CN110891091A

CN110891091A - Block chain-based equipment control method and device and server

Info

Publication number: CN110891091A
Application number: CN201911223553.2A
Authority: CN
Inventors: 丁奇娜
Original assignee: Individual
Current assignee: Guangdong Aofei Data Technology Co ltd
Priority date: 2019-12-03
Filing date: 2019-12-03
Publication date: 2020-03-17
Anticipated expiration: 2039-12-03
Also published as: CN110891091B; CN111526213A; CN111552203A

Abstract

The embodiment of the application provides a device control method, a device and a server based on a block chain, wherein a device control strategy corresponding to current device state information is sequentially determined according to a node participation sequence of each participation node through the pre-established block chain, then a strategy execution process control curve is determined according to a device control association condition between control item type nodes matched with the device state information after first item type information of a control item type matched with the device state information in a relative device control strategy is determined, then second item type information is further determined, a target device control strategy is determined from the device control strategy to carry out device control after the second item type information is combined, so that the integral state expression of the device control state and the differential expression among different item types are effectively considered, and the control deviation of the actual equipment control process is reduced.

Description

Block chain-based equipment control method and device and server

Technical Field

The present application relates to the technical field of device control, and in particular, to a device control method, apparatus and server based on a block chain.

Background

In a traditional equipment control scheme, parameters under a certain item type in equipment to be controlled are adjusted and controlled usually based on an equipment control state, but the scheme only adopts simple corresponding relation matching or deep learning matching when equipment control strategies are matched, does not consider integral state expression of the equipment control state, and does not consider difference expression between different item types, so that not only control deviation is caused in an actual equipment control process, but also each control process can be wrongly learned, and the deviation becomes more and more obvious.

Disclosure of Invention

In order to overcome at least the above-mentioned deficiencies in the prior art, the present application aims to provide a device control method, apparatus and server based on a blockchain, wherein a device control policy corresponding to current device state information is sequentially determined according to a node participation order of each participating node through a pre-established blockchain, then a policy execution process control curve is determined by determining a first item type information of a control item type matching the device state information in a relative device control policy, further according to a device control association condition between the control item type nodes matching the device state information, then a second item type information is further determined, and a target device control policy is determined from the device control policy for device control after combining the second item type information, so as to effectively consider an integral state expression of the device control state and a differential expression between different item types, and the control deviation of the actual equipment control process is reduced.

In a first aspect, the present application provides a device control method based on a blockchain, which is applied to a server, where the server is in communication connection with at least one device to be controlled, and the method includes:

adding the equipment state information into a pre-established block chain corresponding to the equipment to be controlled according to the equipment state information uploaded by each piece of equipment to be controlled, and sequentially determining an equipment control strategy corresponding to the current equipment state information in the block chain according to the node participation sequence of each participation node;

determining a relative device control strategy from the device control strategies related to the device state information and in which the node participation sequence in the device state information is in front of the determined device control strategy, and acquiring first item type information of a control item type matched with the device state information in the relative device control strategy;

performing equipment control association processing on the equipment control strategy according to the equipment control association condition between the first item type information and the control item type node matched with the equipment state information to obtain a strategy execution process control curve of the equipment control strategy;

and obtaining second item type information of the control item type matched with the equipment state information according to the strategy execution process control curve, extracting control characteristic information of a target equipment control strategy from the strategy execution process control curve, and determining the target equipment control strategy from the equipment control strategy according to the control characteristic information and the second item type information.

In a possible design of the first aspect, the step of performing device control association processing on the device control policy according to a device control association between the first item type information and a control item type node matched with the device state information to obtain a policy execution process control curve of the device control policy includes:

acquiring strategy association information of the equipment control strategy according to the equipment control association condition between the first item type information and the control item type node matched with the equipment state information; processing the strategy associated information into strategy associated nodes;

parallelly inputting each strategy association node into each preconfigured strategy association model, wherein the strategy association nodes are used for indicating the corresponding strategy association models to generate first strategy association results corresponding to the strategy association nodes, and the strategy association nodes are also used for indicating the corresponding strategy association models to respectively generate parameter association data columns and process association data columns;

extracting parameter associated features from each parameter associated data of the parameter associated data column and extracting process associated features from each process associated data of the process associated data column respectively;

analyzing each parameter association characteristic and the process association characteristic to obtain a first strategy association result corresponding to the strategy association node, eliminating redundant strategy association results in the first strategy association results output by each strategy association model, and generating a second strategy association result corresponding to the strategy association information in a combined mode according to the strategy association results left after the redundant strategy association results are eliminated;

and performing equipment control association processing on the equipment control strategy according to the second strategy association result to obtain a strategy execution process control curve of the equipment control strategy.

In a possible design of the first aspect, the step of performing device control association processing on the device control policy according to the second policy association result to obtain a policy execution process control curve of the device control policy includes:

acquiring the number of the policy association features included in the second policy association result;

judging the quantity of the strategy association features included in the second strategy association result and the quantity relation between the first set quantity and the second set quantity, wherein the first set quantity is larger than the second set quantity;

if the number of the strategy associated features included in the second strategy associated result is less than or equal to the second set number, determining that the theoretical value of the feature identification parameter expression value of the second strategy associated result is a first preset feature identification parameter value;

if the number of the policy associated features included in the second policy associated result is greater than the second set number and less than or equal to the first set number, calculating a theoretical value of a feature identification parameter expression value of the second policy associated result according to a first set model, wherein the number of the policy associated features included in the second policy associated result is an input part of the first set model, the theoretical value of the feature identification parameter expression value of the second policy associated result is an output part of the first set model, and in the first set model, the larger the number of the policy associated features included in the second policy associated result is, the larger the theoretical value of the feature identification parameter expression value of the second policy associated result is;

if the number of policy association features included in the second policy association result is greater than the first set number, calculating a theoretical value of the feature identification parameter expression value of the second policy association result according to a second set model, wherein the number of the policy association features included in the second policy association result is an input part of the second setting model, the theoretical value of the characteristic identification parameter expression value of the second strategy correlation result is the output part of the second setting model, in the second setting model, the larger the number of the policy associated features included in the second policy associated result is, the smaller the theoretical value of the feature identification parameter expression value of the second policy associated result is, wherein the associated feature value of the second policy association result is a trade-off value between the feature identification parameter of the associated feature and the feature identification parameter of the non-associated feature in the second policy association result;

