CN110972118B - Duplex-mode social interaction relationship data acquisition platform and method - Google Patents

Duplex-mode social interaction relationship data acquisition platform and method Download PDF

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CN110972118B
CN110972118B CN201911193200.2A CN201911193200A CN110972118B CN 110972118 B CN110972118 B CN 110972118B CN 201911193200 A CN201911193200 A CN 201911193200A CN 110972118 B CN110972118 B CN 110972118B
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CN110972118A (en
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蔡萌
李彬
陈晨
崔颖
李素霞
刘晓
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Xian Jiaotong University
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    • H—ELECTRICITY
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Abstract

The invention discloses a duplex mode social interaction relationship data acquisition platform and a duplex mode social interaction relationship data acquisition method, wherein the duplex mode social interaction relationship data acquisition platform comprises a comprehensive controller, an Internet of things node coordinator and a plurality of Internet of things sensing nodes; and the test object utilizes the sensing node of the Internet of things worn by the test object to realize the collection of social interaction behavior data. Specifically, the method comprises the following steps: the node of the Internet of things utilizes the ultrasonic receiving and transmitting module to measure the relative position of personnel and transmits the data through the radio frequency receiving and transmitting module of the wireless sensing node. Data transmission has two working modes of centralized type and distributed type. For centralized data transmission, a plurality of internet of things node data are transmitted to the internet of things node coordinators in a wireless multi-hop mode and are collected at the integrated controller. For distributed data transmission, a node coordinator is not needed, and only the nodes of the adjacent Internet of things are needed to carry out iterative information transmission, so that the interactive information of the nodes of the whole network is acquired.

Description

Duplex-mode social interaction relationship data acquisition platform and method
Technical Field
The invention belongs to the technical field of intersection of information science and social science, and particularly relates to a duplex-mode social interaction relationship data acquisition platform and method, which are used for providing objective and accurate relationship type data for social science research.
Background
In recent years, rapid development of information technology deeply influences the interaction modes and interrelations of individuals and organizations, and causes great impact on different cultural groups and social structures of the human society, thereby leading to rapid improvement of social complexity and interaction degree. Traditional human society science is difficult to carry out rigorous reasoning and accurate quantitative calculation, and can not meet various modeling, analyzing, managing and controlling challenges brought by a modern network society with complex dynamics. Under the background, based on the urgent real needs of understanding complex human activities and network society, the introduction of the technical methods of information science and computer science into social science becomes a necessary choice.
The occurrence reasons and evolution mechanisms of a plurality of daily social activities can be effectively explained through the analysis and research of social interaction behaviors, and the behavior body, behavior process and trigger results in the public management process can be effectively controlled, dredged and solved by fully mastering and scientifically measuring the characteristics of the social interaction behaviors. However, due to the lack of deep cross-fusion of natural and social scientific research, there are still some disadvantages in the current research: in the aspect of research paradigm, social science researchers rely more on qualitative paths to analyze cases due to lack of data and limitation of methods, and generally accepted rules are difficult to obtain; however, natural science researchers try to reveal the evolution mechanism of the relevant problems by theoretical analysis and simulation calculation by means of the advantages of the methods, but the applicability of the corresponding research results is still to be tested due to the lack of deep grasp of relevant social situations and individual differences. In the aspect of data research, social interaction behaviors represented by group events have the characteristics of emergencies, difficult process recurrence and the like, the traditional social science data acquisition strategy cannot meet the requirements, corresponding data are lacked in social science research, and even data analyzed on individual cases are mostly from literature reports; although researchers in natural science acquire relevant network data by using technical means, the data basically lack social background information, for example, social attribute information (including sex, age, education and the like) of individuals in the network is lacked, so that research results are often difficult to deeply explain. In the aspect of research methods, currently, politicians, sociologists, physicists and the like respectively analyze and research relevant problems from respective perspectives, and respectively pay attention to political connotation, social influence and simulation models, however, traditional single-subject research cannot meet the requirements of social management development, and complexity of social interaction behavior requires multidisciplinary cross research. Therefore, the acquisition of social interaction behavior data is crucial to the research and solution of the above-mentioned complex social problems. The method is an academic requirement for researching and solving complex social problems, and is a practical requirement for maintaining good social order, innovating social management and promoting harmony and stability.
Data is used as the basis of scientific research, and the collection and measurement of the data are always an important link for social demonstration research. But due to the complexity of social interaction behavior and privacy of social relationships, the collection of relationship data has long been a significant bottleneck limiting relevant research. A large body of literature indicates that traditional data acquisition methods have been difficult to meet the needs of contemporary social scientific research, such as: document (1) flourishing han, Zhan, Du Jian and so on, theory and application of social scientific calculation experiments, Shanghai triple bookshop, 2009.7; literature (2) the significance, development and research status of social calculations, e-Science forum, 2010.7; reference (3) Fischbach K., Gloor P.A., Schoder D.analysis of Information Communication Networks-Case study. Business & Information Systems engineering.2009,1(2): 140-149; document (4) wang leap, artificial society, computational experiments, parallel systems-discussion on computational research of complex socioeconomic systems, complex systems and complex science 2004.10. The literature (1) indicates that it is difficult to accurately describe the laws and features of social problems only by qualitative description or case analysis. The document (2) indicates that the traditional social investigation is difficult to implement, needs to invest a large amount of cost and has difficult guarantee of data quality. Document (3) states that relational data obtained by unreasonable data collection methods, particularly subjective data collected through a single channel, does not truly reflect the reality of an actor's social network. Document (4) indicates that, in the conventional data acquisition process, interventional measurement is mostly adopted, and data acquisition under such unnatural circumstances is prone to errors and has privacy and ethical problems.
