Long-endurance real-time intelligent transmission method of wireless low-power-consumption transmitter

Abstract

The invention relates to a long-endurance real-time intelligent transmission method of a wireless low-power-consumption transmitter, which belongs to the technical field of electric digital data processing and comprises the following steps of: a) establishing a data transmission priority queue based on the timeliness of data sent by the transmitter; step b), adjusting a data transmission priority queue by adopting a dynamic real-time scheduling mode based on the transmitter; c) performing intelligent transmission data processing on the adjusted data transmission priority queue based on a transmitter; step d), receiving the data processed by the intelligent transmission data by a signal receiver, and establishing an intelligent transmission data evaluation model to evaluate the quality of the transmission data; step e), distributing the evaluated transmission data; the method has the beneficial effects that the shorter the effective time is set, the higher the priority is, and the high-priority data is transmitted within the short effective time, namely, the high-priority data is transmitted within the short effective time, so that the data transmission quantity is reduced, and low-power-consumption data transmission is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of electronic digital data processing, and particularly relates to a long-endurance real-time intelligent transmission method for a wireless low-power transmitter. Background Art

[0002] Wireless low-power data transmission is a wireless data transmission technology aiming to reduce energy consumption. It is widely used in Internet of Things technology. By collecting data through various sensors and performing low-power transmission, actual data collection is achieved.

[0003] In existing wireless low-power data transmission, a wireless radio frequency system and a high-precision analog signal collector are set at the transmitter end to preprocess the collected original data, including operations such as noise removal, data filtering, data calibration, and temperature compensation, so as to improve data quality, reduce the transmission of invalid data, and reduce the overall operating power consumption. However, specifically how to reduce the overall operating power consumption is an urgent problem to be solved. Summary of the Invention

[0004] The present invention provides a long-endurance real-time intelligent transmission method for a wireless low-power transmitter, which is used to solve the technical problem of how to achieve low-power data transmission. The shorter the effective time is set, the higher the priority. Within a short effective time, high-priority data is transmitted. The main purpose of intelligent transmission data processing is to transmit high-priority data within a short effective time to reduce the data transmission volume and achieve low-power data transmission.

[0005] To achieve the above purpose, the present invention is realized through the following technical solutions:

[0006] A long-endurance real-time intelligent transmission method for a wireless low-power transmitter includes the following steps:

[0007] Step a): Establish a data transmission priority queue based on the data timeliness of the transmitter;

[0008] Step b): Adjust the data transmission priority queue based on the transmitter using a dynamic real-time scheduling method;

[0009] Step c): Perform intelligent transmission data processing on the adjusted data transmission priority queue; among them, a method of data level and time quantization is used to perform intelligent transmission data processing to reduce the data transmission volume and achieve low-power data transmission;

[0010] Step d): The signal receiver receives the data after intelligent transmission data processing and establishes an intelligent transmission data evaluation model to evaluate the quality of the transmitted data; among them, the quality of the transmitted data is evaluated based on the amount and priority of the transmitted data;

[0011] Step e): Allocate the evaluated transmission data.

[0012] Optionally, in step a), within the data timeliness, for the establishment of the data transmission priority queue, the following method is adopted:

[0013] Arrange the data transmission priority queue according to the chronological order; among them, according to the chronological order, perform data transmission from low-priority to high-priority.

[0014] Arrange the data transmission priority queue according to the random order of time sequence.

[0015] Optionally, in step b), the method of dynamic real-time scheduling is as follows:

[0016] If there are tasks , and each task has an execution time ;

[0017] For preemptive priority scheduling, if the tasks are sorted from high to low in priority and high-priority tasks will not be preempted in execution time by low-priority tasks, then the completion time of the task can be calculated by the following formula:

[0018] , then the completion time of the highest-priority task is its execution time;

[0019] , represents that the completion time of task is the completion time of the previous high-priority task plus its own execution time.

[0020] Optionally, for a set of independent periodic tasks, assuming the task set , the task has a period of , an execution time of , and the priority is arranged according to , the sufficient condition for the task set to be schedulable under preemptive priority-driven scheduling is .

[0021] Optionally, in step c), perform intelligent transmission processing on all the received data, adopting the following steps:

[0022] Step Ⅰ): Screen the transmission data with small data volume and high priority;

[0023] Step Ⅱ): Among the screened data, data is transmitted according to the data with the least amount and the highest priority.

