CN111462918B - Epidemic situation monitoring method and system based on block chain - Google Patents
Epidemic situation monitoring method and system based on block chain Download PDFInfo
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/80—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
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- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
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Abstract
The invention discloses an epidemic situation monitoring method and system based on a block chain. The method comprises the following steps: the checking node generates diagnosis information containing the user identification and broadcasts the diagnosis information in the block chain network; each community node judges whether the user node associated with the community node has a definite diagnosis or not according to the user identifier; if yes, broadcasting a first action track of the confirmed user node in a preset period in the block chain network, and sending confirmed information to the sub-block chain network; the monitoring node acquires a second action track of the non-diagnosed user node in a preset period through the community node, and generates an infection risk list based on the first action track and the second action track; and the monitoring node broadcasts a diagnosis infection risk list in the blockchain network. According to the block chain-based epidemic situation monitoring method, the confirmed person can be transparent to infection in a latent period through tracing and monitoring of the person in contact with the confirmed person, prevention and control are timely achieved, and large-area outbreak of infection is avoided.
Description
Technical Field
The invention belongs to the field of disease monitoring, and particularly relates to an epidemic situation monitoring method and system based on a block chain.
Background
The new coronary pneumonia brings great challenges to epidemic prevention work, the disease is characterized by long latent period, and patients still have strong infectivity in the latent period.
Therefore, the tracing and monitoring of the personnel in contact with the confirmed personnel becomes the central importance of the epidemic prevention work and is also the key point for avoiding large-area outbreaks.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a block chain-based epidemic situation monitoring method and system.
In one aspect, one of the technical solutions of the present invention provides an epidemic situation monitoring method based on a block chain, which is applied to a block chain network, where the block chain network includes at least one community node, an inspection node, and a monitoring node, each community node is communicatively connected to a sub-block chain network, the sub-block chain network includes at least one user node, and the method includes:
the checking node generates diagnosis information containing the user identification and broadcasts the diagnosis information in the block chain network;
each community node judges whether the user node associated with the community node has a definite diagnosis or not according to the user identifier;
if yes, broadcasting a first moving track of the confirmed user node in a preset period in the block chain network, and sending confirmed information to the sub-block chain network;
the monitoring node acquires a second action track of the non-diagnosed user node in a preset period through the community node, and generates an infection risk list based on the first action track and the second action track;
and the monitoring node broadcasts a diagnosis infection risk list in the blockchain network.
In a further improved solution, the diagnostic information with the user identification is generated from the check node and broadcasted in the blockchain network, the method comprising:
the community node acquires the body measurement information of the user node related to the community node for the first time through a sub-block chain network, wherein the body measurement information comprises a user identifier and body temperature data;
comparing the body temperature data with a body temperature threshold;
if the body temperature data is larger than the body temperature threshold value, broadcasting body measurement information in the block chain network, and broadcasting the body measurement information in the sub-block chain network again corresponding to the user node according to the user identification request;
judging whether the body temperature data acquired for the second time is still larger than a body temperature threshold value, if so, collecting body measurement information and forwarding the body measurement information to an inspection node;
otherwise, after the preset time, the corresponding user node is requested to broadcast the physical testing information in the sub-block chain network again according to the user identification;
and judging whether the body temperature data acquired for the third time is still larger than the body temperature threshold value, if so, collecting body measurement information and forwarding the body measurement information to the check node.
In a further improved scheme, according to the second action track of the monitoring node, the second action track of the non-diagnosed user node is obtained through the community node, and the method comprises the following steps:
the monitoring node sends the public key to the block chain network;
each community node encrypts a second action track of the non-diagnosed user node through the public key of the monitoring node and then sends the second action track to the block chain network;
and the monitoring node decrypts the public key according to the private key of the monitoring node to obtain a second action track of the non-diagnosed user node.