Disclosure of Invention
In order to solve the above problems, the present invention provides a duplex social interaction relationship data collection platform and method, which can accurately collect interaction data between samples without interfering with normal activities of the samples.
The invention adopts the following technical scheme:
a duplex mode social interaction relationship data acquisition platform comprises:
the wearable Internet of things nodes are used for transmitting first signals to the surroundings, searching adjacent Internet of things nodes by using the first signals, and recording and storing the numbers of the Internet of things nodes adjacent to the nodes when the adjacent Internet of things nodes are searched; when the first signal transmitted by the node of the Internet of things adjacent to the node of the Internet of things is received again, the node of the Internet of things adjacent to the node of the Internet of things transmits a second signal at the same time, the distance between the node of the Internet of things adjacent to the node of the Internet of things is calculated by using the second signal, and whether interaction is carried out with the node of the Internet of things adjacent to the node of the Internet of things is judged according to the distance; when the nodes of the internet of things adjacent to the nodes of the internet of things are judged to be interacting, recording and storing the numbers of the nodes of the internet of things adjacent to the nodes of the internet of things, the distances between the nodes of the internet of things adjacent to the nodes of the internet of things, and the interaction starting time and the interaction ending time between the nodes of the internet of things adjacent to the nodes of the internet of things;
the Internet of things node coordinator is used for periodically sending a query instruction to the Internet of things nodes, enabling the Internet of things nodes receiving the query instruction to upload the number of the Internet of things nodes, the number of the Internet of things nodes interacting with the Internet of things nodes, the distance between the Internet of things nodes interacting with the Internet of things nodes, and the interaction starting time and the interaction ending time between the Internet of things nodes interacting with the Internet of things nodes, and uploading received data;
and the integrated controller is used for receiving the data uploaded by the nodes coordinators of the Internet of things.
The node of the Internet of things comprises a slave ARM main control module, a slave radio frequency transceiving module, an ultrasonic transceiving module, a time synchronization module, an operation unit, a storage module and a power module, wherein the slave radio frequency transceiving module, the ultrasonic transceiving module, the operation unit, the time synchronization module and the storage module are all connected with the slave ARM main control module, the power module is respectively connected with the slave ARM main control module, the slave radio frequency transceiving module, the ultrasonic transceiving module, the operation unit, the time synchronization module and the storage module, and the operation module is connected with the storage module;
the ultrasonic receiving and transmitting module is used for transmitting and receiving ultrasonic signals;
the slave radio frequency transceiving module is used for transmitting and receiving radio frequency signals;
the time synchronization module is used for controlling the ultrasonic transceiver module and the radio frequency transceiver module to synchronously transmit signals and recording the time points of the ultrasonic transceiver module and the radio frequency transceiver module for receiving the signals;
the slave ARM main control module is used for calculating the distance between the two nodes of the Internet of things through the received echo time difference of the received ultrasonic wave signals and judging whether the two nodes of the Internet of things are interacted or not according to the distance; the slave ARM main control module is also used for identifying the number of the node of the Internet of things which transmits the received radio frequency signal according to the radio frequency signal received from the radio frequency transceiver module; the slave ARM main control module is also used for recording the serial number of the node of the Internet of things where the slave ARM main control module is located, the serial number of the node of the Internet of things which is communicated with the node of the Internet of things where the slave ARM main control module is located, the distance between the node of the Internet of things which is communicated with the node of the Internet of things where the slave ARM main control module is located and data recorded by the time synchronization module, and uploading and storing the data recorded by;
the Internet of things node coordinator comprises a main ARM main control module and a main radio frequency transceiving module; the main ARM main control module is used for controlling the main radio frequency transceiver module to periodically send a query instruction to the Internet of things node, and the Internet of things node which receives the query instruction uploads the data stored in the storage module by the Internet of things node.
A duplex mode social interaction relationship data acquisition method comprises the following steps:
s1, each Internet of things node periodically transmits a first signal to the surroundings, Internet of things nodes which can receive the first signal mutually are adjacent to each other, and in the adjacent Internet of things nodes, each Internet of things node records and stores the serial number of the Internet of things node adjacent to the node;
for any two internet of things nodes in the adjacent internet of things nodes, when one of the internet of things nodes receives the first signal transmitted by the other internet of things node again, the two internet of things nodes transmit a second signal at the same time, and the second signal is used for calculating the distance between the two internet of things nodes;
when the distance between any two nodes of the Internet of things is not greater than a set interaction threshold value, judging that the two nodes of the Internet of things are interacting, otherwise, judging that the two nodes of the Internet of things are not interacting;
when two Internet of things nodes are judged to interact, each Internet of things node records and stores the number of the node, the number of the Internet of things node interacting with the node, the distance between the Internet of things nodes interacting with the node, and the interaction starting time and the interaction ending time between the Internet of things nodes interacting with the node;
s2, the Internet of things node coordinator periodically sends a query instruction to each Internet of things node to query all the Internet of things nodes in a circulating mode, after the query instruction is received by the Internet of things nodes, each Internet of things node uploads data to the Internet of things node coordinator, the Internet of things node coordinator uploads the data uploaded by the Internet of things nodes to the integrated controller, and the data uploaded by each Internet of things node to the Internet of things node coordinator comprises the number of the node, the number of the Internet of things node interacting with the node, the distance between the Internet of things nodes interacting with the node, and the interaction start time and the interaction end time between the Internet of things nodes interacting with the node.
