Method and system for regulating and controlling power consumption of multiple sensors of offshore buoy

Abstract

The invention relates to the technical field of maritime buoys, in particular to a maritime buoy multi-sensor power consumption regulation and control method and system.The maritime buoy multi-sensor power consumption regulation and control method comprises the steps that during maritime buoy multi-sensor power consumption regulation and control, the priorities of tasks are determined firstly, and then task weight values are set according to the tasks of the priorities; the method comprises the following steps: acquiring a plurality of tasks, determining an association weight value between each task and a sensor, and calculating a sensor priority comprehensive score of each sensor under different tasks, so that the obtained sensor priority comprehensive score is used for regulating and controlling the power consumption of the sensor, and the regulation and control are more scientific; meanwhile, an improved genetic algorithm is adopted to solve the regulation and control model, and the genetic algorithm is improved, so that the algorithm is encouraged to perform more exploration when the population diversity is relatively low, and premature convergence is avoided; meanwhile, the fitness function is dynamically adjusted, so that the algorithm can be adjusted according to the real-time state of the population, and the adaptability of the algorithm is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of marine buoys, and in particular to a method and system for controlling power consumption of multiple sensors of marine buoys. Background Art

[0002] Marine buoys are widely used devices for ocean monitoring, typically equipped with a variety of sensors to collect marine environmental data, such as temperature, humidity, wind speed, wind direction, and current speed. However, marine buoys are usually battery-powered, and the limited battery power limits their operating time and data collection frequency. Existing power consumption control methods often use simple timed sleep or single sensor sleep strategies, which cannot flexibly adjust the sensor's operating state according to actual mission requirements, resulting in wasted power or incomplete data collection, making it difficult to meet the needs of long-term, high-efficiency ocean monitoring. Therefore, it is of great practical significance to develop a scientific power consumption control method and system that can dynamically adjust sensor sleep and wake-up according to mission priority. Summary of the Invention

[0003] In order to solve the above technical problems, the present invention provides a method and system for controlling power consumption of multiple sensors of an offshore buoy, which are used to solve the problems existing in the prior art.

[0004] The present invention provides a method for controlling power consumption of multiple sensors of a marine buoy, comprising the following steps: S1: Prioritize the tasks to be completed by the offshore buoy; S2: Set task weight values ​​for tasks of each priority level; S3: Determine the association weight value between each task and sensor; S4: Calculate the sensor priority comprehensive score of each sensor under different tasks according to the task weight value and the association weight value; S5: Regulating the power consumption of multiple sensors according to the sensor priority comprehensive score.

[0005] The S5 is specifically: S5.1: Construct an optimization model based on an improved genetic algorithm; S5.2: solving the optimization model based on the improved genetic algorithm; The genetic algorithm is improved by a dynamic fitness function determination method, and the dynamic fitness determination method is specifically as follows: First, calculate the maximum Euclidean distance and the average Euclidean distance between any two individuals in the population; then define the adjustment factor; finally, adjust the fitness function; The formula for the adjustment factor α is: ; Among them, the fitness function adjustment formula is: ; In the formula, x is an individual, is the adjusted fitness function, is the fitness function before adjustment, β is the adjustment amplitude control parameter; S5.3: Implement multi-sensor power consumption control based on the solution results.

[0006] Preferably, the optimization model based on the improved genetic algorithm includes model parameters, objective functions and constraints.

[0007] Preferably, the parameters of the optimization model based on the improved genetic algorithm include: S: sensor set, S={1,2,…,n}, where n is the total number of sensors; T: task set, T={1,2,…,m}, where m is the total number of tasks; P i : The priority comprehensive score of sensor i; E i : power consumption of sensor i; R t : The priority of task t; B: Current power of the offshore buoy; B min : The minimum threshold of the power of the offshore buoy. When the power is lower than this value, energy-saving measures must be taken; x i : state variable of sensor i, x i =1 indicates working state, x i =0 means sleep state; The objective function is: ; Where λ is a balancing factor used to weigh the relationship between priority score and power consumption; The constraints of the optimization model based on the improved genetic algorithm include power constraints and sensor state constraints; The power constraint is: the power of the offshore buoy cannot be lower than a minimum threshold; ; The sensor state constraint: the state variable of the sensor can only be 0 or 1; .