[0024] Step Ⅲ): The data with the least amount and the highest priority is used as the data transmission priority queue.

[0025] Optionally, in step c), the method of data level and time quantization is as follows: Let the initial effective time of the data be , the current time be , then the effective time is ;

[0026] Priority can be calculated by the following formula: When , , as decreases, increases rapidly;

[0027] Or, the generation time of the data is , the effective cut-off time of the data is , the current time is , then the effective time The calculation formula is: ;

[0028] The priority of the data is determined according to the effective time. The shorter the effective time, the higher the priority of the data;

[0029] The priority calculation model is a linear function:

[0030] , the priority is calculated as the ratio of the effective time to the total calculation time. The shorter the effective time is set and the total time remains unchanged, the smaller the ratio is, and the higher the priority is. In a short effective time, high-priority data is transmitted to reduce the data transmission volume and achieve low-power data transmission.

[0031] Optionally, in step d), the establishment of the intelligent data transmission evaluation model adopts the following steps:

[0032] Step 1): Using the least amount of transmitted data and the highest priority as the quality standard for evaluating the transmitted data;

[0033] Step 2): Using the least amount of transmitted data and the highest priority as high-quality transmitted data, and the largest amount of transmitted data and the lowest priority as low-quality transmitted data;

[0034] Step 3): After evaluating each transmitted data, arrange them from high-quality transmitted data to low-quality transmitted data.

[0035] Optionally, in step 3), high-quality transmission data is used for data transmission to low-quality transmission data.

[0036] Optionally, in step e), among the evaluated transmission data, the high-quality transmission data is allocated.

[0037] Advantages of the present invention:

[0038] 1. The present invention first establishes a data transmission priority queue, adjusts the data transmission priority queue, performs intelligent transmission data processing and sends data, receives the data sent by the data sending module, establishes an intelligent transmission data evaluation model to evaluate the quality of the transmission data, and allocates or executes the evaluated transmission data.

[0039] 2. The shorter the effective time set by the present invention, the higher the priority. Within a short effective time, high-priority data is transmitted. The intelligent transmission data processing mainly involves transmitting high-priority data within a short effective time to reduce the data transmission volume and achieve low-power data transmission. Brief Description of the Drawings

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0041] Figure 1 It is a schematic diagram of the system structure of the present invention;

[0042] Figure 2 It is a working flowchart of the present invention. Detailed Embodiments

[0043] The following will describe the embodiments of the present application in detail with reference to the drawings.

[0044] Embodiment 1:

[0045] As Figure 1 shown, this embodiment provides an intelligent transmission system for a wireless low-power transmitter, including: a transmitter and a signal receiver;

[0046] The transmitter includes a data acquisition module and a data sending module;

[0047] The signal receiver includes a data receiving module and a data evaluation module;

[0048] The data acquisition module in the transmitter is connected to the data sending module, the data receiving module in the signal receiver is connected to the data evaluation module, and the data sending module and the data receiving module are connected by a signal.

[0049] The data acquisition module acquires data, the data sending module sends data, the data receiving module receives the data sent by the data sending module, the data evaluation module evaluates the data, and the evaluated data is then executed.

[0050] Specifically, the data acquisition module of the transmitter acquires data, the data acquisition module establishes a data transmission priority queue, the data sending module adjusts the data transmission priority queue, performs intelligent transmission data processing and sends data, the data receiving module of the signal receiver receives the data sent by the data sending module, the data evaluation module establishes an intelligent transmission data evaluation model to evaluate the quality of the transmitted data, the data evaluation module is connected to the execution unit, and the execution unit distributes or executes the evaluated transmitted data.

[0051] Embodiment 2:

[0052] Based on Embodiment 1, as Figure 2 shown, this embodiment provides a long-endurance real-time intelligent transmission method for a wireless low-power transmitter, including the following steps:

[0053] Step a): Establish a data transmission priority queue based on the timeliness of the data sent by the transmitter;

[0054] Step b): Adjust the data transmission priority queue based on the dynamic real-time scheduling method adopted by the transmitter;

[0055] Step c): Perform intelligent transmission data processing on the adjusted data transmission priority queue based on the transmitter; among them, a method of data level and time quantization is adopted to perform intelligent transmission data processing to reduce the data transmission volume and achieve low-power data transmission;

[0056] Step d): The signal receiver receives the data after intelligent transmission data processing and establishes an intelligent transmission data evaluation model to evaluate the quality of the transmitted data; among them, the quality of the transmitted data is evaluated based on the amount and priority of the transmitted data;

[0057] Step e): Distribute the evaluated transmitted data.