In a further refinement, the method comprises, in accordance with generating an infection risk list based on the first and second motion trajectories:
with the confirmed user node as the center of a circle and the preset infection distance R as the radius, radiating outwards into a circular infection range, and forming an infection path of the confirmed user node in a preset period along the first moving track;
respectively judging whether the second action track of each non-diagnosed user node is intersected with the infection path, if the non-diagnosed user node is positioned in the infection path within the intersection time period calculated by the diagnosed user node once in each intersection, accumulating the contact times once;
calculating the infection probability of each node of the non-diagnosed user, wherein the infection probability I is calculated according to the formula (one):
wherein c is the total number of times of contact between the non-diagnosed user node and the diagnosed user node; i is0Is an initial value of the probability of infection; alpha and beta are constants, and the alpha, beta are belonged to [0,1]And α + β ═ 1; d1The total contact time of the non-confirmed user node and the confirmed user node in a preset period is set; d2The total length of the non-confirmed user node and the confirmed user node which are not contacted in a preset period is defined; theta is an adjustment factor;
and generating an infection risk list according to the infection probability of each non-diagnosed user node.
In a further improved scheme, an infection risk list is generated according to the infection probability and the user identification of each non-diagnosed user node, and the method comprises the following steps:
determining the non-diagnosed user node with the infection probability smaller than the infection threshold as a third risk level;
determining the non-diagnosed user node with the infection probability greater than the infection threshold as a second risk level;
determining a non-diagnosed user node with an infection probability greater than an infection threshold and a temperature data greater than a temperature threshold record as a first risk level;
and generating an infection risk list according to the risk level and the user identification of the non-diagnosed user node.
In a further improved scheme, an infection risk list is generated according to the risk level and the user identification of the non-diagnosed user node, and the method comprises the following steps:
determining the community node with the risk value of zero as a third risk level;
determining the community nodes with the risk values larger than zero and smaller than the risk threshold value as a second risk level;
determining the community nodes with the risk values larger than a risk threshold value as a first risk level;
and generating an infection risk list according to the risk level of the community node, the information of the confirmed user node, the infection probability of the non-confirmed user node and the user identification.
In a further improved scheme, the risk value R of the community node is calculated according to formula (two):
wherein x is the number of the current confirmed user nodes of the community node, y is the number of the confirmed user nodes of the community node before the preset period, w is the total number of times that the community node sends the physical testing information to the inspection node in the preset period,
average infection probability of all non-definite user nodes of community nodes。
In one aspect, one of the technical solutions of the present invention provides an epidemic situation monitoring system based on a block chain, including:
a blockchain system comprising a blockchain backbone, at least one community node, at least one check node, and at least one monitoring node;
each community node is in communication connection with a sub-blockchain system which comprises a blockchain main chain and at least one user node;
the checking node is used for generating the diagnosis information containing the user identification and broadcasting the diagnosis information in the block chain network;
the community node is used for judging whether the user node associated with the community node has a confirmed diagnosis according to the user identifier; if yes, broadcasting a first action track of the confirmed user node in a preset period in the block chain network, and sending confirmed information to a sub-block chain system;
and the monitoring node is used for acquiring a second action track of the non-diagnosed user node in a preset period through the community node, generating an infection risk list based on the first action track and the second action track, and broadcasting the diagnosed infection risk list in the block chain network.
According to the epidemic situation monitoring method based on the block chain, information and action tracks of confirmed diagnosticians are published in time, rapid spread of the epidemic situation is inhibited, and more importantly, through tracing and monitoring of personnel in contact with the confirmed diagnosticians, the confirmed diagnosticians can cause infection transparence in a latent period, and are prevented and controlled in time, and infection of large-area outbreak is avoided.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a block chain-based epidemic monitoring method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a block chain based epidemic monitoring method according to a second embodiment of the invention;
FIG. 3 is a flow chart of a block chain-based epidemic monitoring method according to a third embodiment of the invention;
FIG. 4 is a flow chart of a block chain-based epidemic monitoring method according to a fourth embodiment of the invention;
FIG. 5 is a flow chart of a block chain-based epidemic monitoring method according to a fifth embodiment of the invention;
FIG. 6 is a flow chart of a block chain based epidemic monitoring method according to a sixth embodiment of the invention;
fig. 7 is a block chain-based epidemic monitoring system architecture diagram according to an embodiment of the present invention;
fig. 8 is a hardware schematic diagram of a node device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
One embodiment of the invention provides an epidemic situation monitoring method based on a block chain, which is applied to a block chain network, wherein the block chain network comprises at least one community node, an inspection node and a monitoring node, the monitoring node can be set up by a government epidemic prevention department, each community node is in communication connection with a sub-block chain network, and the sub-block chain network comprises at least one user node.