calculating a compensation correlation value of the second policy correlation result according to a theoretical value of a correlation characteristic value of the second policy correlation result and a correlation characteristic value of a last policy correlation characteristic of the second policy correlation result, wherein the compensation correlation value is used for performing compensation updating on a target correlation policy for controlling a correlation position in the second policy correlation result, and the correlation characteristic value of the last policy correlation characteristic is a balance value between an average value of application characteristic identification parameters of non-correlation characteristics in the last policy correlation characteristic and an average value of application characteristic identification parameters of correlation characteristics in the last policy correlation characteristic;

acquiring a target association policy of a control association position in the second policy association result according to the compensation association value, wherein the target association policy of the control association position is used for performing control association processing on the equipment control policy;

and performing control association processing on the equipment control strategy according to the target association strategy to obtain a strategy execution process control curve of the equipment control strategy.

In a possible design of the first aspect, the step of performing control association processing on the device control policy according to the target association policy to obtain a policy-implemented process control curve of the device control policy includes:

sequentially acquiring data to be associated and processed corresponding to a target association sub-strategy corresponding to each item type in the target association strategy, wherein the data to be associated and processed corresponding to the target association sub-strategy comprises a plurality of control association models;

sequentially acquiring a control association model of current to-be-controlled association in data to be associated and processed corresponding to the target association sub-strategy, if the control association model of the current to-be-controlled association comprises control association nodes, acquiring the position of a parameter control unit of parameter control information of the equipment control strategy in a first traversal item type, calculating the position of the control association model of the parameter control information of the equipment control strategy in the first traversal item type according to the position of the parameter control unit of the parameter control information of the equipment control strategy in the first traversal item type, calculating control association model call information of the parameter control information of the equipment control strategy in the first traversal item type according to the position of the control association model of the parameter control information of the equipment control strategy in the first traversal item type, and/or acquiring process node information of control associated data feature points in the control associated nodes, acquiring process control feature vectors of process node sets of process control information from the control associated data feature points to the equipment control strategy in a second traversal project type, calculating set position information of the process node sets according to the process control feature vectors and the process node information, and calculating control associated model call information of the set position information in the second traversal project type;

acquiring control association model calling information of past control association of a target association sub-strategy corresponding to the first traversal item type, and/or acquiring past control association model calling information in a target association sub-strategy corresponding to the second traversal item type;

if the control association model calling information of past control association in the target association sub-strategy corresponding to the first traversal item type matches the control association model calling information of the equipment control strategy in the target association sub-strategy corresponding to the first traversal item type, and/or the control association model calling information of past control association in the target association sub-strategy corresponding to the second traversal item type matches the control association model calling information of the process control information of the equipment control strategy in the target association sub-strategy corresponding to the second traversal item type, performing control association processing on the current control association model to be controlled and the equipment control strategy, and judging whether the number of control association nodes of the current control association model to be controlled is greater than the number of preset control association models;

if the number of control associated nodes of the control associated model to be currently controlled and associated is larger than the number of preset control associated models, acquiring the control associated model to be currently called and processed, and calling the control associated model to be currently called and processed;

judging whether the control correlation model calling information of the current control correlation model to be correlated is matched with the control correlation model calling information of the last control correlation model in the correlation data to be controlled corresponding to the item type;

if the control associated model calling information of the current control associated model matches the control associated model calling information of the last control associated model in the associated data to be controlled corresponding to the item type, acquiring all control associated models which are not called and processed in the associated data to be controlled corresponding to the item type, and calling all control associated models which are not called and processed in the associated data to be controlled corresponding to the item type in sequence;

if the control associated model calling information currently in control association in the first traversal item type does not match the control associated model calling information of the parameter control information of the device control strategy in the first traversal item type, and/or the control associated model calling information currently in call processing in the second traversal item type does not match the control associated model calling information of the process control information of the device control strategy in the second traversal item type, waiting for the control association of the first traversal item type and/or waiting for the call processing of the second traversal item type until the control associated model calling information currently in control association in the first traversal item type matches the control associated model calling information of the parameter control information of the device control strategy in the first traversal item type, and/or the control associated model call information currently being called and processed in the second traversal item type is matched with the process control information of the equipment control strategy until the control associated model call information in the second traversal item type;

if the control associated model of the current to-be-controlled association does not comprise a control associated node, performing control association on the control associated model of the current to-be-controlled association, judging whether control associated model calling information of the control associated model of the current to-be-controlled association matches a preset control associated model number or control associated model calling information of the last control associated model in the to-be-controlled associated data corresponding to the project type, if the control associated model calling information of the control associated model of the current to-be-controlled association matches the preset control associated model number, acquiring the control associated model of the current to-be-called processing, and calling the control associated model of the current to-be-called processing; the difference value between the current control correlation model calling information to be controlled and correlated in the correlation data to be controlled corresponding to the item type and the current control correlation model calling information to be called and processed in the correlation data to be controlled corresponding to the item type is the preset control correlation model number; if the control associated model calling information of the current control associated model matches the control associated model calling information of the last control associated model in the associated data to be controlled corresponding to the item type, all control associated models which are not called and processed in the associated data to be controlled corresponding to the item type are obtained, and all control associated models which are not called and processed in the associated data to be controlled corresponding to the item type are called and processed in sequence.

In a possible design of the first aspect, the step of obtaining second item type information of a control item type that matches the device state information according to the policy-enforcement process control curve includes:

extracting a strategy execution position, a strategy execution mode and a strategy execution control command in the strategy execution process control curve;

after the strategy execution position is extracted, acquiring type information to be acquired of the control item type matched with the equipment state information according to the strategy execution position;

acquiring a policy execution path corresponding to the policy execution mode and an information execution path of the type information to be acquired;

judging whether the information execution path of the type information to be acquired is larger than the strategy execution path or not, if the information execution path of the type information to be acquired is judged to be matched with the strategy execution path, acquiring the execution process information corresponding to the information execution path from the type information to be acquired, and correspondingly configuring the execution process path corresponding to the execution process information and the strategy execution mode;

searching an execution process path corresponding to the strategy execution mode, and determining a command image file corresponding to the strategy execution control command;

searching a command operation set corresponding to the command mirror image file, and after acquiring an operation command corresponding to the policy execution control command from the searched command operation set, performing operation processing on the type information to be acquired according to the operation command;

and searching the execution process information corresponding to the execution process path, and writing the type information to be acquired after operation processing into the searched execution process information to obtain second item type information of the control item type matched with the equipment state information.