[0058] Embodiment 3:

[0059] Based on Embodiment 2, specifically, in step a), within the data timeliness (e.g., within 30 min), for the establishment of the data transmission priority queue, the following method is adopted:

[0060] Generally, the data transmission priority queue is arranged according to the chronological order; among them, according to the chronological order, the data transmission is carried out from the lower level to the higher level; that is to say, the lower-level data is transmitted in the earlier time sequence, and the higher-level data is transmitted in the later time sequence.

[0061] Arranging the data transmission priority queue according to the chronological order, that is to say, regardless of the chronological order, the data transmission is carried out from the lower level to the higher level. This method is generally not adopted.

[0062] In step b), the dynamic real-time scheduling method is that if there are tasks , each task has an execution time ;

[0063] For preemptive priority scheduling, if the tasks are sorted from high to low according to the priority, and the high-priority tasks will not be preempted by the low-priority tasks (except by the higher-priority tasks) for the execution time, then the completion time of the task can be calculated by the following formula:

[0064] , then the completion time of the highest-priority task is its execution time;

[0065] , represents that the completion time of the task is the completion time of the previous high-priority task plus its own execution time, because in preemptive priority scheduling, the low-priority tasks can only be executed when there are no higher-priority tasks executing.

[0066] In step b), the schedulability of the dynamic real-time scheduling is:

[0067] Using the Liu-Layland formula: For a set of independent periodic tasks, assuming the task set , the task has a period of , an execution time of , and the priorities are arranged according to . The sufficient condition for the task set to be schedulable under preemptive priority-driven scheduling is . When tends to infinity, approaches ln2≈0.693. For example, there are three tasks , , , , , , , , . It can be calculated that , while , because 1.025 > 0.7797, so according to the Liu-Layland formula, the task set is not schedulable under preemptive priority-driven scheduling.

[0068] Schedulability analysis:

[0069] To determine whether the system can meet the real-time requirements of all tasks under priority-driven scheduling, it is necessary to analyze the system load. The system load can be calculated through the execution time and period of the tasks. Assume that the task has a period of (for aperiodic tasks, the arrival time interval can be regarded as the period), then the system load is: .

[0070] When ≤1, it is theoretically possible for the system to meet the real-time requirements of all tasks, but this is only a necessary condition, not a sufficient condition. Because issues such as task priority allocation and the existence of priority inversion also need to be considered. For example, even if ≤1, but if a low-priority task occupies resources for a long time, resulting in a high-priority task not being able to execute in time, it may also not be able to meet the real-time requirements.

[0071] Response time calculation: The response time of a task refers to the time interval from when the task arrives at the system to when it starts to execute. For priority-driven scheduling, the response time of the task is affected by its own priority and other high-priority tasks.

[0072] Set to represent the set of tasks with a priority higher than that of task , then the response time of task can be calculated through the following recursive formula: , where is the response time of the task with a priority higher than , and the formula indicates that the response time of task

[0073] For the specific calculation of the response time: For a single task , the response time calculation needs to consider its relationship with other high - priority tasks. Assume represents the set of tasks with a higher priority than task , represents the maximum blocking time that task may be subject to (e.g., blocked by other tasks due to resource sharing, etc.), then 's calculation formula is , which is a recursive formula and needs to be solved through iterative calculation . For example: There are three tasks , , , with priorities , , , , , , , let (because may be blocked by other tasks for 1 time unit). First, calculate , because is the highest - priority task and is not affected by other high - priority tasks, so . Then calculate , , , and through iterative calculation, we can get = 5. Finally, calculate , , After multiple iterative calculations, we can get = 10.

[0074] For the entire task set, to determine whether all tasks can be completed within their respective deadlines, it is necessary to calculate the response time of each task and compare it with their deadlines. If the response times of all tasks are less than or equal to their deadlines, the task set is schedulable; otherwise, the task set is not schedulable.