[0008] Preferably, the S5.3 is specifically as follows: an optimal solution can be output through step S5.2, the optimal solution including a status value of each sensor, which is used to indicate whether each sensor should work, and a sleep or wake-up instruction is sent to the sensor according to the optimal solution to realize power consumption control of the offshore buoy.

[0009] Preferably, in S4, the calculation formula for the sensor priority comprehensive score of each sensor under different tasks is: Sensor priority comprehensive score = task weight value × sensor association weight value × sensor performance coefficient.

[0010] Preferably, in S3, the requirement degree of each task for each sensor is analyzed, and the association weight between the task and the sensor is determined.

[0011] Preferably, in S1, the offshore buoy tasks are divided into three priorities: high priority tasks, medium priority tasks and low priority tasks.

[0012] According to another aspect of the present invention, a system for controlling power consumption of multiple sensors on an offshore buoy is provided. The system adopts the above-mentioned method for controlling power consumption of multiple sensors on an offshore buoy, and the system comprises: A priority allocation module, configured to allocate priorities to tasks to be completed by the offshore buoy; Task weight value calculation module, used to set task weight value for tasks of each priority level; An association weight calculation module is used to determine the association weight value between each task and the sensor; A sensor priority comprehensive score calculation module is used to calculate the sensor priority comprehensive score of each sensor under different tasks based on the task weight value and the association weight value; The power consumption control module is used to control the power consumption of multiple sensors according to the comprehensive score of the sensor priorities.

[0013] The embodiments of the present invention have the following technical effects: When regulating the power consumption of multiple sensors on an offshore buoy, the present invention first determines the priority of the task, then sets a task weight value based on the task of each priority, and determines the association weight value between each task and the sensor. Based on this, the sensor priority comprehensive score of each sensor under different tasks is calculated. The sensor priority comprehensive score obtained in this way is used to regulate the sensor power consumption, making the regulation more scientific. At the same time, the present invention adopts an improved genetic algorithm to solve the control model. When improving the genetic algorithm, an adjustment factor is set according to the Euclidean distance, and the fitness is adjusted according to the adjustment factor. The Euclidean distance is related to the diversity of the population, thereby encouraging the algorithm to conduct more exploration when the population diversity is low and avoiding premature convergence. At the same time, the fitness function is dynamically adjusted so that the algorithm can be adjusted according to the real-time status of the population, thereby improving the adaptability of the algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0015] Figure 1 This is a flow chart of a method for controlling power consumption of multiple sensors on a marine buoy provided by an embodiment of the present invention; Figure 2 This is a flow chart of regulating the power consumption of multiple sensors according to the sensor priority comprehensive score provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0016] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0017] Attachment Figure 1 A flow chart of a method for controlling power consumption of multiple sensors on a marine buoy is shown in the attached figure. Figure 1 As shown, a method for controlling power consumption of multiple sensors of a marine buoy includes the following steps: S1: Prioritize the tasks to be completed by the offshore buoy; The tasks undertaken by offshore buoys are diverse, involving marine environmental monitoring, weather forecasting, marine disaster warning and other aspects. In order to reasonably allocate task priorities, it is first necessary to scientifically classify these tasks.

[0018] In this embodiment, the offshore buoy tasks are divided into three priorities: high priority tasks, medium priority tasks, and low priority tasks.

[0019] High-priority tasks include marine disaster warnings and key marine scientific research missions. These include emergency tasks such as typhoon warnings, tsunami monitoring, and red tide outbreak monitoring. Data collection and transmission for these tasks require high real-time and accuracy, and are crucial for safeguarding marine safety and the safety of human life and property. For example, in typhoon warning missions, offshore buoys must collect real-time data on wind speed, wind direction, air pressure, and wave height, and promptly transmit this data to onshore monitoring centers to accurately predict typhoon paths and intensity, providing a scientific basis for disaster prevention and mitigation. Key marine scientific research missions include key data collection tasks in deep-sea observation programs and core monitoring tasks in marine ecosystem protection. The data from these missions is of great significance to marine scientific research and marine resource development, and their collection and transmission must be prioritized. For example, when studying the response of marine ecosystems in a specific sea area to climate change, the data collected by offshore buoys on key parameters such as seawater temperature, salinity, and dissolved oxygen in that area is extremely demanding, and data collection and transmission for these tasks must be prioritized.

