Remote equipment control method and system based on Internet of Things

Abstract

The invention discloses a remote equipment control method and system based on Internet of Things, and relates to the technical field of Internet of Things remote control, and the method comprises the steps: collecting the operation state parameters of remote equipment in real time through an Internet of Things sensor, and carrying out the preprocessing; constructing operation energy consumption detection characteristics according to the preprocessed operation state parameters, and calculating an operation energy consumption coefficient; the remote devices are sorted in an ascending order according to the operation energy consumption coefficients, and workload distribution control is carried out according to the ascending order; constructing operation state detection features according to the preprocessed operation state parameters, and calculating an operation state coefficient; and sorting the remote equipment in a descending order according to the operation state coefficient, stopping the remote equipment greater than a preset threshold value, and redistributing the corresponding workload according to the operation energy consumption coefficient. Through intelligent monitoring and dynamic control based on the Internet of Things, intelligent workload distribution is realized, the operation efficiency is improved, dynamic workload redistribution is provided, and the energy efficiency and reliability of equipment are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things remote control, and in particular to a remote device control method and system based on the Internet of Things. Background Art

[0002] With the rapid development of Internet of Things technology, more and more devices are connected to the network and are efficiently managed through remote control. However, the existing remote device management methods have certain limitations, which are mainly manifested as follows: Imperfect equipment energy consumption management: In the existing technology, although the equipment energy consumption can be managed by monitoring parameters such as voltage and current, there is a lack of in-depth analysis of characteristics such as equipment load changes and energy consumption fluctuations, which makes it difficult to achieve refined management in the energy consumption optimization and task allocation of multiple devices, resulting in waste of resources; Limited equipment operation status monitoring: Existing equipment monitoring methods mainly rely on a single operation status parameter, such as power or voltage. This method cannot fully reflect the fatigue status and operating efficiency of the equipment, resulting in excessive or underutilized equipment, shortening the service life of the equipment; Lack of intelligent workload allocation mechanism: Existing control systems usually lack intelligent evaluation of the current status and working capacity of the equipment, and cannot dynamically adjust in real time according to the equipment's operating energy consumption coefficient and operating status coefficient, which easily leads to overload operation of some equipment, while other equipment is idle, reducing the efficiency of the overall system. Summary of the invention

[0003] Based on the above-mentioned shortcomings of the prior art, the purpose of the present invention is to provide a remote device control method and system based on the Internet of Things to solve the above-mentioned technical problems.

[0004] To achieve the above object, the present invention provides the following technical solution: a remote device control method based on the Internet of Things, comprising:

[0005] Collect operating status parameters of remote devices in real time through IoT sensors and pre-process the operating status parameters;

[0006] Constructing an operation energy consumption detection feature according to the preprocessed operation state parameters, and calculating an operation energy consumption coefficient according to the operation energy consumption detection feature, wherein the operation energy consumption detection feature includes a load change feature and an energy consumption fluctuation feature;

[0007] Sorting the remote devices in ascending order according to the operating energy consumption coefficients, and performing workload distribution control in the ascending sequence;

[0008] Constructing an operation state detection feature according to the preprocessed operation state parameters, and calculating an operation state coefficient according to the operation state detection feature, wherein the operation state detection feature includes an operation efficiency feature and an equipment fatigue feature;

[0009] The remote devices are sorted in descending order according to the operating status coefficients, the remote devices whose operating status coefficients are greater than a preset threshold are shut down, and the corresponding workloads are redistributed according to the operating energy consumption coefficients.

[0010] The present invention is further configured such that the operating status parameters include voltage, current, load, energy consumption, power, ambient temperature, workload completion rate, working time and total operating time during operation.

[0011] The present invention is further configured to construct an operation energy consumption detection feature according to the preprocessed operation state parameters, and calculate an operation energy consumption coefficient according to the operation energy consumption detection feature, including:

[0012] calculating a load variation characteristic according to the voltage, the current and the load;

[0013] Calculating energy consumption fluctuation characteristics according to the energy consumption, the power and the ambient temperature;

[0014] An operating energy consumption coefficient is calculated according to the load variation characteristics and the energy consumption fluctuation characteristics.