[0075] Example 4:

[0076] Based on Example 2, in step c), perform intelligent data transmission processing on the adjusted data transmission priority queue;

[0077] Due to the strong timeliness of the data, the data needs to be transmitted within the specified time, otherwise it will lose its value. Therefore, calculate the priority according to the valid time of the data and transmit the adjusted data;

[0078] Intelligent transmission data processing is (a method of data level and time quantization, that is, a data level and time quantization model): Assume the initial effective time of the data is , and the current time is , then the effective time is .

[0079] Priority can be calculated by the following formula: (when ); as decreases, increases rapidly. For example, when shortens from 10 seconds to 1 second, increases from to 1, and the priority is significantly improved. It is applicable to scenarios with extremely high requirements for timeliness and where the data value drops sharply near expiration.

[0080] It can be interpreted that the effective time of real-time data transmission is only a few minutes. As time goes by, the effective time decreases and the priority will gradually increase to ensure that the transmission is completed within the effective time.

[0081] In this way, the shorter the effective time is set, the higher the priority. Within a short effective time, high-priority data is transmitted. The main purpose of intelligent transmission data processing is to transmit high-priority data within a short effective time to reduce the data transmission volume and achieve low-power data transmission.

[0082] Specifically, the generation time of the data is , the effective expiration time of the data is (the time node when the data loses value or cannot be used anymore in the scenario), and the current time is (the moment when the system acquires the data and calculates the priority), then the effective time The calculation formula is: ;

[0083] The priority of the data can be determined according to the effective time. Generally speaking, the shorter the effective time, the higher the priority of the data.

[0084] The priority calculation model is a linear function:

[0085] , therefore, the priority calculation is the ratio of the effective time to the total calculation time ( ). The shorter the effective time is set and the total time remains unchanged, the smaller the ratio, the higher the priority. Within a short effective time, high-priority data is transmitted to reduce the data transmission volume and achieve low-power data transmission;

[0086] The inverse proportional form of a linear function (for the transformation of a linear function) is (when ), the priority calculation is to calculate the ratio of the total time to the effective time.

[0087] In the priority calculation based on timeliness, the effective time is the core parameter, which reflects the effective deadline and the effective time at the current moment. The formula intuitively shows the remaining state of data timeliness.

[0088] For the inverse proportional form of a linear function (when ), represents the total calculation time of the data. The total calculation time (initial effective time ) is associated with the effective time to calculate the proportional change in the priority of the data throughout its life cycle. For example, when the total data time is 60 minutes and the effective time is 30 minutes, ; when the effective time is 15 minutes, , the priority increases linearly, which is applicable to the scenario where the data value decreases uniformly over time.

[0089] Data expiration means : when , the data has lost its timeliness. At this time, the priority can be set to the lowest (e.g., 0), or removed from the priority queue.

[0090] For the inverse proportional form of a linear function, at the time of data generation, the initial can be used to calculate the initial priority. For example, for a task data with an effective duration of 1 hour, at the moment of generation, is 3600s, and the initial priority is calculated through the inverse proportional function. As time progresses, the priority changes continuously.

[0091] Example 5:

[0092] Based on Example 2, in step d), to establish an intelligent transmission data evaluation model, the following steps are adopted:

[0093] Step 1): Taking the least amount of transmitted data and the highest priority as the quality standard for evaluating transmitted data;

[0094] Step 2): Taking the least amount of transmitted data and the highest priority as high-quality transmitted data, and the most amount of transmitted data and the lowest priority as low-quality transmitted data;

[0095] Step 3): After evaluating each transmitted data, arrange them from high-quality transmitted data to low-quality transmitted data.

[0096] In step 3), transfer high-quality transmission data to low-quality transmission data for data transmission.

[0097] For the intelligent transmission data evaluation model, the Analytic Hierarchy Process (AHP) is adopted: decompose the elements related to the decision into the target, criterion, and scheme levels, and on this basis, a decision-making method of qualitative and quantitative analysis is carried out. By constructing a judgment matrix, calculate the weights of various factors, and then comprehensively evaluate the priority of the data.

[0098] Example: When evaluating the priority of network data transmission, take security, real-time performance, bandwidth requirements, etc. as the criterion layer, determine the relative importance between each criterion through pairwise comparison, construct a judgment matrix, calculate the weights of each criterion, and then combine the performance of the data under each criterion to obtain the priority.