In S2, after the Internet of things node coordinators periodically send query instructions to each Internet of things node, the Internet of things nodes upload data to the Internet of things node coordinators in sequence in a preset interaction period according to the sequence of respective numbers; when one Internet of things node does not upload data in the interaction period, the next Internet of things node starts to upload data to the Internet of things node coordinator;
when the nodes of the Internet of things do not upload data in the interaction period, judging whether the nodes of the Internet of things and the nodes of the Internet of things coordinator have communication faults or not, if so, acquiring data by all the nodes of the Internet of things according to a distributed information transmission mode; and otherwise, the Internet of things node coordinator transmits the received data of the Internet of things node to the integrated controller.
The process of judging whether the communication fault occurs between the Internet of things node and the Internet of things node coordinator comprises the following steps:
(a) calculating the fault proportion of the nodes of the Internet of things;
(b) judging the size of the fault proportion obtained in the step (a) and a set fault threshold, if the fault proportion is not less than the fault threshold, judging that communication fault occurs, otherwise, judging that the communication is normal;
the fault proportion is the proportion of the number of the nodes of the internet of things with communication faults in the total number of the nodes of the internet of things.
The process that all nodes of the Internet of things acquire data according to the distributed information transmission mode comprises the following steps:
firstly, each Internet of things node carries out S1, and recorded and stored data are placed at the tail of each storage sequence;
then, each Internet of things node in the mutually adjacent Internet of things nodes sends the head information of the respective storage sequence to the adjacent Internet of things node, receives the head information sent by the adjacent Internet of things node, and stores the received head information to the tail of the respective storage sequence; repeatedly carrying out information interaction on each Internet of things node and adjacent Internet of things nodes until the interaction information of all the Internet of things nodes is stored in the storage sequence of each Internet of things node;
the first information is the earliest interactive information in the information which is not transmitted in the storage sequence of the nodes of the Internet of things.
After the mutual information of all the internet of things nodes is stored in the storage sequence of each internet of things node, all the internet of things nodes are collected and form a communication network, and the whole social interaction relationship information is obtained by adopting a distributed information transmission mode; the distributed information transmission mode for obtaining the information of the whole social interaction relationship comprises the following steps:
1) initializing a transmission data vector of each Internet of things node;
2) each Internet of things node transmits data vectors with adjacent Internet of things nodes capable of communicating, and the data vectors are updated according to an average consistency algorithm; and after iteration is carried out for a preset number of times according to the average consistency algorithm, the updated data vector of the current Internet of things node is the social interaction relationship information of the whole Internet of things.
In the step 1), initializing a transmission data vector of each node of the internet of things includes:
in M nodes of the Internet of things, for any node M of the Internet of things, a column vector S with 4 storage sequences and M dimensions is providedm、Em、DmAnd Nm；
Wherein S ismStoring a vector for the interaction start time of the Internet of things node m, EmStoring a vector, D, for the interaction end time of the Internet of things node mmStoring a vector, N, for the interaction distance of the node m of the Internet of thingsmThe number of the Internet of things node interacting with the Internet of things node m is numbered;
four column vectors S to node m of the Internet of thingsm,Em,DmAnd NmThe process of performing initialization includes: setting the ith position in each column vector of the node m of the Internet of things as
Figure GDA0002339007500000061
And
Figure GDA0002339007500000062
the remaining positions are all 0; wherein,
Figure GDA0002339007500000063
Figure GDA0002339007500000064
Figure GDA0002339007500000065
Figure GDA0002339007500000066
wherein,
Figure GDA0002339007500000071
representing a vector
Figure GDA0002339007500000072
Data of the ith position of (a);in order to be the start time of the interaction,
Figure GDA0002339007500000074
as interaction end time, dmjAnd j is the number of the internet of things node interacting with the internet of things node.
In the step 2), an iterative formula of an average consensus algorithm for any internet of things node m is as follows:
Figure GDA0002339007500000075
wherein,
Figure GDA0002339007500000076
representing the vector S in the k-th iterationm、Em、DmOr Nm，JmA set of neighboring internet of things nodes representing node m,mrthe information iteration step length of the node m and the node r of the Internet of things is obtained;
selecting information iteration step length when updating data vectormrAnd setting the number of iterations, and using the iteration formula of the average consensus algorithm to enable
Figure GDA0002339007500000077
Convergence to the initial average of all nodes
Figure GDA0002339007500000078
Updating of the data vector is realized;
the average value of the initial value
Figure GDA0002339007500000079
The mutual information of all nodes of the whole internet of things network is averaged by the initial value
Figure GDA00023390075000000710
As social interaction relationship information of the whole Internet of things;
wherein, the information iteration step length is selectedmrThe process comprises the following steps:
determining a network topology structure of the Internet of things where all the nodes of the Internet of things form;
for the condition that the topological structure of the network of the Internet of things is unchanged and known, the information iteration step length is selected according to the following processmr: setting the information iteration step length as a fixed value,mr＝＝2/[λ2(L)+λM(L)](ii) a Wherein λ isi(L) represents the ith (i belongs to {1,2, …, M }) eigenvalue after the eigenvalues of the Laplace matrix L of the network diagram of the Internet of things are arranged in an ascending order;
for the condition that the topological structure of the network of the Internet of things is dynamically changed and each node of the Internet of things does not know the topological structure of the whole network, the information iteration step lengthmrComprises the following steps:
Figure GDA00023390075000000711
wherein n ismAnd representing the degree of the node m of the Internet of things.