[0020] The medium-priority tasks include routine marine environmental monitoring tasks and general marine scientific research tasks; among them, the routine marine environmental monitoring tasks include daily monitoring of parameters such as seawater temperature, salinity, and pH. The data from these tasks are of great significance for studying marine ecosystems, marine climate change, etc., but relatively speaking, they do not require as much time urgency as high-priority tasks. Data collection for routine tasks is usually carried out according to a certain cycle, such as once a day or every few hours, so they are classified as medium-priority tasks; the general marine scientific research tasks have certain reference value for marine environmental monitoring and marine resource assessment, but are not core and critical tasks, including routine marine environmental parameter monitoring of some non-key sea areas. Although the data from these tasks also have certain application value, their importance is relatively low under the condition of limited resources, and they are classified as medium-priority tasks.

[0021] The low-priority tasks include the offshore buoy's own status inspection task and auxiliary monitoring tasks; the offshore buoy's own status inspection task mainly monitors the buoy's battery power, sensor working status, communication system status, etc. Although these tasks are crucial to ensuring the normal operation of the offshore buoy, they have relatively low requirements for the timeliness of data collection and can be carried out without affecting the main monitoring tasks. For example, the offshore buoy's own status inspection task can be carried out when the offshore buoy has sufficient power and there are no urgent tasks, so it is classified as a low-priority task; the auxiliary monitoring tasks are mainly to meet some specific research needs or temporary monitoring tasks, such as auxiliary ocean monitoring tasks in student scientific research projects, short-term ocean experimental monitoring tasks, etc. The data collection of these tasks can be flexibly arranged according to the remaining resources of the offshore buoy and are classified as low-priority tasks.

[0022] S2: Set task weight values ​​for tasks of each priority level; Each priority task is assigned a corresponding weight value, where the high-priority task has the highest weight value and the low-priority task has the lowest weight value. In this step, the task weight value is in numerical form, the high-priority task has a task weight of 3, the medium-priority task has a task weight of 2, and the low-priority task has a task weight of 1. The task weight value is used to subsequently calculate the comprehensive score of the task priority to determine the sleep and wake-up strategy of the sensor.

[0023] S3: Determine the association weight value between each task and sensor; In this step, the sensor requirements for each task are analyzed, and the association weights between tasks and sensors are determined. For example, for a high-priority marine disaster warning task, the wind speed sensor and wave height sensor have higher association weights, perhaps set to 0.8 and 0.7, respectively. Meanwhile, for a medium-priority routine marine environment monitoring task, the seawater temperature sensor and salinity sensor have higher association weights, set to 0.6 and 0.5, respectively.

[0024] S4: Calculate the sensor priority comprehensive score of each sensor under different tasks according to the task weight value and the association weight value; The calculation formula for the sensor priority comprehensive score of each sensor under different tasks is: Sensor priority comprehensive score = task weight value × sensor association weight value × sensor performance coefficient; The sensor performance coefficient is a coefficient determined based on a performance evaluation result of the sensor. If the sensor is in a normal state, the coefficient is 1; if the working performance of the sensor is degraded, the sensor performance coefficient is 0.5.

[0025] S5: Regulating the power consumption of multiple sensors according to the sensor priority comprehensive score.

[0026] In this step, based on the key indicator of sensor priority comprehensive score, the power consumption of multiple sensors is regulated by building a model and solving it to achieve optimal power consumption management.

[0027] Among them, as attached Figure 2 As shown, the S5 is specifically: S5.1: Construct an optimization model based on an improved genetic algorithm; The parameters of the optimization model based on the improved genetic algorithm include: S: sensor set, S={1,2,…,n}, where n is the total number of sensors; T: task set, T={1,2,…,m}, where m is the total number of tasks; P i : The priority comprehensive score of sensor i; E i : power consumption of sensor i; R t : The priority of task t; B: Current power of the offshore buoy; B min : The minimum threshold of the power of the offshore buoy. When the power is lower than this value, energy-saving measures must be taken; x i : state variable of sensor i, x i =1 indicates working state, x i =0 indicates sleep state.