[0015] The present invention is further configured such that the calculation logic of the load change characteristic is: Among them, RLCR is the load change characteristic, L current is the load at the current moment, L previous is the load of the previous time interval, V current is the current voltage, V rated is the rated voltage, I current is the current, I rated is the rated current;

[0016] The calculation logic of the energy consumption fluctuation characteristics is: Among them, EVC is the energy consumption fluctuation characteristic, E current is the current energy consumption, E previous is the energy consumption of the previous time interval, P current is the current power, P rated is the rated power, T current is the ambient temperature, T max is the maximum allowable ambient temperature of the equipment;

[0017] The calculation logic of the operating energy consumption coefficient is: Among them, CEC is the operating energy consumption coefficient, α, β and γ are adjustment coefficients, which are used to control the sensitivity and nonlinearity of the load change characteristics and the energy consumption fluctuation characteristics, and are all greater than zero.

[0018] The present invention is further configured to sort the remote devices in ascending order according to the operating energy consumption coefficients, and perform workload distribution control in the ascending sequence, including:

[0019] Acquire the maximum processing capacity and current available status of the remote device, wherein the current available status includes available and unavailable;

[0020] When the current available state is available, a preset proportion of the workload of the maximum processing capacity of the remote device is allocated in ascending order to complete the total workload allocation.

[0021] The present invention is further configured to construct an operation state detection feature according to the preprocessed operation state parameter, and calculate an operation state coefficient according to the operation state detection feature, including:

[0022] Calculating an operation efficiency characteristic according to the workload completion rate, the working time, and the load;

[0023] calculating a fatigue characteristic of the equipment based on the power and the total operating time;

[0024] An operating status coefficient is calculated based on the operating efficiency characteristics and the fatigue level of the remote device.

[0025] The present invention is further configured such that the calculation logic of the operation efficiency feature is: Among them, OEI is the operating efficiency characteristic, D current is the workload completion rate, T oper is working time, P rated is the rated power of the equipment, L current is the load at the current moment, C capacity is the rated load of the equipment;

[0026] The calculation logic of the equipment fatigue characteristics is: Among them, FD is the equipment fatigue characteristic, P dynamic is the average power, T total is the total running time;

[0027] The calculation logic of the operating state coefficient is: RSC = OEI δ ·e -ω·FD , where RSC is the operating state coefficient, δ and ω are adjustment coefficients, which are used to control the influence of the operating efficiency characteristics and the equipment fatigue characteristics, and are all greater than zero.

[0028] The present invention is further configured to shut down a remote device whose operating state coefficient is greater than a preset threshold, and redistribute the corresponding workload according to the operating energy consumption coefficient, including:

[0029] Collect the unfinished workload of all downtime remote devices and calculate the total workload to be redistributed;

[0030] The operating energy consumption coefficients of all currently non-shutdown remote devices are calculated, all the non-shutdown remote devices are sorted in ascending order according to the operating energy consumption coefficients, and the total workload to be reallocated is controlled according to the ascending sequence.

[0031] The present invention also provides a remote device control system based on the Internet of Things, the system comprising:

[0032] Parameter collection module: collects the operating status parameters of remote devices in real time through IoT sensors and pre-processes the operating status parameters;

[0033] The first feature module: constructs an operation energy consumption detection feature according to the preprocessed operation state parameters, and calculates an operation energy consumption coefficient according to the operation energy consumption detection feature, wherein the operation energy consumption detection feature includes a load change feature and an energy consumption fluctuation feature;

[0034] A first control module: sorting the remote devices in ascending order according to the operating energy consumption coefficients, and performing workload distribution control in the ascending sequence;

[0035] The second feature module: constructs an operation state detection feature according to the preprocessed operation state parameters, and calculates an operation state coefficient according to the operation state detection feature, wherein the operation state detection feature includes an operation efficiency feature and an equipment fatigue feature;

[0036] The second control module: sorts the remote devices in descending order according to the operating status coefficient, shuts down the remote devices whose operating status coefficient is greater than a preset threshold, and redistributes the corresponding workload according to the operating energy consumption coefficient.