In a possible design of the first aspect, the step of extracting the control feature information of the target device control policy from the policy execution process control curve includes:

acquiring a dimension coordinate corresponding to a strategy dimension coordinate in the target equipment control strategy currently in a strategy execution process control curve as each first dimension coordinate, and determining a coordinate label of the first dimension coordinate;

when the coordinate label of the first-dimension coordinate represents that the first-dimension coordinate is a control feature coordinate, writing the first-dimension coordinate into a control feature sequence;

when the first dimension coordinate is not a control feature coordinate, writing the first dimension coordinate into a non-control feature sequence;

determining whether the control feature sequence stores dimensional coordinates or not, and when the control feature sequence stores the dimensional coordinates, acquiring sequence mark coordinates of the control feature sequence as second dimensional coordinates;

determining whether the control features corresponding to the second-dimension coordinates have unmarked features or not, wherein when the features are marked, the control features are characterized to be used for control;

determining whether the sequence of non-control features includes only the first dimension coordinate when there are no unmarked features after the second dimension coordinate;

when the non-control feature sequence only comprises the first dimension coordinate, extracting the second dimension coordinate from the control feature sequence, emptying the non-control feature sequence, and transferring the first dimension coordinate to the next dimension coordinate to be detected to obtain each extracted second dimension coordinate;

extracting control feature spaces corresponding to all the second-dimension coordinates in a preset time length according to the extracted second-dimension coordinates, grouping the control feature spaces according to different control types, calculating the control feature space grade of each control type in a preset time period, and selecting corresponding control feature identification nodes according to the control feature space grade;

setting a plurality of node control code rows corresponding to each control feature identification node according to the selected control feature identification node corresponding to the control feature space, and dividing each node control code row into a control type code row, a non-control type code row, a maintenance type code row and a non-maintenance type code row;

in each node control code line, sequencing according to the time sequence called by the node control code line for the last time to obtain a time sequence characteristic sequence corresponding to each node control code line set, wherein the node control code line with the calling time for the last time closest to the current time in the time sequence characteristic sequence is used as a first node control code line, and the node control code line with the calling time for the last time farthest from the current time is used as a second node control code line;

sequentially detecting time sequence characteristic sequences of a control type code line, a non-control type code line, a maintenance type code line and a non-maintenance type code line, if a first non-space-time sequence characteristic sequence is detected, removing a node control code line at the position of a second node control code line in the time sequence characteristic sequence, and regenerating a corresponding time sequence characteristic sequence for a node control code line set corresponding to the time sequence characteristic sequence;

and obtaining the control characteristic information of the target equipment control strategy according to the timing sequence characteristic sequence corresponding to each regenerated node control code line set.

In a possible design of the first aspect, the determining the target device control policy from the device control policies according to the control feature information and the second item type information includes:

respectively constructing a first strategy model for controlling characteristic information and a second strategy model for controlling the second item type information;

adopting a first strategy model of the control characteristic information to construct a strategy execution model of the control characteristic information, and simultaneously adopting a second strategy model of the second item type information to construct a strategy execution model of the second item type information;

representing the control feature space of the control feature information by adopting the strategy execution model of the control feature information, and simultaneously representing the control feature space of the second item type information by adopting the strategy execution model of the second item type information;

preliminarily detecting the strategy execution node of the control feature information in the control feature space of the control feature information, and simultaneously preliminarily detecting the strategy execution node of the second item type information in the control feature space of the second item type information to obtain a strategy execution node sequence of the control feature information in the control feature space and a strategy execution node sequence of the second item type information in the control feature space;

removing unstable strategy executing nodes from the strategy executing node sequence of the control characteristic information in the control characteristic space, and removing unstable strategy executing nodes from the strategy executing node sequence of the second item type information in the control characteristic space to obtain target strategy executing nodes of the control characteristic information and target strategy executing nodes of the second item type information;

respectively determining a strategy main executing process of a target strategy executing node of the control characteristic information and a strategy main executing process of a target strategy executing node of the second item type information to obtain a target strategy executing node process of the control characteristic information and a target strategy executing node process of the second item type information;

adopting the target strategy execution node process of the control characteristic information to calculate target strategy execution node process metadata corresponding to the target strategy execution node process of the control characteristic information, and simultaneously adopting the target strategy execution node process of the second item type information to calculate target strategy execution node process metadata corresponding to the target strategy execution node process of the second item type information to obtain the target strategy execution node process metadata of the control characteristic information and the target strategy execution node process metadata of the second item type information;

performing initial matching on the control feature information and the second item type information according to the target strategy execution node process metadata of the control feature information and the target strategy execution node process metadata of the second item type information to obtain a matching strategy execution node pair of the control feature information and the second item type information;

determining matching parameters of the control feature information and the second item type information according to the matching strategy execution node pair of the control feature information and the second item type information;

and determining the target equipment control strategy from the equipment control strategies according to the matching parameters of the control characteristic information and the second item type information.

In a second aspect, an embodiment of the present application further provides an apparatus for controlling a device based on a block chain, where the apparatus is applied to a server, and the server is in communication connection with at least one device to be controlled, and the apparatus includes:

the adding module is used for adding the equipment state information into a pre-established block chain corresponding to the equipment to be controlled according to the equipment state information uploaded by each piece of equipment to be controlled, and sequentially determining an equipment control strategy corresponding to the current equipment state information in the block chain according to the node participation sequence of each participation node;

a determining and obtaining module, configured to determine a relative device control policy from device control policies associated with the device state information and in which a node participation order in the device state information is before the determined device control policy, and obtain first item type information of a control item type that matches the device state information in the relative device control policy;

the control association module is used for performing equipment control association processing on the equipment control strategy according to the equipment control association condition between the first item type information and the control item type node matched with the equipment state information to obtain a strategy execution process control curve of the equipment control strategy;

and the strategy determining module is used for obtaining second item type information of the control item type matched with the equipment state information according to the strategy execution process control curve, extracting control characteristic information of a target equipment control strategy from the strategy execution process control curve, and determining the target equipment control strategy from the equipment control strategy according to the control characteristic information and the second item type information.