As shown in fig. 1, the method comprises the steps of:
s100, generating diagnosis information containing user identification by the check node and broadcasting the diagnosis information in the block chain network;
s200, each community node judges whether a diagnosis is confirmed or not according to the user identification;
s300, if yes, broadcasting a first action track of the confirmed user node in a preset period in the block chain network, and sending confirmed information to the sub-block chain network;
s400, the monitoring node acquires a second action track of the non-diagnosed user node in a preset period through the community node, and generates an infection risk list based on the first action track and the second action track;
s500, the monitoring node broadcasts a diagnosis infection risk list in the block chain network.
Compared with the prior art, the epidemic situation monitoring method based on the block chain has the advantages that the information of confirmed patients is sent in the block chain network through the inspection nodes, the confirmed information is timely and accurately transmitted through at least one community node and at least one monitoring node, people can timely know information such as the number of infected people, the location and the like, and the epidemic situation monitoring method is quite effective for epidemic situation prevention and control and rumor elimination; community epidemic prevention personnel can bind community nodes with user nodes in a sub-blockchain network which is in communication connection with the community nodes in advance, the community node can acquire the authority of the real-time position of the user node, the user node can be one node of each family or a plurality of families, the nodes can be intelligent terminals such as mobile phones, only residents can carry bound mobile phones to go out to obtain the real-time position of the user node during the epidemic situation, if the community node confirms that the user node in the sub-block chain network in communication connection with the community node has a diagnosis, broadcasting a first action track of the confirmed user node in a preset period in the blockchain network, and sending the confirmed information to the sub-blockchain network, the dangerous area where the diagnosed patient acts is disinfected or the dangerous area is avoided by government epidemic prevention departments, community epidemic prevention personnel and community residents; the monitoring node generates an infection risk list and broadcasts the infection risk list in a block chain network, and then generates an infection risk list for community residents who have contacted with the diagnosed patient in a short distance in a preset period of 14-day latency, and according to the infection risks of different community residents in the infection risk list, government epidemic prevention departments and community epidemic prevention personnel adopt correspondingly different epidemic prevention measures such as centralized isolation, household observation and temperature measurement; in addition, the block chain is used for epidemic situation monitoring, data can be irrevocably modified and traceable, and any node broadcasts false data or illegally operates, and is accountable by taking the data stored in the block chain as evidence. The application provides a epidemic situation monitoring method based on block chain realizes in time publishing confirmed person information and action track, is favorable to restraining the rapid propagation of epidemic situation, and more importantly, through the tracing back and the monitoring with confirmed person contact personnel for confirmed person probably causes infection transparentization in the incubation period, in time obtains prevention and control, avoids infecting the outbreak of large tracts of land.
As shown in fig. 2, another embodiment of the present invention provides a block chain-based epidemic monitoring method, further including the following steps:
s110, the community nodes acquire the body measurement information of the user nodes related to the community nodes for the first time through a sub-block chain network, wherein the body measurement information comprises user identification and body temperature data;
s120, comparing the body temperature data with a body temperature threshold;
s130, if the body temperature data is larger than the body temperature threshold value, broadcasting the body measurement information in the block chain network, and broadcasting the body measurement information in the sub-block chain network again corresponding to the user node according to the user identification request;
s140, judging whether the body temperature data acquired for the second time is larger than a body temperature threshold value, if so, summarizing body test information and forwarding the body test information to a check node;
s150, if not, after the preset time, the corresponding user node broadcasts the body test information in the sub-block chain network again according to the user identification request;
and S160, judging whether the body temperature data acquired for the third time is larger than a body temperature threshold value, and if so, summarizing and forwarding the body measurement information to the inspection node.