[0037] The present invention provides a remote device control method and system based on the Internet of Things. The method collects the operating status parameters of the remote device in real time through the Internet of Things sensor, and pre-processes the operating status parameters; constructs an operating energy consumption detection feature according to the pre-processed operating status parameters, and calculates the operating energy consumption coefficient according to the operating energy consumption detection feature, wherein the operating energy consumption detection feature includes a load change feature and an energy consumption fluctuation feature; sorts the remote devices in ascending order according to the operating energy consumption coefficient, and performs workload distribution control according to the ascending sequence; constructs an operating status detection feature according to the pre-processed operating status parameters, and calculates the operating status coefficient according to the operating status detection feature, wherein the operating status detection feature includes an operating efficiency feature and an equipment fatigue feature; sorts the remote devices in descending order according to the operating status coefficient, shuts down the remote devices whose operating status coefficient is greater than a preset threshold, and redistributes the corresponding workload according to the operating energy consumption coefficient, and the beneficial effects produced include:

[0038] 1. Optimize equipment energy consumption management: By calculating the load change characteristics and energy consumption fluctuation characteristics, the present invention can accurately identify the load changes and energy consumption fluctuations during the operation of the equipment, thereby accurately calculating the equipment's operating energy consumption coefficient, optimizing the energy consumption distribution in a multi-equipment environment, avoiding excessive waste of equipment energy consumption, and improving the energy utilization rate of the overall system;

[0039] 2. Intelligent workload distribution: The present invention sorts the devices in ascending order based on their operating energy consumption coefficients and distributes the workload according to the load bearing capacity of the devices, effectively solving the problem of uneven equipment distribution in the prior art. The method can automatically adjust the work tasks according to the real-time status of the devices, ensuring that each device operates under a reasonable load, avoiding equipment overload or resource waste;

[0040] 3. Extending the service life of equipment: Through real-time monitoring and calculation of equipment operating efficiency characteristics and equipment fatigue characteristics, the present invention can intelligently evaluate the operating status of the equipment, sort the equipment in descending order according to the operating status coefficient, and promptly deactivate the equipment whose status coefficient is greater than the preset threshold. This method effectively avoids equipment failure and loss caused by excessive work and extends the service life of the equipment;

[0041] 4. Dynamic workload redistribution mechanism: When some equipment needs to be shut down for maintenance, the present invention can automatically and reasonably distribute the remaining workload to other equipment by calculating the workload to be reallocated and the operating energy consumption coefficient of all currently non-shutdown equipment, thereby ensuring that the overall work efficiency of the system is not affected. The dynamic redistribution mechanism improves the utilization rate of the equipment and reduces the system downtime.

[0042] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0044] Figure 1 A flowchart of a remote device control method based on the Internet of Things is shown as an exemplary embodiment of the present invention;

[0045] Figure 2 The schematic diagram is a structural diagram of a remote device control system based on the Internet of Things according to an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0046] The following will describe the embodiments of the present invention with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention, not for limiting the scope of protection of the present invention.

[0047] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0048] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it is obvious to those skilled in the art that the embodiments of the present invention can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present invention difficult to understand.

[0049] Embodiment 1

[0050] Remote device control methods based on the Internet of Things, such as Figure 1 As shown, including:

[0051] Collect operating status parameters of remote devices in real time through IoT sensors and pre-process the operating status parameters;

[0052] Constructing an operation energy consumption detection feature according to the preprocessed operation state parameters, and calculating an operation energy consumption coefficient according to the operation energy consumption detection feature, wherein the operation energy consumption detection feature includes a load change feature and an energy consumption fluctuation feature;

[0053] Sorting the remote devices in ascending order according to the operating energy consumption coefficients, and performing workload distribution control in the ascending sequence;

[0054] Constructing an operation state detection feature according to the preprocessed operation state parameters, and calculating an operation state coefficient according to the operation state detection feature, wherein the operation state detection feature includes an operation efficiency feature and an equipment fatigue feature;

[0055] The remote devices are sorted in descending order according to the operating status coefficients, the remote devices whose operating status coefficients are greater than a preset threshold are shut down, and the corresponding workloads are redistributed according to the operating energy consumption coefficients.