Mean value of initial value
Figure GDA00023390075000000712
Specifically, the average value of the number of the four column vectors to all the nodes of the internet of things is
Figure GDA00023390075000000713
And
Figure GDA00023390075000000714
and
Figure GDA00023390075000000715
respectively as follows:
Figure GDA0002339007500000081
Figure GDA0002339007500000082
Figure GDA0002339007500000083
Figure GDA0002339007500000084
wherein j ismAnd the number of the Internet of things node interacting with the Internet of things node m is represented. The specific algorithm is completed by an arithmetic unit, and the arithmetic unit is realized by a 8051-based single chip microcomputer or a Digital Signal Processor (DSP); the arithmetic unit mainly comprises multiplication and addition operations. The operation unit needs to be connected with the communication module through an interface and used for receiving node information of the adjacent Internet of things
Figure GDA0002339007500000085
And transmitting the updated node information
Figure GDA0002339007500000086
The invention has the following beneficial effects:
in the duplex-mode social interaction relationship data acquisition platform, each Internet of things node can search the Internet of things nodes adjacent to the Internet of things node and calculate the distance between the Internet of things nodes, information interaction can be carried out between the adjacent Internet of things nodes, and each Internet of things node can record and store the number of the Internet of things node, the number of the Internet of things node adjacent to the Internet of things node, the distance between the Internet of things nodes adjacent to the Internet of things node, and the interaction starting time and the interaction ending time between the Internet of things nodes adjacent to the Internet of things node; all internet of things nodes can upload information according to the query command of the internet of things node coordinator, the internet of things node coordinator uploads the uploaded information to the integrated controller, interaction data between samples are acquired, the internet of things nodes can be worn on an object, the object acquires data in a non-intervention mode by using the internet of things nodes when moving, the internet of things nodes can acquire sample data under natural conditions, social interaction behavior data distortion caused by subjective factors can be effectively eliminated, and accuracy of data acquisition is greatly improved.
When the method for collecting the social interaction relationship data in the duplex mode is carried out, sample data can be collected under natural conditions, and the social interaction behavior data distortion of a collected object caused by subjective factors is effectively eliminated, so that the normal activity of the sample cannot be interfered, and the accuracy of data collection is greatly improved.
Drawings
FIG. 1 is a schematic structural diagram of a duplex-mode social interaction relationship data acquisition platform according to the present invention;
FIG. 2 is a schematic diagram of a distributed information transmission mode according to the present invention;
FIG. 3 is a block diagram of a node of the Internet of things of the present invention;
FIG. 4 is a flow chart of a social interaction behavior data collection method of the present invention.
Detailed Description
The embodiments and effects of the present invention will be described in further detail below with reference to the accompanying drawings.
Referring to fig. 1, the duplex-mode social interaction relationship data acquisition platform of the present invention comprises: the system comprises a comprehensive controller, an Internet of things node coordinator and a plurality of Internet of things nodes; the Internet of things node can be worn on an experimental object and used for acquiring social interaction relationship data of the experimental object and transmitting the acquired social interaction relationship data to the Internet of things node coordinator through a serial port communication protocol, and the Internet of things node coordinator is used for collecting and uploading the social interaction relationship data acquired by the Internet of things node to the integrated controller; the comprehensive controller can analyze and process the received social interaction behavior data.
Referring to fig. 3, the node of the internet of things includes a slave ARM main control module, a slave radio frequency transceiver module, an ultrasonic transceiver module, a time synchronization module, a storage module, an operation unit, a power module and an RS232 serial port module, wherein the power module is used for supplying power to each module, the RS232 serial port module is used for communicating with a coordinator of the node of the internet of things, and the operation unit is used for realizing a related algorithm during distributed communication, is connected with the ARM main control module, and is connected with the storage module;
the Internet of things node coordinator comprises a main ARM main control module and a main radio frequency transceiving module;
the time synchronization module is used for controlling each internet of things node to synchronously transmit signals and recording the time point of receiving the signals of each internet of things node; the slave ARM main control module calculates the distance between the two Internet of things nodes through the obtained echo time difference of the ultrasonic waves and the radio waves, and judges whether the distance between the two Internet of things nodes is smaller than a set interaction threshold value or not, if yes, the two Internet of things nodes are judged to be interacting, and if not, the two nodes are judged not to be interacting; the slave ARM main control module is also used for recording the node number of the internet of things of the computer, the node number of the internet of things communicated with the slave ARM main control module and the distance between two nodes of the internet of things, and storing the recorded data in the storage module;
the storage data of the storage module is transmitted to the Internet of things node coordinator through a serial port communication protocol, the main ARM main control module controls the main radio frequency transceiver module to send out a query instruction, the Internet of things nodes are searched circularly, and the queried Internet of things nodes are instructed to upload collected data information; the main radio frequency transceiver module receives data information uploaded by the Internet of things node and transmits the data information to the integrated controller through the serial port communication module, and therefore social interaction behavior data are collected and transmitted.
In one embodiment of the present invention, the serial port communication module is an RS232 serial port module; the RS232 serial port module is connected with the integrated controller through a DB9 serial port line.
According to one embodiment of the invention, the master ARM master control module and the slave ARM master control module are respectively a low-power ARM master control chip.
In an embodiment of the present invention, the storage module is a flash memory.
In an embodiment of the present invention, the serial port communication protocol is a custom ARM radio frequency transmission protocol.
According to one embodiment of the invention, the information transmission mode of the data acquisition platform is a centralized information transmission mode or a distributed information transmission mode.
