CN110971427A - Internet of things agriculture big data analysis system based on cooperative cooperation - Google Patents
Internet of things agriculture big data analysis system based on cooperative cooperation Download PDFInfo
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Abstract
The invention discloses an Internet of things agriculture big data analysis system based on cooperative work, which comprises: the system comprises a physical layer, a big data layer, a cooperation layer, an application layer and a cross-layer interaction interface, wherein the physical layer is mainly responsible for deploying sensor nodes capable of acquiring various data and collecting diversity data; the big data layer carries out technical processing such as retrieval, cleaning, filtering, sequencing and the like on the data acquired by the physical layer; the cooperative layer is mainly responsible for providing big data transmission reliability guarantee for the big data layer application through an opportunity cooperative communication technology; the application layer can provide services for users in a wireless local area network, 3G/4G mobile communication network and other modes, and the users can access the system to obtain the services through equipment such as a PC (personal computer) or a mobile phone; the cross-layer interactive interface mainly realizes data sharing and self-adaptive intelligent control, effectively improves the agricultural informatization level, improves agricultural comprehensive decision and reduces the agricultural production cost.
Description
Technical Field
The invention belongs to the technical field of big data of the Internet of things, and relates to an Internet of things agriculture big data analysis system based on cooperative cooperation.
Background
With the research and development of wireless communication technology, especially internet of things technology and application platform thereof, the internet of things application technology provides important support and platform for the development of modern agriculture, and becomes one of the hotspots of the research of modern industrial, agricultural and academic industries. The agricultural internet of things technology can effectively enhance supervision and early warning of quality safety of agricultural products, and can effectively improve agricultural comprehensive decision and management level. In addition, based on the application technology platform of the internet of things, the traditional agricultural process can be upgraded, the application, irrigation and fertilization of crops and related animal husbandry and the like can be monitored in real time, the resource utilization rate is improved, the pollution to the environment is reduced, particularly, the crop disease monitoring and common infectious epidemic situation early warning are enhanced, the production economic benefit is improved while the crop yield increasing rate is ensured, and therefore the agricultural modern efficient operation and sustainable development are achieved.
Meanwhile, in the agricultural internet of things, as the monitoring data are various and the data volume is large, how to effectively transmit and process big data becomes one of important challenges.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide an Internet of things agriculture big data analysis system based on cooperative cooperation, a cross-layer interaction analysis model is established by utilizing the Internet of things technology, an opportunity cooperative mechanism and big data processing are combined, the agriculture informatization level is effectively improved, the agriculture comprehensive decision is improved, the agriculture production cost is reduced, and the challenges of reliable data transmission and big data efficient processing in the environment with the characteristics of node mobility, the complexity of a wireless communication environment, high error rate, big data diversity and the like in the agricultural Internet of things are effectively solved.
In order to solve the technical problems, the invention adopts the following technical scheme: an internet of things agriculture big data analysis system based on cooperative work, the system comprises: the system comprises a physical layer, a big data layer, a cooperation layer, an application layer and a cross-layer interaction interface, wherein the physical layer is mainly responsible for deploying sensor nodes capable of acquiring various data and collecting diversity data; the big data layer carries out technical processing such as retrieval, cleaning, filtering, sequencing and the like on the data acquired by the physical layer; the cooperative layer is mainly responsible for providing big data transmission reliability guarantee for the big data layer application through an opportunity cooperative communication technology; the application layer can provide services for users in a wireless local area network, a 3G/4G mobile communication network and other modes, and the users can access the system to obtain the services through equipment such as a PC (personal computer) or a mobile phone; the cross-layer interaction interface mainly realizes data sharing and self-adaptive intelligent control.
Further, the physical layer is mainly divided into a heterogeneous sensor network formed by different types of sensors and an RFID tag capable of acquiring different types of data according to different data acquisition devices.
Further, the big data layer provides 4 modules, namely a sensor acquisition data processing module, a Radio Frequency Identification (RFID) tag data processing module, a diversity application data processing module and an adaptive control data processing module; the sensor data acquisition and processing module is mainly responsible for acquiring data in real time in the agricultural Internet of things; the Radio Frequency Identification (RFID) tag module identifies and receives the data acquired by the sensor data acquisition and processing module; the diversity application data processing module is mainly responsible for retrieving, sequencing and optimizing data; the self-adaptive control data processing module can quickly search the data mapping table items and the Hash elements with high retrieval frequency, reasonable retrieval sequence and minimum interaction interval cost when the internal data and the external data of the terminal are replaced.
Compared with the prior art, the invention has the following beneficial effects:
aiming at the problems of various monitoring data, large data amount and the like in the agricultural Internet of things, the Internet of things technology is utilized, a cross-layer interaction analysis model is established, an opportunity cooperation mechanism and large data processing are combined, the agricultural informatization level is effectively improved, the agricultural comprehensive decision is improved, the agricultural production cost is reduced, and the challenges of reliable data transmission and large data efficient processing in the environments with the characteristics of node mobility, complexity of a wireless communication environment, high error rate, large data diversity and the like in the agricultural Internet of things are effectively solved.