[0056] Specifically, IoT sensors are installed at key locations of remote devices to monitor the operating status parameters of the devices in real time. The present invention is further configured such that the operating status parameters include voltage, current, load, energy consumption, power, ambient temperature, workload completion rate, working hours and total operating time during operation; the voltage reflects the voltage level provided by the power system to the device, and the voltage stability affects the energy consumption and efficiency of the device. Voltage fluctuations may lead to increased energy consumption and decreased efficiency; current reflects the actual amount of electrical energy consumed by the equipment, and the magnitude of the current directly reflects the load condition of the equipment. Excessive current may mean that the equipment is overloaded. Current and voltage are used together to calculate power and energy consumption; load represents the workload or output requirements that the equipment bears during operation, including electrical load; energy consumption represents the total amount of energy consumed by the equipment during operation, and the energy consumption level is an important indicator for evaluating the operating efficiency of the equipment; power is the energy consumed or converted by the equipment per unit time, which represents the instantaneous energy consumption rate of the equipment; ambient temperature is the temperature of the environment in which the equipment is located; workload completion rate is the ratio of the workload completed by the equipment in a specific time to the total workload, expressed as a percentage; working time is the actual running time of the equipment when the equipment is performing the workload; total running time is the running time of the equipment when it is turned on, including standby time and working time; data preprocessing is used to improve data quality and provide a reliable data basis for subsequent analysis. It includes data cleaning: detecting and processing missing values, outliers and duplicate data, and repairing data defects by using interpolation, mean filling and other methods; data calibration: correcting the collected data according to the calibration parameters of the sensor to eliminate system errors; data synchronization and alignment: performing time synchronization and alignment for data from different sensors to ensure data consistency; data transformation: normalizing and standardizing the data as needed to eliminate the impact of different dimensions.

[0057] The present invention is further configured to construct an operation energy consumption detection feature according to the preprocessed operation state parameters, and calculate an operation energy consumption coefficient according to the operation energy consumption detection feature, including:

[0058] The load change characteristic is calculated according to the voltage, the current and the load; the present invention is further configured such that the calculation logic of the load change characteristic is: Among them, RLCR is the load change characteristic, L current is the load at the current moment, L previous is the load of the previous time interval, V current is the current voltage, V rated is the rated voltage, I currentis the current, I rated is the rated current; specifically, the load change characteristic is used to reflect the dynamic changes of load, voltage and current of the remote device during operation; the purpose is to quantify the load change of the remote device and analyze the operating characteristics of the device under different load conditions in combination with the electrical parameters of the device; Indicates the change ratio of the current load to the previous load, reflecting the dynamic fluctuation of the load. The greater the load change, the greater the ratio; The changes in voltage and current are combined to correct the impact of load changes. The load change feature combines the changes in load, voltage and current to more accurately monitor the load fluctuations of the equipment during operation, helping operation and maintenance personnel to detect abnormal load problems in a timely manner. By real-time monitoring of load and electrical parameters, the system can dynamically adjust the operating status of the equipment and optimize the energy efficiency performance of the equipment.

[0059] The energy consumption fluctuation characteristic is calculated according to the energy consumption, the power and the ambient temperature; the calculation logic of the energy consumption fluctuation characteristic is: Among them, EVC is the energy consumption fluctuation characteristic, E current is the current energy consumption, E previous is the energy consumption of the previous time interval, P current is the current power, P rated is the rated power, T current is the ambient temperature, T max is the maximum allowable ambient temperature of the equipment; specifically, the energy consumption fluctuation characteristic coefficient is used to reflect the energy consumption fluctuation of the equipment under different energy consumption, power and ambient temperature; Indicates the change ratio of the current energy consumption to the energy consumption at the previous moment. The larger the ratio, the greater the energy consumption fluctuation and the more significant the energy efficiency fluctuation of the equipment. It is used to measure the performance of the current operating power and ambient temperature of the equipment relative to the energy consumption fluctuation. By calculating the energy consumption fluctuation characteristics, the energy consumption fluctuation of the equipment can be monitored in real time and abnormal fluctuations in energy consumption can be identified.