[0028] The objective function of the linear programming-based optimization model is established with the goal of maximizing the sensor's priority comprehensive score while minimizing power consumption: Specifically, the objective function is: ; Where λ is a balancing factor used to weigh the relationship between priority score and power consumption; Wherein, the constraint conditions of the optimization model based on the improved genetic algorithm include power constraint and sensor state constraint; The power constraint is: the power of the offshore buoy cannot be lower than a minimum threshold; ; The sensor state constraint: the state variable of the sensor can only be 0 or 1; .

[0029] S5.2: solving the optimization model based on the improved genetic algorithm; A genetic algorithm (GA) is a search algorithm that simulates the principles of natural selection and genetics and is suitable for solving complex optimization problems. To improve the performance of the GA, this embodiment proposes an improved GA that enhances the algorithm's global search capability and convergence speed by introducing a dynamic fitness function determination method.

[0030] Specifically, the dynamic fitness determination method is as follows: First, calculate the maximum Euclidean distance and the average Euclidean distance between any two individuals in the population; then define the adjustment factor; finally, adjust the fitness; The formula for the adjustment factor α is: ; Among them, the fitness adjustment formula is: ; In the formula, x is an individual, is the adjusted fitness, is the fitness before adjustment, β is the adjustment amplitude control parameter; In this step, by setting an adjustment factor according to the Euclidean distance and adjusting the fitness according to the adjustment factor, the Euclidean distance is related to the diversity of the population, thereby encouraging the algorithm to conduct more exploration when the population diversity is low and avoid premature convergence; at the same time, the fitness function is dynamically adjusted so that the algorithm can adjust according to the real-time status of the population, thereby improving the adaptability of the algorithm.

[0031] S5.3: Implement multi-sensor power consumption control based on the solution results; Among them, the S5.3 is specifically: the optimal solution can be output through step S5.2, and the optimal solution includes the status value of each sensor, that is, indicating whether each sensor should work, and sending a sleep or wake-up instruction to the sensor according to the optimal solution to realize the power consumption control of the offshore buoy.

[0032] In Example 2, the present invention further provides a system for controlling power consumption of multiple sensors on a buoy at sea. The system adopts the method for controlling power consumption of multiple sensors on a buoy at sea in Example 1, and the system includes: A priority allocation module, configured to allocate priorities to tasks to be completed by the offshore buoy; Task weight value calculation module, used to set task weight value for tasks of each priority level; An association weight calculation module is used to determine the association weight value between each task and the sensor; A sensor priority comprehensive score calculation module is used to calculate the sensor priority comprehensive score of each sensor under different tasks based on the task weight value and the association weight value; The power consumption control module is used to control the power consumption of multiple sensors according to the comprehensive score of the sensor priorities.

[0033] Example 3: The present invention also provides an electronic device, including one or more processors and a memory.

[0034] The processor may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0035] The memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), a hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor may execute the program instructions to implement the marine buoy multi-sensor power consumption control method of any embodiment of the present application described above and / or other desired functions. Various contents such as initial external parameters and thresholds may also be stored in the computer-readable storage medium.

[0036] In one example, the electronic device may further include an input device and an output device, these components interconnected via a bus system and / or other connection mechanisms (not shown). The input device may include, for example, a keyboard, a mouse, etc. The output device may output various information to the outside, including warning information, braking force, etc. The output device may include, for example, a display, a speaker, a printer, a communication network, and remote output devices connected thereto.

[0037] Of course, for the sake of simplicity, components such as buses, input / output interfaces, etc. are omitted. In addition, the electronic device may further include any other appropriate components according to specific application scenarios.

[0038] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to implement the functions of the offshore buoy multi-sensor power consumption control method provided in any embodiment of the present application.

[0039] The computer program product may be written in any combination of one or more programming languages ​​to implement the program code for performing the operations of the embodiments of the present application, including object-oriented programming languages ​​such as Java, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0040] In addition, an embodiment of the present application may also be a computer-readable storage medium having computer program instructions stored thereon. When the computer program instructions are executed by a processor, the processor implements the method for controlling power consumption of multiple sensors of a marine buoy provided in any embodiment of the present application.

[0041] The computer-readable storage medium may be any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0042] It should be noted that the terms used in the present invention are only for describing specific embodiments and are not intended to limit the scope of this application. As shown in the present specification, unless the context clearly indicates an exception, the words "one", "a", "a kind of" and / or "the" do not specifically refer to the singular and may also include the plural. The terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method or device comprising a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method or device. In the absence of further restrictions, the elements defined by the sentence "comprise a..." do not exclude the presence of other identical elements in the process, method or device comprising the elements.