In a third aspect, an embodiment of the present application further provides a server, where the server includes a processor, a machine-readable storage medium, and a network interface, where the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is configured to be communicatively connected to at least one device to be controlled, the machine-readable storage medium is configured to store a program, an instruction, or code, and the processor is configured to execute the program, the instruction, or the code in the machine-readable storage medium to perform the method for controlling a device based on a block chain in any one of possible designs of the first aspect or the first aspect.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the instructions are detected on a computer, the computer is caused to execute the method for controlling a device based on a blockchain in the first aspect or any one of the possible designs of the first aspect.

Based on any one of the above aspects, the present application determines the device control policy corresponding to the current device status information in sequence according to the node participation order of each participating node through a pre-established blockchain, and then determines the first item type information of the control item type matching the device status information in the relative device control policy, further according to the device control association between the control item type nodes matched with the device state information, determining a policy enforcement process control curve, and thereafter further determining second item type information, and determines a target device control strategy from the device control strategies to carry out device control after combining the second item type information, therefore, the overall state expression of the control state of the equipment and the difference expression among different item types are effectively considered, and the control deviation of the actual equipment control process is reduced.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

Fig. 1 is a schematic application scenario diagram of a device control system based on a block chain according to an embodiment of the present application;

fig. 2 is a schematic flowchart of a device control method based on a blockchain according to an embodiment of the present disclosure;

FIG. 3 is a flowchart illustrating the sub-steps included in step S130 shown in FIG. 2;

fig. 4 is a functional block diagram of a device control apparatus based on a blockchain according to an embodiment of the present disclosure;

fig. 5 is a block diagram schematically illustrating a structure of a server for implementing the above device control method based on a block chain according to an embodiment of the present application.

Detailed Description

The present application will now be described in detail with reference to the drawings, and the specific operations in the method embodiments may also be applied to the apparatus embodiments or the system embodiments. In the description of the present application, "at least one" includes one or more unless otherwise specified. "plurality" means two or more. For example, at least one of A, B and C, comprising: a alone, B alone, a and B in combination, a and C in combination, B and C in combination, and A, B and C in combination. In this application, "/" means "or, for example, A/B may mean A or B; "and/or" herein is merely a relational expression describing a relational relationship relating target nuclear magnetic resonance apparatuses, and means that three relations may exist, for example, a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone.

Fig. 1 is an interaction diagram of a device control system 10 based on a blockchain according to an embodiment of the present application. The device control system 10 based on the blockchain may include a server 100 and a device 200 to be controlled communicatively connected to the server 100, and the server 100 may include a processor for executing instruction operations. The blockchain-based plant control system 10 shown in fig. 1 is only one possible example, and in other possible embodiments, the blockchain-based plant control system 10 may also include only a portion of the components shown in fig. 1 or may also include other components.

In some embodiments, the server 100 may be a single server or a group of servers. The set of operating servers may be centralized or distributed (e.g., the server 100 may be a distributed system). In some embodiments, the server 100 may be local or remote with respect to the device to be controlled 200. For example, the server 100 may access information stored in the device to be controlled 200 and a database, or any combination thereof, via a network. As another example, the server 100 may be directly connected to at least one of the device to be controlled 200 and a database to access information and/or data stored therein. In some embodiments, the server 100 may be implemented on a cloud platform; by way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud (community cloud), a distributed cloud, an inter-cloud, a multi-cloud, and the like, or any combination thereof. In some embodiments, the server 100 and the device to be controlled 200 may be implemented on an electronic device 200 having one or more components shown in fig. 2 in the embodiment of the present application.

In some embodiments, the server 100 may include a processor. The processor may process information and/or data related to the service request to perform one or more of the functions described herein. A processor may include one or more processing cores (e.g., a single-core processor (S) or a multi-core processor (S)). Merely by way of example, a Processor may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), an Application Specific Instruction Set Processor (ASIP), a Graphics Processing Unit (GPU), a Physical Processing Unit (PPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a microcontroller Unit, a reduced Instruction Set computer (reduced Instruction Set computer), a microprocessor, or the like, or any combination thereof.

The network may be used for the exchange of information and/or data. In some embodiments, one or more components (e.g., the server 100, the device to be controlled 200, and the database) in the blockchain based device control system 10 may send information and/or data to other components. In some embodiments, the network may be any type of wired or wireless network, or combination thereof. Merely by way of example, Network 130 may include a wired Network, a Wireless Network, a fiber optic Network, a telecommunications Network, an intranet, the internet, a Local Area Network (LAN), a Wide Area Network (WAN), a Wireless Local Area Network (WLAN), a WLAN, a Metropolitan Area Network (MAN), a Wide Area Network (WAN), a Public Switched Telephone Network (PSTN), a bluetooth Network, a ZigBee Network, a Near Field Communication (NFC) Network, or the like, or any combination thereof. In some embodiments, the network may include one or more network access points. For example, the network may include wired or wireless network access points, such as base stations and/or network switching nodes, through which one or more components of the blockchain-based device control system 10 may connect to the network to exchange data and/or information.

The aforementioned database may store data and/or instructions. In some embodiments, the database may store data obtained from the device to be controlled 200. In some embodiments, the database may store data and/or instructions for the exemplary methods described herein. In some embodiments, the database may include mass storage, removable storage, volatile Read-write Memory, or Read-Only Memory (ROM), among others, or any combination thereof. By way of example, mass storage may include magnetic disks, optical disks, solid state drives, and the like; removable memory may include flash drives, floppy disks, optical disks, memory cards, zip disks, tapes, and the like; volatile read-write memory may include Random Access Memory (RAM); the RAM may include Dynamic RAM (DRAM), Double data Rate Synchronous Dynamic RAM (DDR SDRAM); static RAM (SRAM), Thyristor-Based Random Access Memory (T-RAM), Zero-capacitor RAM (Zero-RAM), and the like. By way of example, ROMs may include Mask Read-Only memories (MROMs), Programmable ROMs (PROMs), Erasable Programmable ROMs (PERROMs), Electrically Erasable Programmable ROMs (EEPROMs), compact disk ROMs (CD-ROMs), digital versatile disks (ROMs), and the like. In some embodiments, the database may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, across clouds, multiple clouds, or the like, or any combination thereof.