Under normal conditions, a centralized information transmission mode is adopted for operation, and when communication faults occur, a distributed information transmission mode (as shown in fig. 2) is adopted, each node of the internet of things serves as a temporary storage to store interactive information.
The Internet of things coordinator and each Internet of things node comprise power modules which are used for supplying power to the Internet of things coordinator and ensuring normal work of the Internet of things coordinator and each Internet of things node.
The acquisition platform of the invention mainly obtains interpersonal interaction relationship data between objects according to the TDOA ranging technology and the interaction state of the Internet of things nodes worn by the objects, wherein the interpersonal interaction relationship data comprises information such as sample numbers and sample interaction duration, provides real and complete social interaction behavior data, and improves the accuracy of social experiments.
Based on the collection platform and referring to fig. 4, the invention provides a social interaction relationship data collection method in a duplex mode, which operates in a centralized information transmission mode, namely, a main ARM main control module of an internet of things node coordinator controls a main radio frequency transceiver module to send out a query instruction, circularly searches internet of things nodes, and commands the queried internet of things nodes to upload collected social interaction behavior data;
the method comprises the following steps:
s1, each Internet of things node periodically transmits radio frequency signals to the surroundings from the radio frequency transceiver module, and simultaneously can receive radio frequency signals transmitted by other Internet of things nodes so as to search Internet of things nodes (namely broadcast messages) adjacent to the node, the Internet of things nodes which can receive the radio frequency signals mutually are adjacent to each other, and in the adjacent Internet of things nodes, each Internet of things node records and stores the serial number of the Internet of things node adjacent to the node;
for any two internet of things nodes in the adjacent internet of things nodes, when one of the internet of things nodes receives a radio frequency signal transmitted by the other internet of things node again, the two internet of things nodes transmit ultrasonic signals through respective ultrasonic transceiver modules at the same time, and the distance between the two internet of things nodes is calculated by utilizing the ultrasonic signals; the distance between the nodes of the internet of things is measured by adopting a TDOA (time difference of arrival) ranging method.
When the distance between any two nodes of the Internet of things is not greater than a set interaction threshold value, judging that the two nodes of the Internet of things are interacting, otherwise, judging that the two nodes of the Internet of things are not interacting;
when two Internet of things nodes are judged to interact, each Internet of things node records and stores the number of the node, the number of the Internet of things node interacting with the node, the distance between the Internet of things nodes interacting with the node, and the interaction starting time and the interaction ending time between the Internet of things nodes interacting with the node;
s2, the Internet of things node coordinator periodically sends a query instruction to each Internet of things node to query all the Internet of things nodes in a circulating manner, after the nodes of the Internet of things receive the query command, the corresponding data information of each node of the Internet of things is read from the ARM main control module, and the Internet of things node coordinators feed back ACK data packets by uploading data from the radio frequency transceiving module to the Internet of things node coordinators, and the data uploaded to the Internet of things node coordinator by each Internet of things node comprises the number of the node, the number of the Internet of things nodes interacted with the node, the distance between the Internet of things nodes interacted with the node, and the interaction starting time and the interaction ending time between the Internet of things nodes interacted with the node.
In S2, after the Internet of things node coordinators periodically send query instructions to each Internet of things node, the Internet of things nodes upload data to the Internet of things node coordinators in sequence in a preset interaction period according to the sequence of respective numbers; when one Internet of things node does not upload data in the interaction period, the next Internet of things node starts to upload data to the Internet of things node coordinator;
when the nodes of the Internet of things do not upload data in the interaction period, judging whether the nodes of the Internet of things and the nodes of the Internet of things coordinator have communication faults or not, if so, acquiring data by all the nodes of the Internet of things according to a distributed information transmission mode; and otherwise, the Internet of things node coordinator transmits the received data of the Internet of things node to the integrated controller.
The slave ARM main control module of the node of the Internet of things judges the information source in an interaction period, and if the information comes from the coordinator of the Internet of things, the slave ARM main control module executes the query instruction of the coordinator of the node of the Internet of things; if the information comes from the adjacent Internet of things nodes, measuring the distance between the information and the adjacent Internet of things nodes and carrying out information interaction; if no information source exists, the slave ARM main control module controls the ultrasonic transceiver module of the node of the Internet of things where the slave ARM main control module is located to pause working.
As a preferred embodiment of the present invention, in S2, after the node coordinator of the internet of things periodically sends a query instruction to each node of the internet of things, the nodes of the internet of things sequentially upload data to the node coordinator of the internet of things within a preset interaction period according to the sequence of their numbers; when one Internet of things node does not upload data in the interaction period, the next Internet of things node starts to upload data to the Internet of things node coordinator;
when the nodes of the Internet of things do not upload data in the interaction period, judging whether the nodes of the Internet of things and the nodes of the Internet of things coordinator have communication faults or not, if so, acquiring data by all the nodes of the Internet of things according to a distributed information transmission mode; and otherwise, the Internet of things node coordinator transmits the received data of the Internet of things node to the integrated controller.
In an embodiment of the present invention, the determining whether the communication fault occurs between the internet of things node and the internet of things node coordinator specifically includes:
(a) calculating the fault proportion of the nodes of the Internet of things;
(b) judging the size of the fault proportion in the step (a) and a set fault threshold, if the fault proportion is not less than the fault threshold, judging that communication fault occurs, otherwise, judging that the communication is normal;
the fault proportion is the proportion of the number of the nodes of the internet of things with communication faults in the total number of the nodes of the internet of things. The fault threshold value can be set according to factors such as the number of nodes in the internet of things, test time and the like, for example, 1/3, 1/4 and the like.