[0060] The operation energy consumption coefficient is calculated according to the load change characteristics and the energy consumption fluctuation characteristics; the calculation logic of the operation energy consumption coefficient is: Among them, CEC is the operating energy consumption coefficient, α, β and γ are adjustment coefficients, which are used to control the sensitivity and nonlinearity of the load change characteristics and the energy consumption fluctuation characteristics, and are all greater than zero; specifically, the operating energy consumption coefficient is based on the load change characteristics and energy consumption fluctuation characteristics of the equipment, and is used to evaluate the energy consumption level of the equipment under specific operating conditions. Combined with the regulation of nonlinear functions, it can more accurately reflect the energy efficiency fluctuation of the equipment; by adjusting the coefficient α, the influence of the load change characteristics on the operating energy consumption coefficient is controlled. The greater the load change, the greater the load change characteristic value, indicating that the load fluctuation of the equipment is more frequent, and the energy consumption fluctuation will also be aggravated; by adjusting the coefficient β, the influence of the energy consumption fluctuation characteristics on the operating energy consumption coefficient is controlled. The greater the energy consumption fluctuation, the higher the energy consumption fluctuation characteristics, indicating that the energy efficiency performance of the equipment is unstable; the exponential function term e -γ×RLCR×EVC It reflects the combined effect of load and energy consumption fluctuations. By adjusting the value of the coefficient γ, the nonlinear attenuation speed can be adjusted to enhance or weaken the combined effect of load and energy consumption fluctuations; by combining the calculation of load change characteristics and energy consumption fluctuation characteristics, the operating energy consumption coefficient can accurately reflect the energy consumption fluctuation of the equipment during dynamic operation. Compared with simple energy consumption evaluation, this method is more flexible and comprehensive; the introduction of exponential functions makes the impact of load and energy consumption fluctuations on the operating energy consumption coefficient more sensitive. By adjusting γ, the impact of load and energy consumption fluctuations on the equipment can be effectively controlled to avoid damage to the equipment caused by excessive fluctuations.

[0061] The present invention is further configured to sort the remote devices in ascending order according to the operating energy consumption coefficients, and perform workload distribution control in the ascending sequence, including:

[0062] Acquire the maximum processing capacity and current available status of the remote device, wherein the current available status includes available and unavailable;

[0063] When the current available state is available, the workload of the preset proportion of the maximum processing capacity of the remote device is allocated in ascending order to complete the total workload allocation; specifically, the remote devices are sorted by the operation energy consumption coefficient, and the workload is allocated based on the maximum processing capacity and current available state of the device, with the purpose of optimizing the workload distribution of the device, reducing energy consumption, and improving the overall operation efficiency of the device; first, the operation state of each device is evaluated by the operation energy consumption coefficient, and the operation energy consumption coefficient reflects the energy efficiency and working stability of the device; according to the value of the operation energy consumption coefficient, the devices are sorted in ascending order from low to high; the device with a low operation energy consumption coefficient indicates that it has high operation energy efficiency and low energy consumption, and more workload is allocated preferentially; when determining the workload allocation, it is necessary to obtain the maximum processing capacity and the current available state of each remote device, and the maximum processing capacity indicates the processing upper limit of each device, that is, the maximum workload that it can handle under ideal conditions; the current available state indicates the real-time status information of the device, indicating whether the device can participate in the current workload allocation. The available state includes "available" and "unavailable"; by obtaining. The available state ensures that the workload is only allocated to devices that can operate normally, avoiding invalid allocation. According to the ranking results of the equipment's operating energy consumption coefficient, the workload is allocated in the preset proportion of the maximum processing capacity, starting from the equipment with the highest energy efficiency. The workload will be allocated to the equipment with high operating energy efficiency first until the total workload is allocated; by reasonably allocating the workload, the overall energy consumption is reduced and the utilization rate of the equipment is improved.