The community residents can upload body temperature data every day according to the requirements of community epidemic prevention personnel, and the community nodes compare the body temperature data with a body temperature threshold value to screen possible infected persons in an early stage. If the body temperature data is larger than the body temperature threshold value, the body temperature data is required to be measured again immediately, so that the misoperation of a user is avoided, the accuracy of the body temperature data is guaranteed, and meanwhile, the mistaken reporting of community nodes is prevented; if the body temperature data acquired for the second time is larger than the body temperature threshold value, the body measurement information is collected and forwarded to the inspection node, and the inspection node is arranged to inspect corresponding residents and determine whether the residents have confirmed diagnosis; and if the body temperature data acquired for the second time is not greater than the body temperature threshold, performing measurement check again after preset time, and avoiding missing report and missing check. In addition, the identity, the family and the activity area of a potential infectious disease infected person can be quickly locked through the user identification, and help is provided for controlling an epidemic situation.
As shown in fig. 3, a method for monitoring epidemic situation based on block chain according to another embodiment of the present invention further includes the following steps:
s401, the monitoring node sends the public key to a block chain network;
s402, encrypting a second movement track of the non-diagnosed user node by each community node through a public key of the monitoring node, and then sending the second movement track to the block chain network;
and S403, the monitoring node decrypts the public key according to the private key of the monitoring node, and obtains a second action track of the non-diagnosed user node.
The community nodes encrypt the second action tracks of the non-diagnosed user nodes through the public keys of the monitoring nodes respectively, and only the monitoring nodes can decrypt the public keys according to the private keys of the monitoring nodes, so that the data security is guaranteed, and the personal information and the privacy of the non-diagnosed user nodes are protected.
As shown in fig. 4, a method for monitoring epidemic situation based on block chain according to another embodiment of the present invention further includes the following steps:
s410, with the confirmed user node as a circle center and a preset infection distance R as a radius, radiating outwards to form a circular infection range, and forming an infection path of the confirmed user node in a preset period along a first moving track;
s420, respectively judging whether the second action track of each non-diagnosed user node is intersected with the infection path, and accumulating the contact times once when the non-diagnosed user node is positioned in the infection path within the intersection time period calculated by the diagnosed user node in the path intersection once is intersected;
the number of times that the non-diagnosed user node meets the diagnosed user node and enters the infection range of the diagnosed user node is the contact number;
s430, calculating the infection probability of each node of the non-diagnosed user, wherein the infection probability I is calculated according to a formula (I):
wherein c is the total number of times of contact between the non-diagnosed user node and the diagnosed user node; i is0Is an initial value of the probability of infection; alpha and beta are constants, and the alpha, beta are belonged to [0,1]And α + β ═ 1; d1The total contact time of the non-confirmed user node and the confirmed user node in a preset period is set; d2The total length of the non-confirmed user node and the confirmed user node which are not contacted in a preset period is defined; theta is an adjustment factor;
calculating the infection probability I accurately by the formula;
and S440, generating an infection risk list according to the infection probability of each non-diagnosed user node. Specifically, as shown in fig. 5, generating an infection risk list according to the infection probability of each node of the non-diagnosed user includes:
s441, the non-diagnosed user node with the infection probability smaller than the infection threshold is determined as a third risk level;
s442, determining the non-diagnosed user node with the infection probability larger than the infection threshold value as a second risk level;
s443, determining a non-confirmed user node with an infection probability greater than an infection threshold and a body temperature data greater than a body temperature threshold record as a first risk level;
and S444, generating an infection risk list according to the risk level of the non-diagnosed user node and the user identification.