Drawings
FIG. 1 is a collaborative-based Internet of things agricultural big data analysis system architecture diagram.
Detailed Description
The present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which embodiments of the invention are shown. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention.
Referring to fig. 1, the invention provides a collaborative cooperation-based internet of things agricultural big data analysis system, which comprises: the system comprises a physical layer, a big data layer, a cooperation layer, an application layer and a cross-layer interaction interface, wherein the physical layer is mainly responsible for deploying sensor nodes capable of acquiring various data and collecting diversity data; the big data layer carries out technical processing such as retrieval, cleaning, filtering, sequencing and the like on the data acquired by the physical layer; the cooperative layer is mainly responsible for providing big data transmission reliability guarantee for the big data layer application through an opportunity cooperative communication technology; the application layer can provide services for users in a wireless local area network, a 3G/4G mobile communication network and other modes, and the users can access the system to obtain the services through equipment such as a PC (personal computer) or a mobile phone; the cross-layer interaction interface mainly realizes data sharing and self-adaptive intelligent control.
Further, the physical layer is mainly divided into a heterogeneous sensor network formed by different types of sensors and an RFID tag capable of acquiring different types of data according to different data acquisition devices.
Further, the big data layer provides 4 modules, which are a sensor acquisition data processing module, a Radio Frequency Identification (RFID) tag data processing module, a diversity application data processing module and an adaptive control data processing module.
The big data layer is provided with 4 modules which are a sensor acquisition data processing module, a Radio Frequency Identification (RFID) tag data processing module, a diversity application data processing module and an adaptive control data processing module respectively; the sensor data acquisition and processing module is mainly responsible for acquiring data in real time in the agricultural Internet of things; the Radio Frequency Identification (RFID) tag module identifies and receives the data acquired by the sensor data acquisition and processing module; the diversity application data processing module is mainly responsible for retrieving, sequencing and optimizing data; the self-adaptive control data processing module can quickly search the data mapping table items and the Hash elements with high retrieval frequency, reasonable retrieval sequence and minimum interaction interval cost when the internal data and the external data of the terminal are replaced.
In addition, in order to improve the data mining efficiency and precision, databases for storing different types of data are established in a large data layer, so that multi-condition retrieval aiming at a specific database is realized. Meanwhile, aiming at big data of different types and sources, the system adopts a combined retrieval mode combining single-table retrieval and multi-table retrieval. And processing the results obtained by the joint retrieval by using technologies such as cleaning, filtering, sequencing and the like, and then transmitting the results to the user through an opportunistic cooperation technology of a cooperative communication layer. The user can access different types of databases to realize diversified retrieval, and each type of database on the layer can provide a full-text retrieval function so as to provide a humanized interaction form and a visual big data analysis result for the user.
The model adopts the specific implementation of an opportunity cooperation mechanism in the big data processing based on opportunity cooperation as follows:
in the agricultural Internet of things, various communication terminals on a physical layer form a communication subnet, and an opportunity cooperative communication mode is adopted to forward data. In the cooperative communication process, the node with a closer distance or a better channel state is selected and considered as the next hop forwarding node in the initial state. In the wireless communication process, because the nodes have random mobility, the wireless signals, namely the data packets, are also received when the nodes move from the direction of the destination node to the sending node. The source node S sends a data packet to the sink node H, the random moving distance of the H node is longer and longer than that of the S node, so that the data reception fails, at the moment, the R1 node is approaching the S node and is used as a next-hop relay forwarding node with a certain probability, and meanwhile, the R2 node is approaching the S node at a speed 2 times that of the R1 node, so that a certain chance is better than that of the R1 serving as an optimal relay node to help the data packet to reach the destination node H.
Therefore, the R1 and R2 can monitor the data packets transmitted or forwarded by other nodes during the moving process, and if the data packets transmitted or the wireless signals broadcasted by other nodes can be correctly decoded, the data packets can be used as relay nodes with a certain probability to improve the reliability of data transmission. In addition, in the Internet of things system, a user can directly access the sink node through a mobile phone terminal to perform self-adaptive real-time intelligent control. The communication distance for the source node S to send the wireless signal to the sink node H is shown in formula (1):
the communication distance between any 2 nodes can also be obtained by equation (1). The moving sensing distance when a certain node is close to the source node can be obtained by the formula (2), and the moving distance when the certain node is far from the source node can be solved by the formula (3).
L1＝vt (2)
Where t represents the time interval during which the source node transmits a wireless signal,
representing the time interval over which the receiving node broadcasts wirelessly. According to the analysis results of L1 and L2, a second derivative of the moving speed of the node can be obtained by using the opportunity principle, and the probability of opportunity forwarding data and the correct receiving rate of data packets are respectively shown as formulas (4), (5) and (6):
in addition, the transmission power of the source node S or other forwarding nodes can be obtained by combining equations (4), (5) and (6), as shown in equation (7):
and establishing a diversity big data processing mechanism based on the established opportunity cooperative communication model of the Internet of things. And establishing a mapping mechanism of each type of database based on the data type perception characteristic, and improving the data processing performance based on a production line.
