CN115883664A - Wisdom commodity circulation garden sensing cloud platform based on fog calculates - Google Patents
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Abstract
The invention relates to the technical field of smart logistics park management, in particular to a smart logistics park sensing cloud platform based on fog computing. It includes a sensor deployment end, a fog calculation end, and an end user. According to the invention, the corresponding fog nodes are configured according to the transmission path of the sensor transmission data through the fog node connection unit and are used for transporting the data transmitted by the sensor, meanwhile, the data received by the physical sensor is simply processed through filtering, fusion or reconstruction and the like through the data fog calculation unit, the needed data is uploaded to the cloud end, the temporary storage of the sensor data is provided, the network bandwidth consumption is reduced, the storage and calculation load of the cloud end is reduced, and meanwhile, the fog calculation realizes the direct control and management of the sensor nodes.
Description
Technical Field
The invention relates to the technical field of intelligent logistics park management, in particular to a smart logistics park sensing cloud platform based on fog computing.
Background
The logistics park is as important logistics infrastructure, have the function integration, the facility sharing, the advantage of land saving, promote the healthy orderly development of logistics park, to improving social logistics service efficiency, promote the industrial structure adjustment, change economic development mode, it is significant to improve national economy competitiveness, along with the upgrading change of logistics park function and profit mode, also progressively improve to the requirement of information-based construction, the intelligent technology is ubiquitous, data service systematization, whole operation intellectuality, resource sharing platform and industrial service are whole journey, both are the epoch characteristic of wisdom logistics park, simultaneously also be the real demand of modern logistics to the construction of logistics park.
In the environment of the internet of things, any object can be accessed to the internet and generate data, but in some scenes, the cloud application does not necessarily require that the cloud data and the end equipment are completely synchronous, even in some scenes, the data transmitted by the end equipment is not required at all, and in the environment of the traditional internet of things, the data can be uniformly stored in the database after being directly received, the data abnormality can only occur in a few situations in the logistics park, the data in a common state is stable, if the data storage is continuously performed, the storage burden and the calculation load can be increased for the database, and meanwhile, the network bandwidth consumption can be increased, so that a sensing cloud platform based on the fog calculation is urgently needed.
Disclosure of Invention
The invention aims to provide a smart logistics park sensing cloud platform based on fog computing to solve the problems in the background technology.
For realizing above-mentioned purpose, a wisdom commodity circulation garden sensing cloud platform based on fog calculation is provided, including sensor deployment end, sensor deployment end includes sensor information collection unit, sensor information collection unit is used for gathering the data information of each region of wisdom commodity circulation garden, sensor information collection unit input is connected with sensor virtualization unit, sensor virtualization unit carries out the virtualization to physical sensor, makes sensor data can be shared by a plurality of users, sensor information collection unit input still is connected with sensor management unit, sensor management unit carries out classification to each sensor according to the data content of each sensor transmission to be equipped with corresponding management method, sensor deployment end output is connected with the fog calculation end, the fog calculation end includes fog node connection unit, fog node connection unit is responsible for receiving physical sensor's data, fog node connection unit output is connected with data fog calculation unit, data fog calculation unit filters, fuses or reconstructs simple processing back such as, uploads required data to the temporary storage terminal that the sensor data is provided simultaneously, fog calculation end output is connected with the user information receiving unit, user information receiving unit is used for the user data receiving unit and confirms user data receiving unit.
As a further improvement of the technical solution, the sensor information collecting unit includes a sensor position determining module, the sensor position determining module is used for determining the position of the collecting location, the output end of the sensor position determining module is connected with a data content identifying module, the data content identifying module is used for determining the content collected by the collecting location, the output end of the data content identifying module is connected with an information collecting output unit, and the information collecting output unit is used for classifying the collected information and then distributing the information to each fog node.
As a further improvement of the technical scheme, the sensor management unit comprises a sensor ownership distribution module, the sensor ownership distribution module is used for determining managers of each sensor, the output end of the sensor ownership distribution module is connected with an owner authority establishing module, the owner authority establishing module is used for establishing corresponding management authorities of the managers after determination, the output end of the owner authority establishing module is connected with a credible relationship establishing module, and the credible relationship establishing module is used for establishing credible relationships between the sensors and the corresponding managers.
As a further improvement of the technical solution, the data fog calculating unit includes a data type determining module, the data type determining module is configured to determine data types of different places, an output end of the data type determining module is connected to a data preprocessing module, the data preprocessing module formulates a corresponding data preprocessing mode according to the data types to preprocess the data, an output end of the data preprocessing module is connected to a database pre-storing module, and the database pre-storing module is configured to pre-store the preprocessed data.