According to the infection probability and the body temperature data, the non-diagnosed user nodes are graded, on one hand, government epidemic prevention departments and community epidemic prevention personnel can take corresponding different-grade epidemic prevention measures such as confirmed diagnosis inspection, centralized isolation, home observation and continuous temperature measurement observation on community residents and community residents thereof, and on the other hand, epidemic outbreak is restrained in a budding state while influence on life of most of the non-diagnosed user nodes is reduced, on the other hand, epidemic prevention work is light and orderly, more side emphasis is provided, and work burden of workers can be reduced.
As shown in fig. 6, a method for monitoring epidemic situation based on block chain according to another embodiment of the present invention further includes the following steps:
s445, determining the community node with the risk value of zero as a third risk level;
s446, determining the community nodes with the risk values larger than zero and smaller than the risk threshold value as a second risk level;
s447, determining the community nodes with the risk values larger than the risk threshold value as a first risk level;
and S448, generating an infection risk list according to the risk level of the community node, the information of the confirmed user node, the infection probability of the non-confirmed user node and the user identification.
And calculating the risk value R of the community node according to a formula (two):
wherein x is the number of the current confirmed user nodes of the community node, y is the number of the confirmed user nodes of the community node before the preset period, w is the total number of times that the community node sends the physical testing information to the inspection node in the preset period,
and averaging the infection probability of all the non-diagnosed user nodes of the community nodes.
By grading the communities and community residents twice in terms of infection risk, different epidemic prevention strategies can be conveniently adopted by the government epidemic prevention departments for different communities and different residents in the same community, and the maximum epidemic prevention effect can be obtained by minimum generation and exchange according to local conditions. The epidemic situation outbreak is restrained in the bud state while the influence on the life of most of non-diagnosed user nodes is reduced, and on the other hand, the epidemic prevention work is orderly and more laterally important, so that the workload of workers can be reduced.
For example, the community node a is determined as a first risk level, and four user nodes are arranged in the community node a, and the user node a1, the user node a2, the user node a3 and the user node a4 in the community node a are respectively a first risk level, a second risk level, a third risk level and a third risk level; the community node B is determined to be a second risk level, four user nodes are arranged in the community node B, and a user node B1, a user node B2, a user node B3 and a user node B4 in the community node B are respectively a first risk level, a second risk level, a third risk level and a third risk level; the community node C is determined to be a third risk level, four user nodes are arranged in the community node C, and the user node C1, the user node C2, the user node C3 and the user node C4 in the community node C are respectively a first risk level, a second risk level, a third risk level and a third risk level.
For example, the following epidemic prevention measures can be adopted correspondingly: setting the strictest isolation, disinfection and monitoring policies for community node A and all user nodes a1, a2, a3, a4, b1 and c1 of the community node A; setting strict isolation, disinfection and monitoring policies for the community node B and the user node B2, the user node B3, the user node B4 and the user node c2 in the community node B; and relatively loose isolation, disinfection and monitoring policies are set for the community node C and the user node C3 and the user node C4 in the community node C.
As shown in fig. 7, an embodiment of the present invention provides a block chain-based epidemic situation monitoring system, including:
a blockchain system comprising a blockchain backbone, at least one community node, at least one check node, and at least one monitoring node;
each community node is in communication connection with a sub-blockchain system which comprises a blockchain main chain and at least one user node;
the checking node is used for generating the diagnosis information containing the user identification and broadcasting the diagnosis information in the block chain network;
the community node is used for judging whether the user node associated with the community node has a confirmed diagnosis according to the user identifier; if yes, broadcasting a first action track of the confirmed user node in a preset period in the block chain network, and sending confirmed information to a sub-block chain system;
and the monitoring node is used for acquiring a second action track of the non-diagnosed user node in a preset period through the community node, generating an infection risk list based on the first action track and the second action track, and broadcasting the diagnosed infection risk list in the block chain network.