[0043] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling power consumption of multiple sensors on a marine buoy, characterized in that: The following steps are involved: S1: Prioritize the tasks to be completed by the offshore buoy; S2: Set task weight values ​​for tasks of each priority level; S3: Determine the association weight value between each task and sensor; S4: Calculate the sensor priority comprehensive score of each sensor under different tasks according to the task weight value and the association weight value; S5: regulating the power consumption of multiple sensors according to the sensor priority comprehensive score; The S5 is specifically: S5.1: Construct an optimization model based on an improved genetic algorithm; S5.2: solving the optimization model based on the improved genetic algorithm; The genetic algorithm is improved by a dynamic fitness function determination method, and the dynamic fitness determination method is specifically as follows: First, calculate the maximum Euclidean distance and the average Euclidean distance between any two individuals in the population; then define the adjustment factor; finally, adjust the fitness function; The formula for the adjustment factor α is: ； Among them, the fitness function adjustment formula is: ； In the formula, x is an individual, is the adjusted fitness function, is the fitness function before adjustment, β is the adjustment amplitude control parameter; S5.3: Implement multi-sensor power consumption control based on the solution results.

2. The method for controlling power consumption of multiple sensors on a marine buoy according to claim 1, wherein: The optimization model based on the improved genetic algorithm includes model parameters, objective functions and constraint conditions.

3. The method for controlling power consumption of multiple sensors on a marine buoy according to claim 2, wherein: The parameters of the optimization model based on the improved genetic algorithm include: S: sensor set, S={1,2,…,n}, where n is the total number of sensors; T: task set, T={1,2,…,m}, where m is the total number of tasks; P i : The priority comprehensive score of sensor i; E i : power consumption of sensor i; R t : The priority of task t; B: Current power of the offshore buoy; B min : The minimum threshold of the power of the offshore buoy. When the power is lower than this value, energy-saving measures must be taken; x i : state variable of sensor i, x i =1 indicates working state, x i =0 means dormant state; The objective function is: ； Where λ is a balancing factor used to weigh the relationship between priority score and power consumption; The constraints of the optimization model based on the improved genetic algorithm include power constraints and sensor state constraints; The power constraint is: the power of the offshore buoy cannot be lower than a minimum threshold; ； The sensor state constraint: the state variable of the sensor can only be 0 or 1; 。 4. The method for controlling power consumption of multiple sensors on a marine buoy according to claim 1, wherein: Specifically, the step S5.3 is as follows: an optimal solution may be outputted through step S5.2, the optimal solution including a status value of each sensor, which is used to indicate whether each sensor should work, and a sleep or wake-up instruction is sent to the sensor according to the optimal solution to realize power consumption control of the offshore buoy.

5. The method for controlling power consumption of multiple sensors on a marine buoy according to claim 1, wherein: In S4, the calculation formula for the sensor priority comprehensive score of each sensor under different tasks is: Sensor priority comprehensive score = task weight value × sensor association weight value × sensor performance coefficient.

6. The method for controlling power consumption of multiple sensors on a marine buoy according to claim 1, wherein: In S3, the requirement degree of each task for each sensor is analyzed, and the association weight between the task and the sensor is determined.

7. The method for controlling power consumption of multiple sensors on a marine buoy according to claim 1, wherein: In S1, the offshore buoy tasks are divided into three priorities: high priority tasks, medium priority tasks and low priority tasks.

8. A multi-sensor power consumption control system for marine buoys, characterized in that: The system adopts the method for controlling power consumption of multiple sensors of a marine buoy according to any one of claims 1 to 7, and the system comprises: A priority allocation module, configured to allocate priorities to tasks to be completed by the offshore buoy; Task weight value calculation module, used to set task weight value for tasks of each priority level; An association weight calculation module is used to determine the association weight value between each task and the sensor; A sensor priority comprehensive score calculation module is used to calculate the sensor priority comprehensive score of each sensor under different tasks based on the task weight value and the association weight value; The power consumption control module is used to control the power consumption of multiple sensors according to the comprehensive score of the sensor priorities.

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