As a further improvement of the technical solution, the data preprocessing module adopts a data preprocessing algorithm, and an algorithm formula thereof is as follows:
wherein for each data set acquired by the sensor,
to/is>
For each data collected by the sensor, based on the data collected by the sensor>
For a data coincidence decision function>
For the data cluster corresponding to the data needing to be judged, the ^ er>
Data clusters corresponding to data that were previously collected and evaluated>
For a data cluster coincidence rate, ->
For the threshold of data cluster coincidence rate, when the data clusters coincideRatio->
Less than the data cluster coincidence rate threshold>
When the data cluster coincidence rate ^ is greater than or equal to the preset coincidence rate, the output of the data coincidence judgment function is 0, the data needing judgment is not coincident data, and when the coincidence rate of the data cluster is greater than or equal to the preset coincidence rate>
Not less than the data cluster coincidence rate threshold>
Time, data coincidence judgment function>
The output is 1, which indicates that the data to be judged is coincidence data and needs to be integrated.
As a further improvement of the technical scheme, the input end of the sensor information collecting unit is connected with a sensor distribution unit, and the sensor distribution unit is used for monitoring the running state and data receiving of each sensor.
As a further improvement of the technical solution, the sensor virtualization unit performs virtualization processing of the physical sensor in eight ways, such as a one-to-one correspondence formula, a selection formula, an accumulation formula, an aggregation formula, a restriction formula, a situation restriction formula, a prediction formula, and a calculation formula.
As a further improvement of the technical solution, the output end of the data fog calculating unit is connected with a fog management distributing unit, and the fog management distributing unit is used for determining a fog manager and the management authority of the fog manager.
As a further improvement of the technical solution, an input end of the user information receiving unit is connected with a user classifying unit, and the user classifying unit is used for classifying users.
Compared with the prior art, the invention has the beneficial effects that:
1. in this wisdom logistics park sensing cloud platform based on fog calculates, transmit data transmission path according to the sensor through fog node linkage unit, be equipped with corresponding fog node, be used for transporting the data of sensor transmission, simultaneously filter the data of receiving the physics sensor through data fog calculating unit, fuse or after simple processing such as reconsitution, upload to high in the clouds on the data that will need, provide the temporary storage of sensor data, when reducing network bandwidth consumption, reduce the storage and the computational load in high in the clouds, fog calculates and realizes sensor node direct control and management simultaneously.
2. In this wisdom logistics park sensing cloud platform based on fog calculates, sensor distribution unit is equipped with control and measuring component, and control and measuring component regularly inspect the health status of every sensor node, gather the metadata of sensor node and sensor network to supply monitoring personnel to receive the running state of every sensor node in real time, in time maintain unusual sensor.
3. In the intelligent logistics park sensing cloud platform based on fog computing, a fog management distribution unit is used for determining a fog manager and the management authority of the fog manager, the manager is responsible for the management of fog and fog nodes, the management specifically comprises the steps of monitoring the state of the fog nodes, maintaining a user interface, registering service to a cloud end, and managing the state of service instances (virtual sensors) on the fog nodes, and the fog manager is the owner of the sensors at the same time.
Drawings
FIG. 1 is an overall flow chart of the present invention;
FIG. 2 is a flow chart of a sensor information gathering unit of the present invention;
FIG. 3 is a flow chart of a sensor management unit of the present invention;
FIG. 4 is a flow chart of the data fog calculation unit of the present invention;
FIG. 5 is a table of sensor virtualization processing equations of the present invention.
