein the network bandwidth is controlled by a timer to record the time of data packet transmission and reception.
9. The method of claim 2, wherein the round trip delay is a time difference between a message sent from the intelligent network monitoring sensor to a target server.
10. The method for adaptive image transmission of an intelligent network monitoring sensor according to claim 9, wherein the intelligent network monitoring sensor is disposed on a probe of a palm ultrasound device.
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