[0064] The present invention is further configured to construct an operation state detection feature according to the preprocessed operation state parameter, and calculate an operation state coefficient according to the operation state detection feature, including:

[0065] The operation efficiency feature is calculated according to the workload completion rate, the working time and the load; the present invention is further configured such that the calculation logic of the operation efficiency feature is: Among them, OEI is the operating efficiency characteristic, D current is the workload completion rate, T oper is working time, P rated is the rated power of the equipment, L current is the load at the current moment, C capacity is the rated load of the equipment; specifically, the operating efficiency feature is used to quantify the efficiency of the equipment in completing the task, and the operating status and working efficiency of the equipment are evaluated by combining the relationship between the workload completion rate, working time, and load and the rated load of the equipment; It is used to measure the amount of work that can be completed by the equipment at its rated power after a specified period of time, reflecting the production capacity of the equipment; Used to correct the impact of the load on the equipment's working efficiency during actual operation. The closer the load is to the rated value, the smaller the efficiency correction value. When the load is low, the equipment's operating efficiency is relatively high; the operating efficiency feature comprehensively reflects the equipment's working efficiency by combining the workload completion rate and load conditions. It helps identify which equipment has higher operating efficiency, thereby optimizing equipment scheduling; by correcting the equipment's load conditions, the operating efficiency feature can indicate whether the equipment is overloaded or underloaded. Reasonable load distribution helps extend the equipment's service life and prevents equipment failures due to overload;

[0066] The equipment fatigue characteristic is calculated according to the power and the total operating time; the calculation logic of the equipment fatigue characteristic is: Among them, FD is the equipment fatigue characteristic, P dynamic is the average power, T total is the total operating time; specifically, the equipment fatigue characteristics are used to measure the degree of fatigue of the equipment during long-term operation, reflecting the working intensity of the equipment and the changing trend of its operating status over time, which is helpful to predict the operating life and maintenance requirements of the equipment; by calculating the equipment fatigue characteristics, the fatigue degree of the equipment can be predicted, and the maintenance and replacement time of the equipment can be determined according to the accumulated fatigue value, thereby extending the equipment life and reducing the risk of sudden failures; the equipment fatigue characteristics can be used as a reference standard for preventive maintenance of the equipment. When the equipment fatigue value exceeds a certain threshold, the operation and maintenance personnel can be prompted to inspect and maintain the equipment to prevent sudden failures caused by excessive fatigue.

[0067] The operating state coefficient is calculated according to the operating efficiency characteristics and the fatigue of the remote device; the calculation logic of the operating state coefficient is: RSC = OEI δ ·e -ω·FD , where RSC is the operating status coefficient, δ and ω are adjustment coefficients, which are used to control the degree of influence of the operating efficiency characteristics and the equipment fatigue characteristics, and are both greater than zero; specifically, the operating status coefficient combines the operating efficiency characteristics and the equipment fatigue characteristics, and the operating status coefficient is used to comprehensively evaluate the overall status of the equipment under specific operating conditions, reflecting the operating efficiency of the equipment and the fatigue level of the equipment; by combining the operating efficiency and fatigue characteristics, the operating status coefficient provides an indicator for comprehensively evaluating the operating status of the equipment, which can not only reflect the current efficiency of the equipment, but also reflect the accumulated fatigue of the equipment, thereby comprehensively evaluating the health status of the equipment; the operating status coefficient can help operation and maintenance personnel monitor the operating status of the equipment in real time. When the operating status coefficient gradually decreases, it indicates that the equipment operating efficiency is reduced or the fatigue accumulation is large, indicating that maintenance or workload adjustment is required.