The various reference numbers in the figures mean:
10. a sensor acquires an information unit; 110. a sensor acquisition position determining module; 120. a data content identification module; 130. an acquisition information output unit;
20. a sensor virtualization unit;
30. a sensor management unit; 310. a sensor ownership assignment module; 320. an owner authority establishing module; 330. a trusted relationship establishing module;
40. a fog node connection unit;
50. a data fog calculation unit; 510. a data type determination module; 520. a data preprocessing module; 530. a database pre-storage module;
60. a user information receiving unit;
70. a sensor dispensing unit;
80. a fog management distribution unit;
90. and a user classification unit.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the 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 obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1 to 5, a smart logistics park sensing cloud platform based on fog computing is provided, which includes a sensor deployment end, the sensor deployment end includes a sensor information collecting unit 10, the sensor information collecting unit 10 is used for collecting data information of each area of the smart logistics park, an input end of the sensor information collecting unit 10 is connected with a sensor virtualization unit 20, the sensor virtualization unit 20 performs virtualization processing on physical sensors, so that sensor data can be shared by multiple users, an input end of the sensor information collecting unit 10 is also connected with a sensor management unit 30, the sensor management unit 30 performs classification processing on each sensor according to data content transmitted by each sensor, and is provided with a corresponding management method, an output end of the sensor deployment end is connected with a fog computing end, the fog computing end includes a fog node connecting unit 40, the fog node connecting unit 40 is responsible for receiving data of the physical sensors, an output end of the fog node connecting unit 40 is connected with a data fog computing unit 50, the data fog computing unit 50 performs simple processing on the data received by the physical sensors, such as filtering, fusing or reconstructing, and provides data of the sensor data stored in a cloud terminal, and a temporary user information receiving unit 60 is connected with a user receiving unit 60 for determining the user information.
When the intelligent logistics park is used, the sensor information collecting unit 10 collects data information of each area of the intelligent logistics park, such as temperature monitoring information of a warehouse environment and temperature information of a refrigerating box in a cold chain logistics process, and generates collected information, the sensor virtualization unit 20 performs virtualization processing on physical sensors, so that the data information collected by the sensors can be shared by a plurality of users to obtain virtual sensors, the sensor management unit 30 performs classification processing on each sensor according to data content transmitted by each sensor and is provided with a corresponding management method, the fog node connecting unit 40 is provided with corresponding fog nodes according to a sensor transmission data transmission path, each fog node comprises a service instance, the service instance is a core component in the fog node, one fog node can simultaneously run a plurality of service instances as required, and each service instance is registered in a cloud management server, and establishes a link relation with a specific virtual sensor template, and presents the link relation to a user in a directory manner, when the user selects the template and creates a virtual sensor, the virtual sensor automatically establishes a connection with a specific service instance on a specific fog node, activates the service instance and acquires physical sensor data through the instance, the fog node connection unit 40 is used for transporting data transmitted by the sensor, each fog node connection unit 40 is responsible for receiving data of the physical sensor, the data fog calculation unit 50 performs simple processing such as filtering, fusion or reconstruction on the received data of the physical sensor, uploads required data to the cloud, and simultaneously provides temporary storage of sensor data, for example, in the temperature monitoring process of a warehouse environment, the user needs the average temperature of a greenhouse space instead of the original temperature data collected by each sensor, in other scenarios, the user does not necessarily require the cloud data to be completely synchronized with the end device, and even the data transmitted by the end device is not needed at all at some time, for example, in a cold chain logistics process, the user may need to receive the data of the end device only when the temperature of the refrigeration box exceeds a threshold, in these cases, the necessary preprocessing work such as calculation and filtering needs to be performed before the sensor data is sent to the cloud, so as to reduce the network bandwidth consumption and the storage and calculation load of the cloud, and the user information receiving unit 60 determines the user receiving the data and transmits the corresponding data to the user.
According to the invention, the corresponding fog nodes are configured through the fog node connection unit 40 according to the transmission path of the sensor transmission data and are used for transporting the data transmitted by the sensor, meanwhile, the data received by the physical sensor is simply processed through filtering, fusion or reconstruction through the data fog calculation unit 50, and then the needed data is uploaded to the cloud end, so that the temporary storage of the sensor data is provided, the storage and calculation load of the cloud end are reduced while the network bandwidth consumption is reduced, and meanwhile, the fog calculation realizes the direct control and management of the sensor nodes.
In addition, the sensor information collecting unit 10 includes a sensor information collecting position determining module 110, the sensor information collecting position determining module 110 is used for determining the position of the collecting place, the output end of the sensor information collecting position determining module 110 is connected with a data content identifying module 120, the data content identifying module 120 is used for determining the content collected by the collecting place, the output end of the data content identifying module 120 is connected with an information collecting output unit 130, and the information collecting output unit 130 is used for classifying the collected information and then distributing the information to each fog node. During specific use, the sensor collecting position determining module 110 determines the position of the collecting place, generates position collecting information, transmits the position collecting information to the data content identifying module 120, the data content identifying module 120 determines the content collected by the collecting place, transmits the collected content to the collecting information output unit 130, and the collecting information output unit 130 classifies the collected information and then distributes the information to each fog node.