In an embodiment of the present invention, the distributed information transmission mode is used for performing information interaction between each node of the internet of things and neighboring nodes thereof, so that each node of the internet of things has interaction information of all nodes in the whole internet of things, and the distributed information transmission mode specifically includes:
firstly, transmitting a radio frequency signal to the periphery of each Internet of things node from a radio frequency transceiver module of each Internet of things node, searching for adjacent Internet of things nodes, receiving the radio frequency signal and an ultrasonic signal transmitted by the adjacent Internet of things nodes, calculating the distance between each Internet of things node and each Internet of things node adjacent to the Internet of things node by using the ultrasonic signal, judging the interaction state of each Internet of things node and each Internet of things node adjacent to the Internet of things node, recording and storing the interaction information, and putting the interaction information into the tail part of a storage sequence of the Internet of things node;
in an embodiment of the present invention, the interaction information is: interaction start time
Figure GDA0002339007500000131
End time of interaction
Figure GDA0002339007500000132
Interaction distance dmj(namely the distance between adjacent internet of things nodes) and the internet of things node number j for information interaction with the internet of things node.
Wherein,
Figure GDA0002339007500000133
at a timeIn the interaction process, the moment when the node of the Internet of things transmits radio frequency signals to the periphery of the node of the Internet of things;
Figure GDA0002339007500000134
the moment when the node of the internet of things receives the last ultrasonic signal of the node of the internet of things adjacent to the node of the internet of things in each interaction process; the interaction process is an information transmission process when the interaction state of the Internet of things node and the neighbor node is interaction.
Secondly, each Internet of things node carries out second information interaction, namely each Internet of things node sends the head information of the storage sequence to the adjacent Internet of things node, and the adjacent Internet of things node stores the received head information to the tail of the storage sequence; the node of the Internet of things receives the head information of the neighbor node sent by the node of the Internet of things adjacent to the node of the Internet of things, and stores the head information to the tail of the self storage sequence; repeatedly carrying out information interaction on each Internet of things node and the adjacent Internet of things nodes for multiple times until the interaction information of all the Internet of things nodes is stored in the storage sequence of each Internet of things node, namely, completing the interaction of the whole network node;
the first information is the earliest interactive information in the information which is not transmitted in the storage sequence of the node of the Internet of things; and the nodes of the Internet of things send information to the neighbor nodes of the Internet of things according to a preset time interval.
In an embodiment of the present invention, the determining the interaction state between the internet of things node and each neighboring node specifically includes: with the variable c being 0-1mjRepresenting the interaction state of the node m and the node j; setting the node m as a node for detecting and recording the interaction information, and if the node j is within the interaction threshold value of the node m, interacting the node j and the node m, namely cijOtherwise, node j has no interaction with node m, i.e. cij＝0。
In an embodiment of the present invention, the information interaction specifically includes:
firstly, M nodes of the Internet of things are set in the Internet of things, and a 0-1 variable c is adoptedmjRepresenting the interaction state of the node m and the node j; setting node m as detection and recording interaction messageC if node j is within the interaction threshold (e.g., 2 meters) of node mij1 is ═ 1; in each information interaction process of the nodes, the first information of the storage sequence is as follows: interaction start time
Figure GDA0002339007500000141
End time of interaction
Figure GDA0002339007500000142
Interaction distance dmjAnd the node number j with which it interacts.
For any Internet of things node M, the storage sequence is a 4-dimension M column vector Sm,Em,Dm,NmWherein S ismStoring a vector for the interaction start time of the Internet of things node m, EmStoring a vector, D, for the interaction end time of the Internet of things node mmStoring a vector, N, for the interaction distance of the node m of the Internet of thingsmNumbering nodes interacting with nodes m of the Internet of things;
secondly, for any internet of things node m, when information transmission is started, a sequence, namely four column vectors S, is storedm,Em,Dm,NmInitializing, specifically: setting the ith position in each column vector of the node m of the Internet of things as
Figure GDA0002339007500000143
And
Figure GDA0002339007500000144
the remaining positions are all 0; namely:
Figure GDA0002339007500000145
Figure GDA0002339007500000146
Figure GDA0002339007500000151
Figure GDA0002339007500000152
wherein,
Figure GDA0002339007500000153
representing a vector
Figure GDA0002339007500000154
Data of the ith position of (a);
and finally, obtaining the global column vector average value of each internet node by adopting an average consistency algorithm.
Specifically, the iterative formula of the average consensus algorithm for any node m is:
Figure GDA0002339007500000155
wherein,
Figure GDA0002339007500000156
representing the vector S in the k-th iterationm、Em、DmOr Nm，JmA set of neighbor nodes representing a node m,mrstep size for information iteration for node m and node r.
Then, selecting the information iteration step lengthmrTo make
Figure GDA0002339007500000157
Convergence to the average value of the initial values of all nodes
Figure GDA0002339007500000158
Namely, it is
Figure GDA0002339007500000159
Figure GDA00023390075000001510
The average value
Figure GDA00023390075000001511
Namely, the mutual information of all nodes of the whole internet of things network is contained.
Then the average value
Figure GDA00023390075000001512
Specifically, the average value of the four column vectors to the number of all nodes of the internet of things is a global average vector:
Figure GDA00023390075000001513
Figure GDA00023390075000001514
Figure GDA00023390075000001515
Figure GDA00023390075000001516
wherein j ismIndicating the node number interacting with node m. For nodemIf, if
Figure GDA00023390075000001517
The mth position in the four column vectors is 0, i.e. there is no node interaction information.