Since each unit module in the present embodiment can execute the method shown in fig. 1, reference may be made to the related description of fig. 1 for a part of the present embodiment that is not described in detail. Fig. 8 is a hardware schematic of a node device according to an embodiment of the invention. Referring to fig. 8, in a hardware level, the node device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the node device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 8, but that does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
In a possible implementation manner, the processor reads the corresponding computer program from the non-volatile memory into the memory and then runs the computer program, and the corresponding computer program can also be acquired from other equipment so as to form the corresponding apparatus on a logic level. And the processor executes the program stored in the memory so as to realize the node working method provided by any embodiment of the invention through the executed program.
An embodiment of the present invention further provides a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, which when executed by a node device including a plurality of application programs, enable the node device to execute the node operating method provided in any embodiment of the present invention.
The method performed by the node device according to the embodiment of the present invention may be applied to or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or by instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention 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 invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
An embodiment of the present invention further provides a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, which when executed by a node device including a plurality of application programs, enable the node device to execute the node operating method provided in any embodiment of the present invention.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units or modules by function, respectively. Of course, the functionality of the various elements or modules may be implemented in the same one or more software and/or hardware components in implementing the invention.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement the information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments of the present invention are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of the present invention, and is not intended to limit the present invention. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (7)
1. The epidemic situation monitoring method based on the block chain is characterized by being applied to a block chain network, wherein the block chain network comprises at least one community node, an inspection node and a monitoring node, each community node is in communication connection with a sub-block chain network, the sub-block chain network comprises at least one user node, and the method comprises the following steps:
the checking node generates diagnosis information containing the user identification and broadcasts the diagnosis information in the block chain network;
each community node judges whether the user node associated with the community node has a definite diagnosis or not according to the user identifier;
if yes, broadcasting a first action track of the confirmed user node in a preset period in the block chain network, and sending confirmed information to the sub-block chain network;
the monitoring node acquires a second action track of the non-diagnosed user node in a preset period through the community node, and generates an infection risk list based on the first action track and the second action track;
and the monitoring node broadcasts an infection risk list in the blockchain network.
2. The blockchain-based epidemic monitoring method of claim 1, wherein the diagnostic information with the user identifier is generated from the inspection node and broadcasted in the blockchain network, and the method comprises:
the community node acquires the body measurement information of the user node related to the community node for the first time through a sub-block chain network, wherein the body measurement information comprises a user identifier and body temperature data;
comparing the body temperature data with a body temperature threshold;
if the body temperature data is larger than the body temperature threshold value, broadcasting body measurement information in the block chain network, and broadcasting the body measurement information in the sub-block chain network again corresponding to the user node according to the user identification request;
judging whether the body temperature data acquired for the second time is still larger than a body temperature threshold value, if so, summarizing body test information and forwarding the body test information to a check node;
otherwise, after the preset time, the corresponding user node is requested to broadcast the body test information in the sub-block chain network again according to the user identification;
and judging whether the body temperature data acquired for the third time is still larger than the body temperature threshold value, if so, summarizing the body measurement information and forwarding the body measurement information to the inspection node.
3. The blockchain-based epidemic monitoring method according to claim 2, wherein a second action track of the non-diagnosed user node is obtained through the community node according to the monitoring node, and the method comprises:
the monitoring node sends the public key to the block chain network;
each community node encrypts a second action track of the non-diagnosed user node through the public key of the monitoring node and then sends the second action track to the block chain network;
and the monitoring node decrypts the public key according to the private key of the monitoring node to obtain a second action track of the non-diagnosed user node.