In some embodiments, a database may be connected to a network to communicate with one or more components in the blockchain based device control system 10 (e.g., server 100, device to be controlled 200, etc.). One or more components in blockchain-based device control system 10 may access data or instructions stored in a database via a network. In some embodiments, the database may be directly connected to one or more components in the blockchain based device control system 10 (e.g., the server 100, the device to be controlled 200, etc.); alternatively, in some embodiments, the database may also be part of the server 100.

The device to be controlled 200 may be used in a plurality of fields, for example, any implementable field such as control of smart machines, environmental protection device control, big data, artificial intelligence, network security, intelligent medical treatment, image detection processing, computer software technology, and the like, which is not specifically limited in this embodiment of the application.

To solve the technical problem in the foregoing background art, fig. 2 is a flowchart illustrating a device control method based on a block chain according to an embodiment of the present application, where the device control method based on a block chain according to the present application may be executed by the server 100 shown in fig. 1, and the device control method based on a block chain is described in detail below.

Step S110, according to the device state information uploaded by each device to be controlled 200, adding the device state information to a pre-established blockchain corresponding to the device to be controlled 200, and sequentially determining a device control policy corresponding to the current device state information in the blockchain according to the node participation order of each participating node.

Step S120, determining a relative device control policy from the device control policies associated with the device state information and in which the node participation sequence in the device state information is before the determined device control policy, and acquiring first item type information of a control item type matching the device state information in the relative device control policy.

And step S130, performing equipment control association processing on the equipment control strategy according to the equipment control association condition between the first item type information and the control item type node matched with the equipment state information to obtain a strategy execution process control curve of the equipment control strategy.

Step S140, obtaining second item type information of the control item type matched with the equipment state information according to the strategy execution process control curve, extracting the control characteristic information of the target equipment control strategy from the strategy execution process control curve, and determining the target equipment control strategy from the equipment control strategies according to the control characteristic information and the second item type information.

Based on the above steps, in this embodiment, a device control policy corresponding to current device state information is sequentially determined according to a node participation order of each participating node through a pre-established blockchain, then a policy execution process control curve is determined according to a device control association condition between control item type nodes matched with the device state information after first item type information of a control item type matched with the device state information in a relative device control policy is determined, then second item type information is further determined, and a target device control policy is determined from the device control policy for device control after the second item type information is combined, so that an overall state expression of a device control state and a differential expression between different item types are effectively considered, and a control deviation of an actual device control process is reduced.

In a possible design, regarding step S130, in the actual process, considering that there are many policy associated nodes, and there is a great difference in policy associated characteristics of different policy associated nodes, please further refer to fig. 3, step S130 may be further implemented by the following sub-steps:

and a substep S131 of obtaining policy associated information of the device control policy according to the device control associated condition between the first item type information and the control item type node matched with the device state information, and processing the policy associated information into a policy associated node.

And a substep S132 of inputting the policy associated nodes into the pre-configured policy associated models in parallel, wherein the policy associated nodes are used for indicating the corresponding policy associated models to generate first policy associated results corresponding to the policy associated nodes, and the policy associated nodes are also used for indicating the corresponding policy associated models to respectively generate parameter associated data columns and process associated data columns.

Substep S133 extracts the parameter associated feature from each parameter associated data of the parameter associated data column and the process associated feature from each process associated data of the process associated data column, respectively.

And a substep S134, analyzing each parameter association characteristic and the process association characteristic to obtain a first strategy association result corresponding to the strategy association node, eliminating redundant strategy association results in the first strategy association results output by each strategy association model, and generating a second strategy association result corresponding to the strategy association information in a combined manner according to the strategy association results left after the redundant strategy association results are eliminated.

And a substep S135, performing equipment control association processing on the equipment control strategy according to the second strategy association result to obtain a strategy execution process control curve of the equipment control strategy.

Based on the above steps, the present embodiment further considers a plurality of policy associated nodes, and the policy associated features of different policy associated nodes have a large difference, so through the above design, not only the processing efficiency can be improved, but also the difference expression of different policy associated nodes can be further considered, thereby reducing the control deviation of the actual device control process.

In one possible design, for the sub-step S135, in order to fully consider the difference between the numbers in the process of performing the device control association processing, and further reduce the control deviation of the actual device control process, in the implementation process, the number of the policy association features included in the second policy association result may be specifically obtained, and the relationship between the number of the policy association features included in the second policy association result and the number of the first set number and the second set number is determined, where the first set number is greater than the second set number.

And if the number of the strategy associated features included in the second strategy associated result is less than or equal to a second set number, determining the theoretical value of the feature identification parameter expression value of the second strategy associated result as a first preset feature identification parameter value.

And if the quantity of the strategy associated features included in the second strategy associated result is greater than a second set quantity and less than or equal to a first set quantity, calculating a theoretical value of the feature identification parameter expression value of the second strategy associated result according to the first set model, wherein the quantity of the strategy associated features included in the second strategy associated result is an input part of the first set model, the theoretical value of the feature identification parameter expression value of the second strategy associated result is an output part of the first set model, and in the first set model, the larger the quantity of the strategy associated features included in the second strategy associated result is, the larger the theoretical value of the feature identification parameter expression value of the second strategy associated result is.

If the number of the policy associated features included in the second policy associated result is greater than the first set number, calculating a theoretical value of a feature identification parameter expression value of the second policy associated result according to the second set model, wherein the number of the policy associated features included in the second policy associated result is an input part of the second set model, the theoretical value of the feature identification parameter expression value of the second policy associated result is an output part of the second set model, and in the second set model, the larger the number of the policy associated features included in the second policy associated result is, the smaller the theoretical value of the feature identification parameter expression value of the second policy associated result is, and the associated feature value of the second policy associated result is a weighted value between the feature identification parameters of the associated features and the feature identification parameters of the non-associated features in the second policy associated result.