As can be seen from the above-mentioned formula,
Figure GDA00023390075000001518
the four column vectors contain the mutual information of all nodes, so that the mutual information of the nodes of the whole network in transmission is obtained as long as the average value of the column vectors is obtained in one transmission time slice.
In an embodiment of the present invention, the selecting an information iteration step size specifically includes:
firstly, determining a network topology structure of an Internet of things to which an Internet of things node belongs;
secondly, for the condition that the topological structure of the internet of things network is unchanged and known, selecting an information iteration step length according to the following steps:
the iteration step is set to a constant value for the fastest convergence rate, determined by the topology information of the network, i.e. the maximum convergence rate is achievedmr＝＝2/{λ2(L)+λM(L)]. Wherein λ isiAnd (L) represents the ith eigenvalue after the eigenvalues of the laplacian matrix L of the internet of things network graph are sorted in an ascending order.
The convergence of the average consensus algorithm in this case can be measured by eigenvalues of the laplacian matrix representing the network topology.
For the condition that the topological structure of the network of the Internet of things is dynamically changed and each node does not know the topological structure of the whole network, the network nodes cannot obtain the global topological information and the step length of the communication networkmrAccording to local connection information of the node, i.e.
Figure GDA0002339007500000161
Wherein n ismRepresenting the degree of node m. In this case, the information iteration step set by each node is only related to local connectivity. And the operation unit is adopted to complete the correlation algorithm. The arithmetic unit is realized by an 8051-based singlechip or a Digital Signal Processor (DSP); the arithmetic unit mainly comprises multiplication and addition operations. The operation unit is required to be connected with the ARM main control module and the storage module at the same time and is used for receiving the node information of the adjacent Internet of things
Figure GDA0002339007500000162
And transmitting the updated node information
Figure GDA0002339007500000163
The invention is divided intoUnder the distributed information transmission mode, each node of the internet of things can acquire global information (network node interaction information records) by all nodes only by communicating with directly adjacent nodes. In the working mode, the global information can be acquired only by information interaction of adjacent nodes and limited iteration.
According to the technical scheme, the non-invasive data acquisition mode is adopted, sample data can be acquired under natural conditions, social interaction behavior data distortion caused by subjective factors can be effectively eliminated, and the accuracy of data acquisition is greatly improved; the problems of reliability, effectiveness, privacy protection and possible system obstacles of data collection in the field of social science are solved. Meanwhile, the invention can solve the research problem in the social science field through repeatability experiments and quantitative analysis. Finally, the hardware system can be reused, and compared with the traditional social science data collection method, the method has the advantages of low consumption of manpower, material resources and financial resources, and greatly reduced social interaction data collection cost. The Internet of things node adopts a conflict avoidance mechanism, has the characteristic of not interfering the normal activity of a sample, can effectively control the distortion of social interaction behavior data under the unnatural condition by the data acquisition platform, improves the accuracy of social interaction experiments related to social behaviors, can be set individually, has the convenience of acquiring the experimental data, and technically solves the problems of reliability, effectiveness, authenticity, privacy, dimension singleness and the like of data collection in the current social science field.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims (4)

1. A social interaction relation data acquisition method in a duplex mode is characterized by comprising the following steps:
s1, each Internet of things node periodically transmits a first signal to the surroundings, Internet of things nodes which can receive the first signal mutually are adjacent to each other, and in the adjacent Internet of things nodes, each Internet of things node records and stores the serial number of the Internet of things node adjacent to the node;
for any two internet of things nodes in the adjacent internet of things nodes, when one of the internet of things nodes receives the first signal transmitted by the other internet of things node again, the two internet of things nodes transmit a second signal at the same time, and the second signal is used for calculating the distance between the two internet of things nodes;
when the distance between any two nodes of the Internet of things is not greater than a set interaction threshold value, judging that the two nodes of the Internet of things are interacting, otherwise, judging that the two nodes of the Internet of things are not interacting;
when two Internet of things nodes are judged to interact, each Internet of things node records and stores the number of the node, the number of the Internet of things node interacting with the node, the distance between the Internet of things nodes interacting with the node, and the interaction starting time and the interaction ending time between the Internet of things nodes interacting with the node;
s2, the Internet of things node coordinator periodically sends a query instruction to each Internet of things node to query all the Internet of things nodes in a circulating mode, after the Internet of things nodes receive the query instruction, each Internet of things node uploads data to the Internet of things node coordinator, the Internet of things node coordinator uploads the data uploaded by the Internet of things nodes to the integrated controller, and the data uploaded by each Internet of things node to the Internet of things node coordinator comprises the number of the Internet of things node, the number of the Internet of things node interacting with the Internet of things node, the distance between the Internet of things nodes interacting with the Internet of things node, and the interaction starting time and the interaction ending time between the Internet of things nodes interacting with the Internet of things node;
in S2, after the Internet of things node coordinators periodically send query instructions to each Internet of things node, the Internet of things nodes upload data to the Internet of things node coordinators in sequence in a preset interaction period according to the sequence of respective numbers; when one Internet of things node does not upload data in the interaction period, the next Internet of things node starts to upload data to the Internet of things node coordinator;