[0068] The present invention is further configured to shut down a remote device whose operating state coefficient is greater than a preset threshold, and redistribute the corresponding workload according to the operating energy consumption coefficient, including:

[0069] Collect the unfinished workload of all downtime remote devices and calculate the total workload to be redistributed;

[0070] Calculate the operating energy consumption coefficients of all currently non-shutdown remote devices, sort all non-shutdown remote devices in ascending order according to the operating energy consumption coefficients, and control the allocation of the total workload to be reallocated in ascending sequence; specifically, shut down devices whose operating status coefficients are greater than a preset threshold, and reallocate the unfinished workload of the shut down devices to the remaining devices according to the operating energy consumption coefficients, thereby optimizing the equipment operation management. The above logic ensures that the equipment in the system is always in the best working state by real-time monitoring of the equipment's operating status and energy consumption, and can promptly redistribute the workload when the equipment fails or is inefficient, to ensure efficient completion of work tasks.

[0071] Embodiment 2

[0072] See also Figure 2 , the exemplary remote device control system based on the Internet of Things includes:

[0073] Parameter collection module: collects the operating status parameters of remote devices in real time through IoT sensors and pre-processes the operating status parameters;

[0074] The first feature module: constructs an operation energy consumption detection feature according to the preprocessed operation state parameters, and calculates an operation energy consumption coefficient according to the operation energy consumption detection feature, wherein the operation energy consumption detection feature includes a load change feature and an energy consumption fluctuation feature;

[0075] A first control module: sorting the remote devices in ascending order according to the operating energy consumption coefficients, and performing workload distribution control in the ascending sequence;

[0076] The second feature module: constructs an operation state detection feature according to the preprocessed operation state parameters, and calculates an operation state coefficient according to the operation state detection feature, wherein the operation state detection feature includes an operation efficiency feature and an equipment fatigue feature;

[0077] The second control module: sorts the remote devices in descending order according to the operating status coefficient, shuts down the remote devices whose operating status coefficient is greater than a preset threshold, and redistributes the corresponding workload according to the operating energy consumption coefficient.

[0078] It should be noted that the remote device control system based on the Internet of Things provided in the above embodiment and the remote device control method based on the Internet of Things provided in the above embodiment belong to the same concept, wherein the specific manner in which each module and unit performs the operation has been described in detail in the method embodiment and will not be repeated here. In actual application, the remote device control system based on the Internet of Things provided in the above embodiment can distribute the above functions to different functional modules as needed, that is, divide the internal structure of the system into different functional modules to complete all or part of the functions described above, and this is not limited here.

[0079] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0080] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0081] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0082] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0083] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0084] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0085] In the several embodiments provided in the present application, it should be understood that the disclosed system can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0086] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0087] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0088] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0089] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A remote device control method based on the Internet of Things, characterized in that: include: Collect operating status parameters of remote devices in real time through IoT sensors and pre-process the operating status parameters; Constructing an operation energy consumption detection feature according to the preprocessed operation state parameters, and calculating an operation energy consumption coefficient according to the operation energy consumption detection feature, wherein the operation energy consumption detection feature includes a load change feature and an energy consumption fluctuation feature; Sorting the remote devices in ascending order according to the operating energy consumption coefficients, and performing workload distribution control in the ascending sequence; Constructing an operation state detection feature according to the preprocessed operation state parameters, and calculating an operation state coefficient according to the operation state detection feature, wherein the operation state detection feature includes an operation efficiency feature and an equipment fatigue feature; The remote devices are sorted in descending order according to the operating status coefficients, the remote devices whose operating status coefficients are greater than a preset threshold are shut down, and the corresponding workloads are redistributed according to the operating energy consumption coefficients.

2. The remote device control method based on the Internet of Things according to claim 1, characterized in that: The operating status parameters include voltage, current, load, energy consumption, power, ambient temperature, workload completion rate, working time and total operating time during operation.

3. The remote device control method based on the Internet of Things according to claim 2 is characterized in that: Constructing an operation energy consumption detection feature according to the preprocessed operation state parameters, and calculating an operation energy consumption coefficient according to the operation energy consumption detection feature, including: calculating a load variation characteristic according to the voltage, the current and the load; Calculating energy consumption fluctuation characteristics according to the energy consumption, the power and the ambient temperature; An operating energy consumption coefficient is calculated according to the load variation characteristics and the energy consumption fluctuation characteristics.