On this basis, a compensation correlation value of the second policy correlation result may be calculated according to a theoretical value of a correlation feature value of the second policy correlation result and a correlation feature value of a last policy correlation feature of the second policy correlation result, where the compensation correlation value is used to perform compensation update on a target correlation policy controlling a correlation position in the second policy correlation result, and the correlation feature value of the last policy correlation feature is a weighted value between an average value of application feature identification parameters of non-correlation features in the last policy correlation feature and an average value of application feature identification parameters of correlation features in the last policy correlation feature.

Then, a target association policy for controlling the association position in the second policy association result may be obtained according to the compensation association value, where the target association policy for controlling the association position is used to perform control association processing on the device control policy.

Therefore, the device control strategy can be subjected to control association processing according to the target association strategy, and a strategy execution process control curve of the device control strategy is obtained.

Based on the above design, the embodiment can determine the compensation correlation value of the second policy correlation result according to the number of the policy correlation features included in the second policy correlation result, so that the difference between the numbers can be fully considered in the process of performing the device control correlation processing, and the control deviation of the actual device control process is further reduced.

In a possible design, in the process of obtaining the target association policy for controlling the association position in the second policy association result according to the compensation association value, in order to improve the processing efficiency, the difference expressions of policies of different item types are further considered, so as to reduce the control deviation of the actual device control process, which may be specifically implemented in the following manner:

firstly, data to be associated and processed corresponding to a target association sub-strategy corresponding to each item type in a target association strategy is sequentially obtained, and the data to be associated and processed corresponding to the target association sub-strategy comprises a plurality of control association models.

Then, a control association model of the current association to be controlled in the data to be associated and processed corresponding to the target association sub-strategy is sequentially obtained, if the control association model of the current association to be controlled comprises control association nodes, the position of a parameter control unit of the parameter control information of the equipment control strategy in the first traversal project type is obtained, the position of the control association model of the parameter control information of the equipment control strategy in the first traversal project type is calculated and obtained according to the position of the parameter control unit of the parameter control information of the equipment control strategy in the first traversal project type, the control association model calling information of the parameter control information of the equipment control strategy in the first traversal project type is calculated according to the position of the control association model of the parameter control information of the equipment control strategy in the first traversal project type, and/or process node information of the control association data feature points in the control association nodes is obtained, and acquiring a process control characteristic vector of a process node set of process control information for controlling the associated data characteristic points to the equipment control strategy in the second traversal project type, and calculating control associated model calling information of the set position information in the second traversal project type according to the process control characteristic vector and the set position information of the process node set calculated by the process node information.

And then, acquiring control association model calling information of past control association of the target association sub-strategy corresponding to the first traversal item type, and/or acquiring past control association model calling information in the target association sub-strategy corresponding to the second traversal item type.

And if the control association model call information of the past control association in the target association sub-strategy corresponding to the first traversal item type matches the control association model call information of the equipment control strategy in the target association sub-strategy corresponding to the first traversal item type, and/or the control association model call information of the past control association in the target association sub-strategy corresponding to the second traversal item type matches the control association model call information of the process control information of the equipment control strategy in the target association sub-strategy corresponding to the second traversal item type, performing control association processing on the current control association model to be controlled and the equipment control strategy, and judging whether the number of control association nodes of the current control association model to be controlled is greater than the number of preset control association models.

And if the number of the control associated nodes of the control associated model to be currently controlled and associated is greater than the number of the preset control associated models, acquiring the control associated model to be currently called and processed, and calling the control associated model to be currently called and processed.

And judging whether the control associated model calling information of the current control associated model is matched with the control associated model calling information of the last control associated model in the associated data to be controlled corresponding to the item type.

If the control associated model calling information of the current control associated model matches the control associated model calling information of the last control associated model in the associated data to be controlled corresponding to the item type, all control associated models which are not called and processed in the associated data to be controlled corresponding to the item type are obtained, and all control associated models which are not called and processed in the associated data to be controlled corresponding to the item type are called and processed in sequence.

If the control associated model calling information currently in control association in the first traversal item type does not match the control associated model calling information of the parameter control information of the device control strategy in the first traversal item type, and/or the control associated model calling information currently in call processing in the second traversal item type does not match the control associated model calling information of the process control information of the device control strategy in the second traversal item type, waiting for the first traversal item type to carry out control association and/or waiting for the second traversal item type to carry out call processing until the control associated model calling information currently in control association in the first traversal item type matches the control associated model calling information of the parameter control information of the device control strategy in the first traversal item type, and/or waiting for the second traversal item type to carry out call processing until the control associated model calling information currently in call processing in the first traversal item type matches the control associated model calling information of the device control strategy in the first traversal item type, and/or the process of the control associated model calling information The control information is up to the control association model invocation information in the second traversal item type.

And if the control associated model of the current to-be-controlled association does not comprise the control associated node, performing control association on the control associated model of the current to-be-controlled association, judging whether the control associated model calling information of the control associated model of the current to-be-controlled association matches the preset control associated model quantity or the control associated model calling information of the last control associated model in the to-be-controlled association data corresponding to the item type, if the control associated model calling information of the control associated model of the current to-be-controlled association matches the preset control associated model quantity, acquiring the control associated model of the current to-be-called processing, and calling the control associated model of the current to-be-called processing. And the difference value between the calling information of the current control-to-be-controlled associated model in the associated data to be controlled corresponding to the item type and the calling information of the current control-to-be-called processed control associated model in the associated data to be controlled corresponding to the item type is the preset control associated model quantity. If the control associated model calling information of the current control associated model matches the control associated model calling information of the last control associated model in the associated data to be controlled corresponding to the item type, all control associated models which are not called and processed in the associated data to be controlled corresponding to the item type are obtained, and all control associated models which are not called and processed in the associated data to be controlled corresponding to the item type are called and processed in sequence.

Based on the steps, the processing efficiency can be improved, and the difference expression of different item type strategies can be further considered, so that the control deviation of the actual equipment control process is reduced.