[0099] Specifically, the Analytic Hierarchy Process (AHP) is as follows:

[0100] 1. Construct a judgment matrix:

[0101] Suppose there are factors in the criterion layer. For a certain element in the upper layer, compare the importance of each factor pairwise and construct a judgment matrix . Among them, represents the importance degree of the th factor relative to the th factor. Usually, the 1-9 scale method is used for assignment, and its meaning is shown in Table 1 below:

[0102] Table 1 Assignment of the 1-9 scale method

[0103]

[0104] The diagonal elements are 1, that is, , because a factor has the same importance when compared with itself, and the reciprocity is , which ensures the consistency and rationality of the judgment matrix. Suppose we want to evaluate the priority of data transmission and consider three factors: data importance, timeliness, and data volume. For the upper layer of "data transmission priority", construct a judgment matrix. For example, if it is considered that data importance is significantly more important than timeliness, according to the 1-9 scale method, assign a value of 5, then ; data importance is more important than data volume, is assigned a value of 7, , timeliness is slightly more important than data volume, is assigned a value of 3, , and the judgment matrix is as follows:

[0105] ;

[0106] 2. Calculate the weight vector:

[0107] Calculate the product of the elements in each row of the judgment matrix: , .

[0108] Calculate of th root: ;

[0109] Perform normalization on to obtain the weight vector: , , at this time, is obtained, which is the weight vector of each factor, is the transpose symbol.

[0110] Calculate the product of the elements in each row of the judgment matrix: , , .

[0111] Calculate of th root: Here = 3;

[0112] , , .

[0113] Perform normalization on to obtain the weight vector: ; , , .

[0114] Therefore, the weight vector of the three factors of data importance, timeliness, and data volume .

[0115] 3. Calculate the maximum eigenvalue :

[0116] , where represents the th element of the vector.

[0117] Calculate : ;

[0118] Calculate : ;

[0119] 4. Conduct consistency check. Since the judgment matrix is constructed based on subjective judgment, there may be inconsistent situations. Therefore, consistency check is required to ensure the reliability of the results. The commonly used check index is the consistency ratio (CR):

[0120] Calculate the consistency index : , ;

[0121] When = 3, look up the average random consistency index table, and we can get = 0.58. Calculate the consistency ratio : ;

[0122] Look up the corresponding average random consistency index (which can be obtained by looking up the table. Different values correspond to different values). Calculate the consistency ratio : , when < 0.1, it is considered that the judgment matrix has satisfactory consistency. Otherwise, the judgment matrix needs to be adjusted.

[0123] If the judgment matrix has satisfactory consistency, the weight vector we obtained is reliable. When evaluating the data transmission priority, we can determine the priority of the data comprehensively according to the weights of these three factors and the performance of the data on each factor. If a certain data scores 8 points, 6 points, and 4 points in terms of importance, timeliness, and data volume respectively, then its priority score is approximately 0.730×8 + 0.188×6 + 0.082×4 ≈ 7.09 points. In this way, different data can be sorted by priority to arrange the data transmission-related work more reasonably.

[0124] In step e), among the evaluated transmission data, allocate the high-quality transmission data, that is, use the high-quality transmission data for execution.

[0125] Based on all the above embodiments, the present invention first establishes a data transmission priority queue, adjusts the data transmission priority queue, conducts intelligent transmission data processing and sends data, receives the data sent by the data sending module, establishes an intelligent transmission data evaluation model to evaluate the quality of the transmission data, and allocates or executes the evaluated transmission data.

[0126] In the present invention, the shorter the effective time is set, the higher the priority. Within a short effective time, high-priority data is transmitted. For intelligent data transmission processing, mainly within a short effective time, high-priority data is transmitted to reduce the data transmission volume, achieving low-power data transmission.

[0127] Those of ordinary skill in the art can understand that all or part of the steps in realizing the above facts and methods can be completed by instructing relevant hardware through a program. The program involved or the program can be stored in a computer-readable storage medium. When the program is executed, it includes the following steps: At this time, the corresponding method steps are introduced. The storage medium can be ROM / RAM, magnetic disk, optical disk, etc.