4. The blockchain-based epidemic monitoring method of any one of claims 1-3, wherein the method comprises:
with the confirmed user node as the center of a circle and the preset infection distance R as the radius, radiating outwards into a circular infection range, and forming an infection path of the confirmed user node in a preset period along the first moving track;
respectively judging whether the second action track of each non-diagnosed user node is intersected with the infection path, and accumulating the contact times once when the non-diagnosed user node is intersected once and is positioned in the infection path within the intersection time period calculated by the diagnosed user node;
calculating the infection probability of each node of the non-diagnosed user, wherein the infection probability I is calculated according to the formula (one):
wherein c is the total number of times of contact between the non-diagnosed user node and the diagnosed user node; i is0Is an initial value of the probability of infection; alpha and beta are constants, and the alpha, beta are belonged to [0,1]And α + β ═ 1; d1The total contact time of the non-diagnosed user node and the diagnosed user node in a preset period is set; d2The total length of the untouched time of the non-confirmed user node and the confirmed user node in a preset period is defined; theta is an adjustment factor;
and generating an infection risk list according to the infection probability of each non-diagnosed user node.
5. The blockchain-based epidemic monitoring method of claim 4, wherein an infection risk list is generated according to the infection probability and the user identifier of each undiagnosed user node, the method comprising:
determining the non-diagnosed user node with the infection probability smaller than the infection threshold as a third risk level;
determining the non-diagnosed user node with the infection probability greater than the infection threshold as a second risk level;
determining a non-diagnosed user node with an infection probability greater than an infection threshold and a temperature data greater than a temperature threshold record as a first risk level;
and generating an infection risk list according to the risk level and the user identification of the non-diagnosed user node.
6. The blockchain-based epidemic monitoring method of claim 5, wherein an infection risk list is generated according to the risk level of the non-diagnosed user node and the user identifier, the method comprising:
determining the community node with the risk value of zero as a third risk level;
determining the community nodes with the risk values larger than zero and smaller than the risk threshold value as a second risk level;
determining the community nodes with the risk values larger than a risk threshold value as a first risk level;
and generating an infection risk list according to the risk level of the community node, the information of the confirmed user node, the infection probability of the non-confirmed user node and the user identification.
7. The blockchain-based epidemic monitoring method according to claim 6, wherein the risk value R of the community node is calculated according to formula (II):
wherein x is the number of the current confirmed user nodes of the community node, y is the number of the confirmed user nodes of the community node before the preset period, w is the total number of times that the community node sends the physical testing information to the inspection node in the preset period,
and averaging the infection probability of all the non-diagnosed user nodes of the community nodes.
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| CN112259249B (en) * | 2020-10-28 | 2022-12-27 | 山东农业工程学院 | Cross-domain flow identification and epidemic prevention system and method based on Internet of things and block chain |
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| CN112635061A (en) * | 2020-12-30 | 2021-04-09 | 南方科技大学 | Data processing method, device and equipment based on block chain and storage medium |
| CN113593713A (en) * | 2020-12-30 | 2021-11-02 | 南方科技大学 | Epidemic situation prevention and control method, device, equipment and medium |
| CN112735602A (en) * | 2021-01-07 | 2021-04-30 | 南方科技大学 | Block chain risk value management method and device, electronic equipment and storage medium |
| CN112733203A (en) * | 2021-01-14 | 2021-04-30 | 南方科技大学 | Contact data storage method, device, equipment and storage medium |
| CN112768086B (en) * | 2021-02-07 | 2024-03-15 | 厦门兆信物之联智能科技有限公司 | Block chain-based health tracing method, system, mobile terminal and storage medium |
| CN113192644A (en) * | 2021-02-26 | 2021-07-30 | 上海市疾病预防控制中心 | Method, device, processor and computer readable storage medium for realizing quantitative hierarchical evaluation detection aiming at regional epidemic risk |
| CN113035366B (en) * | 2021-03-24 | 2023-01-13 | 南方科技大学 | Close contact person identification method, close contact person identification device, electronic device and storage medium |
| CN113365211A (en) * | 2021-04-19 | 2021-09-07 | 中科劲点（北京）科技有限公司 | Epidemic situation forecasting method based on activity track, device, medium and electronic equipment thereof |
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