when the nodes of the Internet of things do not upload data in the interaction period, judging whether the nodes of the Internet of things and the nodes of the Internet of things coordinator have communication faults or not, if so, acquiring data by all the nodes of the Internet of things according to a distributed information transmission mode; otherwise, the Internet of things node coordinator transmits the received data of the Internet of things nodes to the integrated controller;
the process that all nodes of the Internet of things acquire data according to the distributed information transmission mode comprises the following steps:
firstly, each Internet of things node carries out S1, and recorded and stored data are placed at the tail of each storage sequence;
then, each Internet of things node in the mutually adjacent Internet of things nodes sends the head information of the respective storage sequence to the adjacent Internet of things node, receives the head information sent by the adjacent Internet of things node, and stores the received head information to the tail of the respective storage sequence; repeatedly carrying out information interaction on each Internet of things node and adjacent Internet of things nodes until the interaction information of all the Internet of things nodes is stored in the storage sequence of each Internet of things node;
the first information is the earliest interactive information in the information which is not transmitted in the storage sequence of the nodes of the Internet of things;
after the mutual information of all the internet of things nodes is stored in the storage sequence of each internet of things node, all the internet of things nodes are collected and form a communication network, and the whole social interaction relationship information is obtained by adopting a distributed information transmission mode; the distributed information transmission mode for obtaining the information of the whole social interaction relationship comprises the following steps:
1) initializing a transmission data vector of each Internet of things node;
2) each Internet of things node transmits data vectors with adjacent Internet of things nodes capable of communicating, and the data vectors are updated according to an average consistency algorithm; after iteration is carried out for preset times according to the average consistency algorithm, the data vector updated by the current internet of things node is the social interaction relationship information of the whole internet of things;
in the step 2), an iterative formula of an average consensus algorithm for any internet of things node m is as follows:
Figure FDA0002674035450000021
wherein,
Figure FDA0002674035450000022
representing the vector S in the k-th iterationm、Em、DmOr Nm，JmA set of neighboring internet of things nodes representing node m,mrthe information iteration step length of the node m and the node r of the Internet of things is obtained;
selecting information iteration step length when updating data vectormrAnd setting the number of iterations, and using the iteration formula of the average consensus algorithm to enable
Figure FDA0002674035450000023
Convergence to the initial average of all nodes
Figure FDA0002674035450000024
Updating of the data vector is realized;
the average value of the initial value
Figure FDA0002674035450000031
The mutual information of all nodes of the whole internet of things network is averaged by the initial value
Figure FDA0002674035450000032
As social interaction relationship information of the whole Internet of things;
wherein, the information iteration step length is selectedmrThe process comprises the following steps:
determining a network topology structure of the Internet of things where all the nodes of the Internet of things form;
for the condition that the topological structure of the network of the Internet of things is unchanged and known, the information iteration step length is selected according to the following processmr: setting information stacksThe generation step size is a fixed value,mr＝＝2/[λ2(L)+λM(L)](ii) a Wherein λ isi(L) represents the ith (i belongs to {1, 2.. multidot.M }) eigenvalue after the eigenvalues of the Laplace matrix L of the network diagram of the Internet of things are arranged in an ascending order;
for the condition that the topological structure of the network of the Internet of things is dynamically changed and each node of the Internet of things does not know the topological structure of the whole network, the information iteration step lengthmrComprises the following steps:
Figure FDA0002674035450000033
wherein n ismAnd representing the degree of the node m of the Internet of things.
2. The method for collecting social interaction relationship data in a duplex mode according to claim 1, wherein the step of determining whether the communication failure occurs between the internet of things node and the internet of things node coordinator comprises the steps of:
(a) calculating the fault proportion of the nodes of the Internet of things;
(b) judging the size of the fault proportion obtained in the step (a) and a set fault threshold, if the fault proportion is not less than the fault threshold, judging that communication fault occurs, otherwise, judging that the communication is normal;
the fault proportion is the proportion of the number of the nodes of the internet of things with communication faults in the total number of the nodes of the internet of things.
3. The duplex-mode social interaction relationship data acquisition method according to claim 1, wherein in the step 1), initializing a transmission data vector of each internet of things node comprises:
in M nodes of the Internet of things, for any node M of the Internet of things, a column vector S with 4 storage sequences and M dimensions is providedm、Em、DmAnd Nm；
Wherein S ismStoring a vector for the interaction start time of the internet of things node m,Emstoring a vector, D, for the interaction end time of the Internet of things node mmStoring a vector, N, for the interaction distance of the node m of the Internet of thingsmThe number of the Internet of things node interacting with the Internet of things node m is numbered;
four column vectors S to node m of the Internet of thingsm,Em,DmAnd NmThe process of performing initialization includes: setting the ith position in each column vector of the node m of the Internet of things as
Figure FDA0002674035450000041
And
Figure FDA0002674035450000042
the remaining positions are all 0; wherein,
Figure FDA0002674035450000043
Figure FDA0002674035450000044
Figure FDA0002674035450000045
Figure FDA0002674035450000046
wherein,
Figure FDA0002674035450000047
representing a vector
Figure FDA0002674035450000048
Data of the ith position of (a);
Figure FDA0002674035450000049
in order to be the start time of the interaction,
Figure FDA00026740354500000410
as interaction end time, dmjAnd j is the number of the internet of things node interacting with the internet of things node.
4. The method as claimed in claim 1, wherein the average value of the initial values is the average value of the social interaction relationship data
Figure FDA00026740354500000411
Specifically, the average value of the number of the four column vectors to all the nodes of the internet of things is
Figure FDA00026740354500000412
And
Figure FDA00026740354500000413
and
Figure FDA00026740354500000414
respectively as follows:
Figure FDA00026740354500000415
Figure FDA00026740354500000416
Figure FDA00026740354500000417
Figure FDA0002674035450000051
wherein j ismAnd the number of the Internet of things node interacting with the Internet of things node m is represented.
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