In an actual big data processing system, because it is difficult to accurately predict a database and a data map to be retrieved by a user, it is proposed that in the big data processing system OCA, data processing flow is realized on a process basis. A buffer area is established among different data processing jobs, and a diversity data mapping Hash two-dimensional matrix is stored in the buffer area so as to carry out sequencing and optimization processing. Meanwhile, the locality of big data multi-type mapping and the data workflow interaction mode are considered in the data joint retrieval process. Therefore, the OCA can quickly search the data mapping table entry and the Hash element which have high retrieval frequency, reasonable retrieval sequence and minimum interaction interval cost when the internal data and the external data of the terminal are replaced. The cache big data stored in the big data processing buffer area among the operation flows are mapped to be a preferred matching item, data groups which are reliably transmitted based on opportunity cooperation are mapped to Hash table items in various databases of the big data layer from a link layer, corresponding parameters are initialized, and the Hash table items are comprehensively evaluated and updated according to various types of parameters of the big data to provide support for the next service. According to the multi-node request buffering principle and the inter-workflow buffer processing mechanism, the workflow big data processing throughput rate can be obtained and is obtained by the formula (8).
Only where k represents the number of large data processing requests initiated by the user. The big data processing algorithm based on opportunistic cooperation is as follows:
inputting a job flow mapping i;
and outputting the large data processing speed v.
1)i＝1,p＝0,Pbit＝0。
2) After the big data processing of the primary operation flow is finished, P, P are obtained according to the combined formula (5) and formula (6) of formula (4)bitThen, the Hash matrix and the job flow number i are updated.
3) And if mu is less than 0.5, carrying out a new round of opportunity cooperative relay node selection and data flow optimization processing.
4) Otherwise, the protection site continues to carry out data forwarding and job flow optimization processing.
5) If the job flow number i is larger than n, finishing the big data processing; otherwise, repeating the steps 2) to 4).
In the algorithm, the Hash matrix and the serial number of the big data workflow and the moving speed of the node are initialized firstly. Secondly, updating a Hash table entry and a moving speed second derivative of a buffer area between the operation flows in time, monitoring the throughput rate of processing the big data in real time, and if the throughput rate is less than 0.5, updating the mapping of the database; if the second derivative of the big data processing speed and the throughput rate can be kept in a certain optimization state, the data processing is carried out according to the operation flow step by step according to the user requirements. In addition, a heterogeneous and multi-source big data integration processing method is realized through components (a query module for packaging multi-source data sources), in order to realize multi-source and heterogeneous big data integration and sharing and reduce the number of conversion codes of different data types, XML is used as a data conversion format, different big data objects are optimized into uniform global data, and then the different components are used for accessing the multi-source heterogeneous big data. On the basis of analyzing the heterogeneous and multi-source big data integration processing mechanism and method, in order to realize a big data mining task of an agricultural Internet of things and better improve the performance of a big data processing system, a data mining design scheme based on a B/S structure cloud computing service mode is provided, and the data mining design scheme mainly comprises 5 parts such as 1 database group, 1 server group, a big data management subsystem, a big data mining subsystem and a mining algorithm subsystem.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (3)
1. Internet of things agriculture big data analysis system based on cooperative work, which is characterized in that the system comprises: the system comprises a physical layer, a big data layer, a cooperation layer, an application layer and a cross-layer interaction interface, wherein the physical layer is mainly responsible for deploying sensor nodes capable of acquiring various data and collecting diversity data; the big data layer carries out technical processing such as retrieval, cleaning, filtering, sequencing and the like on the data acquired by the physical layer; the cooperative layer is mainly responsible for providing big data transmission reliability guarantee for the big data layer application through an opportunity cooperative communication technology; the application layer can provide services for users in a wireless local area network, a 3G/4G mobile communication network and other modes, and the users can access the system to obtain the services through equipment such as a PC (personal computer) or a mobile phone and the like; the cross-layer interaction interface mainly realizes data sharing and self-adaptive intelligent control.
2. The collaborative Internet of things agriculture big data analysis system according to claim 1, wherein the physical layer mainly comprises a heterogeneous sensor network composed of different types of sensors and RFID tags capable of collecting different types of data according to different data collection devices.
3. The collaborative-collaboration-based internet of things agricultural big data analysis system according to claim 1, wherein the big data layer provides 4 modules, namely a sensor acquisition data processing module, a Radio Frequency Identification (RFID) tag data processing module, a diversity application data processing module and an adaptive control data processing module; the sensor data acquisition and processing module is mainly responsible for acquiring data in real time in the agricultural Internet of things; the Radio Frequency Identification (RFID) tag module identifies and receives the data acquired by the sensor data acquisition and processing module; the diversity application data processing module is mainly responsible for retrieving, sequencing and optimizing data; the self-adaptive control data processing module can quickly search the data mapping table items and the Hash elements with high retrieval frequency, reasonable retrieval sequence and minimum interaction interval cost when the internal data and the external data of the terminal are replaced.
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| CN112328183A (en) * | 2020-11-26 | 2021-02-05 | 郑州数农通大数据科技有限公司 | Crop information storage system based on Internet of things agricultural big data |
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