In a possible design, further referring to step S140, in the process of obtaining the second item type information of the control item type matching the device state information according to the policy execution process control curve, in order to further reduce the control deviation of the actual device control process, specifically, a policy execution position, a policy execution manner, and a policy execution control command in the policy execution process control curve may be extracted, and after the policy execution position is extracted, the to-be-obtained type information of the control item type matching the device state information is obtained according to the policy execution position.

And then, acquiring a policy execution path corresponding to the policy execution mode and an information execution path of the type information to be acquired, judging whether the information execution path of the type information to be acquired is larger than the policy execution path, if the information execution path of the type information to be acquired is judged to be matched with the policy execution path, acquiring execution process information corresponding to the information execution path from the type information to be acquired, and correspondingly configuring the execution process path corresponding to the execution process information and the policy execution mode.

On the basis, searching an execution process path corresponding to the strategy execution mode, determining a command image file corresponding to the strategy execution control command, searching a command operation set corresponding to the command image file, and after acquiring an operation command corresponding to the strategy execution control command from the searched command operation set, performing operation processing on the type information to be acquired according to the operation command.

Then, the execution process information corresponding to the execution process path can be searched, and the type information to be acquired after the operation processing is written into the searched execution process information, so that second item type information of the control item type matched with the equipment state information is obtained.

In a possible design, further referring to step S140, in the process of extracting the control feature information of the target device control policy from the policy execution process control curve, in order to further reduce the control deviation of the actual device control process, specifically, a dimension coordinate currently corresponding to a policy dimension coordinate in the target device control policy in the policy execution process control curve may be obtained as each first dimension coordinate, and a coordinate tag of the first dimension coordinate is determined.

And when the coordinate label of the first-dimension coordinate represents that the first-dimension coordinate is a control feature coordinate, writing the first-dimension coordinate into the control feature sequence. And when the first-dimension coordinate is not the control feature coordinate, writing the first-dimension coordinate into the non-control feature sequence.

On the basis, whether the control feature sequence stores the dimension coordinates or not can be determined, and when the control feature sequence stores the dimension coordinates, the sequence mark coordinates of the control feature sequence are obtained to serve as second dimension coordinates.

And then, further determining whether the control features corresponding to the second-dimension coordinates have unmarked features, wherein when the features are marked, the control features are characterized to be used for control.

When there are no unmarked features after the second dimension coordinates, it is determined whether the sequence of non-control features includes only the first dimension coordinates. And when the non-control feature sequence only comprises the first dimension coordinate, extracting the second dimension coordinate from the control feature sequence, emptying the non-control feature sequence, and transferring from the first dimension coordinate to the next dimension coordinate to be detected to obtain each extracted second dimension coordinate.

And then, further extracting control feature spaces corresponding to all the second-dimension coordinates in a preset time length according to the extracted second-dimension coordinates, grouping the control feature spaces according to different control types, calculating the control feature space grade of each control type in a preset time period, and selecting corresponding control feature identification nodes according to the control feature space grade.

And then, setting a plurality of node control code lines corresponding to each control feature identification node according to the control feature identification node corresponding to the selected control feature space, and dividing each node control code line into a control type code line, a non-control type code line, a maintenance type code line and a non-maintenance type code line.

On the basis, in each node control code line, sequencing is carried out according to the time sequence called by the node control code line for the last time, and a time sequence characteristic sequence corresponding to each node control code line set is obtained, wherein the node control code line with the latest calling time closest to the current time in the time sequence characteristic sequence is used as a first node control code line, and the node control code line with the latest calling time farthest from the current time is used as a second node control code line.

Therefore, the time sequence characteristic sequences of the control type code line, the non-control type code line, the maintenance type code line and the non-maintenance type code line can be detected in sequence, if the first non-space-time sequence characteristic sequence is detected, the node control code line at the position of the second node control code line in the time sequence characteristic sequence is removed, and the corresponding time sequence characteristic sequence is regenerated for the node control code line set corresponding to the time sequence characteristic sequence. And finally, obtaining the control characteristic information of the target equipment control strategy according to the regenerated time sequence characteristic sequence corresponding to each node control code line set.

In one possible design, further to step S140, in determining the target device control strategy from the device control strategies according to the control feature information and the second item type information, in order to further reduce the control deviation of the actual device control procedure, first a first strategy model of the control feature information and a second strategy model of the second item type information may be respectively constructed. And then, a first strategy model of the control characteristic information is adopted to construct a strategy execution model of the control characteristic information, and a second strategy model of the second item type information is adopted to construct a strategy execution model of the second item type information. Thus, the control feature space of the control feature information may be represented using a policy enforcement model of the control feature information, while the control feature space of the second item type information may be represented using a policy enforcement model of the second item type information.

And then, preliminarily detecting a strategy execution node of the control characteristic information in the control characteristic space of the control characteristic information, and simultaneously preliminarily detecting a strategy execution node of the second item type information in the control characteristic space of the second item type information to obtain a strategy execution node sequence of the control characteristic information in the control characteristic space and a strategy execution node sequence of the second item type information in the control characteristic space.

And then, removing unstable strategy execution nodes from the strategy execution node sequence of the control characteristic information in the control characteristic space, and removing unstable strategy execution nodes from the strategy execution node sequence of the second item type information in the control characteristic space to obtain target strategy execution nodes of the control characteristic information and target strategy execution nodes of the second item type information.

And then, respectively determining a strategy main execution process of a target strategy execution node of the control characteristic information and a strategy main execution process of a target strategy execution node of the second item type information to obtain a target strategy execution node process of the control characteristic information and a target strategy execution node process of the second item type information.

Then, a target strategy execution node process of the control characteristic information is adopted, target strategy execution node process metadata corresponding to the target strategy execution node process of the control characteristic information is calculated, meanwhile, a target strategy execution node process of the second item type information is adopted, target strategy execution node process metadata corresponding to the target strategy execution node process of the second item type information is calculated, and the target strategy execution node process metadata of the control characteristic information and the target strategy execution node process metadata of the second item type information are obtained.