4. The remote device control method based on the Internet of Things according to claim 3 is characterized in that: The calculation logic of the load change characteristic is: Among them, RLCR is the load change characteristic, L current is the load at the current moment, L previous is the load of the previous time interval, V current is the current voltage, V rated is the rated voltage, I current is the current, I rated is the rated current; The calculation logic of the energy consumption fluctuation characteristics is: Among them, EVC is the energy consumption fluctuation characteristic, E current is the current energy consumption, E previous is the energy consumption of the previous time interval, P current is the current power, P rated is the rated power, T current is the ambient temperature, T max is the maximum allowable ambient temperature of the equipment; The calculation logic of the operating energy consumption coefficient is: Among them, CEC is the operating energy consumption coefficient, α, β and γ are adjustment coefficients, which are used to control the sensitivity and nonlinearity of the load change characteristics and the energy consumption fluctuation characteristics, and are all greater than zero.

5. The remote device control method based on the Internet of Things according to claim 4 is characterized in that: The remote devices are sorted in ascending order according to the operating energy consumption coefficients, and workload distribution control is performed according to the ascending sequence, including: Acquire the maximum processing capacity and current available status of the remote device, wherein the current available status includes available and unavailable; When the current available state is available, a preset proportion of the workload of the maximum processing capacity of the remote device is allocated in ascending order to complete the total workload allocation.

6. The remote device control method based on the Internet of Things according to claim 2, characterized in that: Constructing an operation state detection feature according to the preprocessed operation state parameters, and calculating an operation state coefficient according to the operation state detection feature, including: Calculating an operation efficiency characteristic according to the workload completion rate, the working time, and the load; calculating a fatigue characteristic of the equipment based on the power and the total operating time; An operating status coefficient is calculated based on the operating efficiency characteristics and the fatigue level of the remote device.

7. The remote device control method based on the Internet of Things according to claim 6, characterized in that: The calculation logic of the operation efficiency feature is: Among them, OEI is the operating efficiency characteristic, D current is the workload completion rate, T oper is working time, P rated is the rated power of the equipment, L current is the load at the current moment, C capacity is the rated load of the equipment; The calculation logic of the equipment fatigue characteristics is: Among them, FD is the equipment fatigue characteristic, P dynamic is the average power, T total is the total running time; The calculation logic of the operating state coefficient is: RSC = OEI δ ·e -ω·FD , where RSC is the operating state coefficient, δ and ω are adjustment coefficients, which are used to control the influence of the operating efficiency characteristics and the equipment fatigue characteristics, and are all greater than zero.

8. The remote device control method based on the Internet of Things according to claim 5, characterized in that: The remote devices whose operating status coefficient is greater than the preset threshold are shut down, and the corresponding workload is redistributed according to the operating energy consumption coefficient, including: Collect the unfinished workload of all downtime remote devices and calculate the total workload to be redistributed; The operating energy consumption coefficients of all currently non-shutdown remote devices are calculated, all the non-shutdown remote devices are sorted in ascending order according to the operating energy consumption coefficients, and the total workload to be reallocated is controlled according to the ascending sequence.

9. A remote device control system based on the Internet of Things, characterized in that: include: Parameter collection module: collects the operating status parameters of remote devices in real time through IoT sensors and pre-processes the operating status parameters; The first feature module: constructs an operation energy consumption detection feature according to the preprocessed operation state parameters, and calculates an operation energy consumption coefficient according to the operation energy consumption detection feature, wherein the operation energy consumption detection feature includes a load change feature and an energy consumption fluctuation feature; A first control module: sorting the remote devices in ascending order according to the operating energy consumption coefficients, and performing workload distribution control in the ascending sequence; The second feature module: constructs an operation state detection feature according to the preprocessed operation state parameters, and calculates an operation state coefficient according to the operation state detection feature, wherein the operation state detection feature includes an operation efficiency feature and an equipment fatigue feature; The second control module: sorts the remote devices in descending order according to the operating status coefficient, shuts down the remote devices whose operating status coefficient is greater than a preset threshold, and redistributes the corresponding workload according to the operating energy consumption coefficient.

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