[0128] As described above, only the specific embodiments of the present invention are provided, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope recorded in the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A long-endurance real-time intelligent transmission method for a wireless low-power transmitter, characterized in that It includes the following steps: Step a): Establish a data transmission priority queue based on the timeliness of the data sent by the transmitter; Step b): Adjust the data transmission priority queue based on the transmitter using a dynamic real-time scheduling method; Step c): Perform intelligent transmission data processing on the adjusted data transmission priority queue; among them, adopt the method of data level and time quantization to perform intelligent transmission data processing to reduce the data transmission volume and achieve low-power data transmission; Step d): The signal receiver receives the data after intelligent transmission data processing and establishes an intelligent transmission data evaluation model to evaluate the quality of the transmitted data; among them, evaluate the quality of the transmitted data based on the volume and priority of the transmitted data; Step e): Allocate the evaluated transmitted data.

2. The long-endurance real-time intelligent transmission method of a wireless low-power transmitter according to claim 1, characterized in that, In the said step a), within the data timeliness, for the establishment of the data transmission priority queue, adopt the following method: Arrange the data transmission priority queue according to the chronological order; among them, according to the chronological order, perform data transmission from poor level to excellent level; Arrange the data transmission priority queue according to the random order of the time sequence.

3. A long-endurance real-time intelligent transmission method for a wireless low-power transmitter according to claim 1, characterized in that, In the said step b), the dynamic real-time scheduling method is as follows: If there is task and each task has an execution time ; For preemptive priority scheduling, if tasks are sorted from highest to lowest priority and a higher-priority task cannot have its execution time preempted by a lower-priority task, then the completion time of the task is calculated by the following formula: , then the completion time of the highest-priority task is its execution time; , indicates that the completion time of the task is the completion time of the previous high-priority task plus its own execution time.

4. A long-endurance real-time intelligent transmission method for a wireless low-power transmitter according to claim 3, characterized in that, For a set of independent periodic tasks, assume the task set , task has a period of , an execution time of , and a priority arranged according to . The sufficient condition for the task set to be schedulable under preemptive priority-driven scheduling is .

5. A long-endurance real-time intelligent transmission method for a wireless low-power transmitter according to claim 1, characterized in that In the said step c), perform intelligent transmission processing on all the received data, adopting the following steps: Step Ⅰ): Screen the transmission data with small data volume and high priority; Step Ⅱ): Among the screened data, perform data transmission according to the transmission data with the least data volume and the highest priority; Step Ⅲ): Use the transmission data with the least data volume and the highest priority as the data transmission priority queue.

6. A long-endurance real-time intelligent transmission method for a wireless low-power transmitter according to claim 1, characterized in that In the step c), the method for the data level and time quantization is that the initial valid time of the data is set as , the current time is , then the valid time is ; Priority It can be calculated by the following formula: when then along with decreasing rapidly increases; Or, the generation time of the data is , the effective expiration time of the data is , the current time is , then the effective time of the data The calculation formula is: ; Priority of data Determined according to the valid time. The shorter the valid time, the higher the priority of the data; The priority calculation model is a linear function: , the priority is calculated as the ratio of the effective time to the total calculation time. The shorter the effective time is set and the total time remains unchanged, the smaller the ratio is, and the higher the priority is. Within a short effective time, high-priority data is transmitted to reduce the data transmission volume and achieve low-power data transmission.

7. A long-endurance real-time intelligent transmission method for a wireless low-power transmitter according to claim 1, characterized in that In the said step d), for the establishment of the intelligent transmission data evaluation model, adopt the following steps: Step 1): Use the least data volume and the highest priority of the transmitted data as the quality standard for evaluating the transmitted data; Step 2): Use the least data volume and the highest priority of the transmitted data as high-quality transmitted data, and use the most data volume and the lowest priority of the transmitted data as low-quality transmitted data; Step 3): After evaluating each transmitted data, arrange them from high-quality transmitted data to low-quality transmitted data.

8. A long-endurance real-time intelligent transmission method for a wireless low-power transmitter according to claim 7, characterized in that, In the said step 3), use the high-quality transmitted data to the low-quality transmitted data for data transmission.

9. A long-endurance real-time intelligent transmission method for a wireless low-power transmitter according to claim 1, characterized in that, In the said step e), among each evaluated transmitted data, allocate the high-quality transmitted data.

Images