And then, according to the target strategy execution node process metadata of the control characteristic information and the target strategy execution node process metadata of the second item type information, carrying out initial matching on the control characteristic information and the second item type information to obtain a matching strategy execution node pair of the control characteristic information and the second item type information.

And then, determining the matching parameters of the control characteristic information and the second item type information according to the matching strategy execution node pair of the control characteristic information and the second item type information.

And then, determining a target equipment control strategy from the equipment control strategies according to the matching parameters of the control characteristic information and the second item type information.

Fig. 4 is a schematic functional block diagram of the device control apparatus 300 based on a block chain according to an embodiment of the present application, and the embodiment may divide the functional blocks of the device control apparatus 300 based on a block chain according to the foregoing method embodiment. For example, the functional blocks may be divided for the respective functions, or two or more functions may be integrated into one processing block. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. It should be noted that, the division of the modules in the present application is schematic, and is only a logical function division, and there may be another division manner in actual implementation. For example, in the case of dividing each function module by corresponding functions, the device control apparatus 300 based on the block chain shown in fig. 4 is only an apparatus diagram. The device control apparatus 300 based on a blockchain may include an adding module 310, a determination obtaining module 320, a control associating module 330, and a policy determining module 340, where functions of the functional modules of the device control apparatus 300 based on a blockchain are described in detail below.

An adding module 310, configured to add the device state information to a pre-established blockchain corresponding to the device to be controlled 200 according to the device state information uploaded by each device to be controlled 200, and sequentially determine, in the blockchain, a device control policy corresponding to the current device state information according to a node participation order of each participating node.

The determining and acquiring module 320 is configured to determine a relative device control policy from the device control policies associated with the device status information and in which the node participation order in the device status information is before the determined device control policy, and acquire first item type information of a control item type matching the device status information in the relative device control policy.

And the control association module 330 is configured to perform device control association processing on the device control policy according to the device control association between the first item type information and the control item type node matched with the device state information, so as to obtain a policy execution process control curve of the device control policy.

The policy determining module 340 is configured to obtain second item type information of a control item type matching the device state information according to the policy execution process control curve, extract control feature information of the target device control policy from the policy execution process control curve, and determine the target device control policy from the device control policy according to the control feature information and the second item type information.

Further, fig. 5 is a schematic structural diagram of a server 100 for executing the above device control method based on a blockchain according to an embodiment of the present application. As shown in FIG. 5, the server 100 may include a network interface 110, a machine-readable storage medium 120, a processor 130, and a bus 140. The processor 130 may be one or more, and one processor 130 is illustrated in fig. 5 as an example. The network interface 110, the machine-readable storage medium 120, and the processor 130 may be connected by a bus 140 or otherwise, as exemplified by the connection by the bus 140 in fig. 5.

The machine-readable storage medium 120 is a computer-readable storage medium, and can be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the device control method based on block chains in the embodiment of the present application (for example, the adding module 310, the determining and obtaining module 320, the control associating module 330, and the policy determining module 340 of the device control apparatus 300 based on block chains shown in fig. 4). The processor 130 executes various functional applications and data processing of the terminal device by detecting the software programs, instructions and modules stored in the machine-readable storage medium 120, that is, the device control method based on the block chain is implemented, and details are not described herein.

The machine-readable storage medium 120 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the machine-readable storage medium 120 may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile memory may be a Read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of example, but not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), Double data rate Synchronous Dynamic random access memory (DDR SDRAM), Enhanced Synchronous SDRAM (ESDRAM), Synchronous link SDRAM (SLDRAM), and direct memory bus RAM (DR RAM). It should be noted that the memories of the systems and methods described herein are intended to comprise, without being limited to, these and any other suitable memory of a publishing node. In some examples, the machine-readable storage medium 120 may further include memory located remotely from the processor 130, which may be connected to the server 100 over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The processor 130 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method embodiments may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 130. The processor 130 may be a general-purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor.

The server 100 can perform information interaction with other devices (for example, the device to be controlled 200) through the communication interface 110. Communication interface 110 may be a circuit, bus, transceiver, or any other device that may be used to exchange information. Processor 130 may send and receive information using communication interface 110.

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may 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. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.

Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

It will be apparent to those skilled in the art that various changes and modifications may be made in the embodiments of the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the embodiments of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to encompass such modifications and variations.

Claims

1. A device control method based on a block chain is applied to a server which is in communication connection with at least one device to be controlled, and the method comprises the following steps:

2. The device control method according to claim 1, wherein the step of performing device control association processing on the device control policy according to a device control association between the first item type information and a control item type node matched with the device state information to obtain a policy execution process control curve of the device control policy includes:

acquiring the strategy association information of the equipment control strategy according to the equipment control association condition between the first item type information and the control item type node matched with the equipment state information, and processing the strategy association information into a strategy association node;

3. The blockchain-based device control method according to claim 2, wherein the step of performing device control association processing on the device control policy according to the second policy association result to obtain a policy execution process control curve of the device control policy includes:

4. The blockchain-based device control method according to claim 2, wherein the step of performing control association processing on the device control policy according to the target association policy to obtain a policy execution process control curve of the device control policy includes:

5. The blockchain-based device control method according to claim 1, wherein the step of obtaining second item type information of a control item type matching the device state information according to the policy enforcement process control curve includes:

6. The blockchain-based device control method according to claim 1, wherein the extracting of the control feature information of the target device control policy from the policy execution process control curve includes:

7. The blockchain-based device control method according to claim 1, wherein the step of determining the target device control policy from the device control policies according to the control feature information and the second item type information includes:

8. A device control apparatus based on a block chain is applied to a server, the server is in communication connection with at least one device to be controlled, and the apparatus comprises:

9. A server, characterized in that the server comprises a processor, a machine-readable storage medium, and a network interface, the machine-readable storage medium, the network interface and the processor are connected through a bus system, the network interface is used for being connected with at least one device to be controlled in a communication manner, the machine-readable storage medium is used for storing programs, instructions or codes, and the processor is used for executing the programs, instructions or codes in the machine-readable storage medium to execute the device control method based on the block chain according to any one of claims 1 to 8.

10. A readable storage medium having stored therein machine executable instructions which when executed perform the blockchain-based device control method of any one of claims 1 to 8.