Further, the sensor management unit 30 includes a sensor ownership distributing module 310, the sensor ownership distributing module 310 is used for determining managers of each sensor, an output end of the sensor ownership distributing module 310 is connected with an owner authority establishing module 320, the owner authority establishing module 320 is used for performing corresponding management authority establishment on the determined managers, an output end of the owner authority establishing module 320 is connected with a trusted relationship establishing module 330, and the trusted relationship establishing module 330 is used for establishing a trusted relationship between the sensors and the corresponding managers. When the system is used specifically, the sensor ownership allocating module 310 determines managers of each sensor, the sensor managers have ownership of physical sensors, the owner authority establishing module 320 establishes corresponding management authorities for the determined managers, such as authorities for debugging, opening and closing, information calling and the like of the sensors, the trusted relationship establishing module 330 is used for establishing a trusted relationship between the sensors and the corresponding managers, so that a trusted relationship is established between the sensor owners and the cloud platforms, the sensor managers provide accurate and barrier-free sensing services, and the sensors can provide appropriate compensation (such as payment) for the managers according to the use conditions of the sensors; when the manager does not want to continue sharing the physical sensors, the registration information may be deleted, including the type, capabilities, location, etc. of the sensors.
Still further, the data fog calculating unit 50 includes a data type determining module 510, the data type determining module 510 is configured to determine data types of different places, an output end of the data type determining module 510 is connected to a data preprocessing module 520, the data preprocessing module 520 formulates a corresponding data preprocessing mode according to the data types to preprocess the data, an output end of the data preprocessing module 520 is connected to a database pre-storing module 530, and the database pre-storing module 530 is configured to pre-store the preprocessed data. In particular, the data type determination module 510 is configured with a data collection component that collects data from the physical sensors and uploads the data to a particular service instance according to the service instance requirements, meanwhile, the data type determination module 510 determines the data types of different locations, generates data type determination information, and transmits the data type determination information to the data preprocessing module 520, the data preprocessing module 520 formulates a corresponding data preprocessing mode according to the data type, preprocessing data, such as integrating the repeated data, selecting corresponding valid data according to different time nodes, and removing useless data, the data preprocessing module 520 is equipped with a command conversion component responsible for converting and forwarding control instructions for the physical sensors, the data preprocessing module 520 transmits the preprocessed data to the database pre-storing module 530, the database pre-storing module 530 pre-stores the preprocessed data, due to the diversity and complexity of the environment in which "things" are located in the internet of things environment, some objects may be in a harsh complex environment (e.g., outdoor equipment status monitoring, etc.), some objects may be highly mobile (transport vehicles), these objects are difficult to keep permanent connection with the cloud, inevitably affect the real-time transmission of the sensing data, therefore, it is necessary to temporarily store the sensing data in or near the sensing network domain (gateway, etc.), the database pre-storing module 530 is equipped with a temporary storage component, which coordinates the storage space inside the fog, and temporarily storing the preprocessing result under the condition of connection failure with the user side or local application requirement, and automatically deleting the data after the data is successfully uploaded and the local application is finished.
Specifically, the data preprocessing module (520) adopts a data preprocessing algorithm, and the algorithm formula is as follows:
wherein
For each data set collected by a sensor, based on the data set for each sensor>
To/is>
For each data collected by the sensor, based on the data collected by the sensor>
For a data coincidence decision function>
For the data cluster corresponding to the data needing to be judged, the ^ er>
Data clusters corresponding to data that were previously collected and evaluated>
For a data cluster coincidence rate, ->
Is a data cluster coincidence threshold, is a data cluster coincidence rate>
Less than a data cluster coincidence rate threshold>
Time, data coincidence judgment function>
The output is 0, which indicates that the data needing to be judged is not coincident data and is greater than or equal to the coincidence rate of the data cluster>
Not less than a data cluster coincidence rate threshold>
Time, data coincidence judgment function>
The output is 1, which indicates that the data to be judged is coincidence data and needs to be integrated.
In addition, the input end of the sensor information collecting unit 10 is connected with a sensor distributing unit 70, and the sensor distributing unit 70 is used for monitoring the operation state and data receiving of each sensor. During specific use, the sensor distribution unit 70 is equipped with a monitoring and measuring component, the monitoring and measuring component periodically checks the health condition of each sensor node, and collects metadata of the sensor nodes and the sensor network, so that monitoring personnel can receive the running state of each sensor node in real time and timely maintain abnormal sensors.
Further, the sensor virtualization unit 20 performs the virtualization process of the physical sensor by using eight ways, such as a one-to-one correspondence formula, a selection formula, an accumulation formula, an aggregation formula, a limiting formula, a situation limiting formula, a prediction formula, and a calculation formula. The method comprises the following specific steps:
(1) and a one-to-one correspondence formula:
virtual sensors vi there is a one-to-one correspondence between physical sensors pi, so for each physical sensor pi ∈ B, a unique vi is generated. For example, in the state monitoring process of the intelligent logistics park equipment, sensors can be virtualized in a one-to-one correspondence mode;
(2) and the selection formula is as follows:
a set of homogenous physical sensors is represented by a virtual sensor vi, which obtains data from any one of the physical sensors by applying a selection algorithm. For example, when a set of temperature sensors is used to monitor the temperature of a warehouse in a smaller area, the temperature of the area is obtained by acquiring data from any one of the sensors;
(3) and the accumulation formula:
sensor group composed of multiple homogeneous or heterogeneous sensorsBAbstracted into one virtual sensor vi. For example, in an operator condition monitoring application, all sensors used by each individual may be considered a sensor groupBAnd a single VS can be virtualized;
(4) and a polymerization formula:
for all physical sensors pi by the aggregation function h: processing the data of pi epsilon B, and representing the processing result as a virtual sensor vi, for example, when a group of temperature sensors are distributed in a large geographic area, calculating the average temperature of the area through h, and then representing by vi, so that the average temperature of the area can be obtained by accessing vi;
(5) and the limited formula:
representing physical sensors pi using virtual sensors vi, but vi satisfies a defined function only when data from pifIt is then converted to an active mode. For example, when the temperature and humidity of a warehouse are monitored through a virtual sensor, when the values exceed threshold values, the sensor can give an alarm;
(6) the situation limiting formula:
similar to the qualifier, except that the qualifier function f observes one or more other sensors in the group sensor B, { pj | pj ∈ B and pj ≠ pi };
(7) and a prediction formula:
the cloud layer type virtual sensor is provided with a prediction algorithm, and when a corresponding physical sensor is not on line, the current data value can be predicted by performing time sequence data analysis on historical data of the sensor;
(8) and calculating the formula:
belonging to cloud layer, the virtual sensor has context calculation capability, and is realized byBThe data of all the sensors in the system are analyzed, and more easily understood information is provided. For example, image analysis algorithms may be applied to the image from the sensor groupBThe data of (a) are analyzed. In this case, the VS is an integrated form that includes data from the sensor group, the associated algorithms, and the necessary computational and memory resources.
Still further, the output end of the data fog calculating unit 50 is connected to a fog management distributing unit 80, the fog management distributing unit 80 is used for determining the management authority of a fog manager and the fog manager, and during specific use, the fog manager is responsible for managing fog and fog nodes, specifically including monitoring the state of the fog nodes, maintaining a user interface, registering services to the cloud, and managing the state of service instances (virtual sensors) on the fog nodes, and the fog manager is the owner of the sensors at the same time.
In addition, a user classification unit 90 is connected to an input end of the user information receiving unit 60, and the user classification unit 90 is used for classifying users. When the system is used specifically, the user classification unit 90 can be divided into a remote user and a local user according to the position of the user, and for the remote user, a proper virtual sensor and a proper virtual sensor group template can be selected according to the requirement to send out a use request; multiple virtual sensor templates can be selected according to the actual conditions of the user or the existing virtual sensor group template can be modified to create the virtual sensor group template of the user, and the newly created template can be shared by other users; the state of the virtual sensor can be monitored through a web browser or through an application, and the virtual sensor is activated or cancelled, so that for a local user, a fog node can be selected to provide service under the condition of real-time application or failure of connection with a cloud end, but only the existing service instance on the fog node can be used and the service cannot be created by the fog node.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and the preferred embodiments of the present invention are described in the above embodiments and the description, and are not intended to limit the present invention. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (9)
1. The utility model provides a wisdom logistics park sensing cloud platform based on fog calculates, includes that the sensor deploys the end, the sensor deploys the end and includes sensor acquisition information unit (10), sensor acquisition information unit (10) are used for gathering the data information in each region of wisdom logistics park, its characterized in that: the sensor data collection system is characterized in that the input end of a sensor information collection unit (10) is connected with a sensor virtualization unit (20), the sensor virtualization unit (20) is used for performing virtualization processing on physical sensors, so that sensor data can be shared by a plurality of users, the input end of the sensor information collection unit (10) is further connected with a sensor management unit (30), the sensor management unit (30) is used for classifying and processing each sensor according to data content transmitted by each sensor and is provided with a corresponding management method, the output end of a sensor deployment end is connected with a fog calculation end, the fog calculation end comprises a fog node connection unit (40), the fog node connection unit (40) is responsible for receiving data of the physical sensors, the output end of the fog node connection unit (40) is connected with a data fog calculation unit (50), the data fog calculation unit (50) is used for uploading needed data to a cloud end after simple processing such as filtering, fusion or reconstruction is performed on the data of the physical sensors, and the data is temporarily stored, the output end user information receiving unit (60) is used for determining the user data of the physical sensors.
2. The smart logistics park sensing cloud platform based on fog computing of claim 1, wherein: the sensor information collecting unit (10) comprises a sensor information collecting position determining module (110), the sensor information collecting position determining module (110) is used for determining the position of a collecting place, the output end of the sensor information collecting position determining module (110) is connected with a data content identifying module (120), the data content identifying module (120) is used for determining the content collected by the collecting place, the output end of the data content identifying module (120) is connected with an information collecting output unit (130), and the information collecting output unit (130) is used for classifying the collected information and then distributing the information to all fog nodes.
3. The smart logistics park sensing cloud platform based on fog computing of claim 2, wherein: the sensor management unit (30) comprises a sensor ownership distribution module (310), the sensor ownership distribution module (310) is used for determining managers of each sensor, the output end of the sensor ownership distribution module (310) is connected with an owner authority establishing module (320), the owner authority establishing module (320) is used for establishing corresponding management authorities of the managers after determination, the output end of the owner authority establishing module (320) is connected with a credible relationship establishing module (330), and the credible relationship establishing module (330) is used for establishing credible relationship between the sensors and the corresponding managers.
4. The smart logistics park sensing cloud platform based on fog computing of claim 1, wherein: the data fog calculating unit (50) comprises a data type determining module (510), the data type determining module (510) is used for determining data types of different places, the output end of the data type determining module (510) is connected with a data preprocessing module (520), the data preprocessing module (520) formulates a corresponding data preprocessing mode according to the data types to preprocess data, the output end of the data preprocessing module (520) is connected with a database pre-storing module (530), and the database pre-storing module (530) is used for pre-storing the preprocessed data.
5. The smart logistics park sensing cloud platform based on fog computing of claim 4, wherein: the data preprocessing module (520) adopts a data preprocessing algorithm, and the algorithm formula is as follows:
wherein
For each data set collected by a sensor, based on the data set for each sensor>
To/is>
For each data acquired by the sensor, a decision is made as to whether the data has been stored in a memory>
For a data coincidence decision function>
For the data cluster corresponding to the data needing to be judged, the ^ er>
For data clusters corresponding to previously collected data, based on the previous collection completion>
For data cluster coincidence rates>
For a data cluster coincidence rate threshold, upon a data cluster coincidence rate>
Less than the data cluster coincidence rate threshold>
Time, data coincidence judgment function>
The output is 0, which indicates that the data needing to be judged is not coincident data, and when the coincidence rate of the data cluster is greater than or equal to the preset value>
Not less than the data cluster coincidence rate threshold>
Time, data coincidence judgment function>
The output is 1, which indicates that the data needing to be judged is coincidence numberAccordingly, the data needs to be integrated.
6. The smart logistics park sensing cloud platform based on fog computing of claim 2, wherein: the input end of the sensor information acquisition unit (10) is connected with a sensor distribution unit (70), and the sensor distribution unit (70) is used for monitoring the running state and data receiving of each sensor.
7. The smart logistics park sensing cloud platform based on fog computing of claim 1, wherein: the sensor virtualization unit (20) performs virtualization processing of the physical sensor in eight ways, i.e., a one-to-one correspondence formula, a selection formula, an accumulation formula, an aggregation formula, a limiting formula, a situation limiting formula, a prediction formula, a calculation formula and the like.
8. The smart logistics park sensing cloud platform based on fog computing of claim 1, wherein: the output end of the data fog computing unit (50) is connected with a fog management distribution unit (80), and the fog management distribution unit (80) is used for determining a fog manager and the management authority of the fog manager.
9. The smart logistics park sensing cloud platform based on fog computing of claim 1, wherein: the input end of the user information receiving unit (60) is connected with a user classifying unit (90), and the user classifying unit (90) is used for classifying users.
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