CN114040352A - Information acquisition method, system and device based on big data - Google Patents
Information acquisition method, system and device based on big data Download PDFInfo
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- CN114040352A CN114040352A CN202111362989.7A CN202111362989A CN114040352A CN 114040352 A CN114040352 A CN 114040352A CN 202111362989 A CN202111362989 A CN 202111362989A CN 114040352 A CN114040352 A CN 114040352A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/08—Testing, supervising or monitoring using real traffic
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
- H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention relates to the technical field of communication, and discloses an information acquisition method, system and device based on big data. The method, the system and the device of the invention receive the information collected by each sink node, store the received information to form a big data platform based on the information, calculate the flow data of the information sent by each sink node in a set period, and send early warning information to a preset intelligent mobile terminal when the flow data exceeds a preset flow threshold. The embodiment of the invention utilizes a big data technology, can realize high-efficiency and timely acquisition of information, and realizes timely early warning through analysis of information flow data.
Description
Technical Field
The invention relates to the technical field of information acquisition, in particular to an information acquisition method, system and device based on big data.
Background
In the prior art, when information is acquired, people are generally dispatched to each monitoring area to carry out monitoring, and the acquired information is input into a related system.
Disclosure of Invention
The invention provides an information acquisition method, system and device based on big data, which are used for solving the technical problems that the existing information acquisition mode is low in efficiency and cannot realize timely and efficient information acquisition.
The invention provides an information acquisition method based on big data in a first aspect, which comprises the following steps:
receiving information sent by each aggregation node; the sink node is used for collecting information collected by each sensor node in the responsible area;
storing the received information, and calculating the flow data of the information sent by each sink node in a set period;
and when the flow data exceeds a preset flow threshold, sending early warning information to the corresponding mobile terminal according to a preset mobile terminal list.
According to a possible implementation manner of the first aspect of the present invention, the storing the received information includes:
and carrying out partition storage according to the identification information of the corresponding sink node.
According to an enabling aspect of the first aspect of the invention, the method further comprises:
receiving login account information sent by a first terminal;
matching the login account information with login account information stored in advance;
and if the matching is successful, adding the corresponding identification information of the first terminal into the mobile terminal list.
According to an enabling aspect of the first aspect of the invention, the method further comprises:
receiving an access request of a second terminal, wherein the access request comprises identification information of the second terminal;
matching the identification information of the second terminal with the identification information in the mobile terminal list;
if the matching is successful, providing an operation interface for data query to the second terminal;
and responding to the operation of the second terminal based on the operation interface.
The second aspect of the present invention provides an information collecting apparatus based on big data, the apparatus comprising:
the first receiving module is used for receiving information sent by each aggregation node; the sink node is used for collecting information collected by each sensor node in the responsible area;
the storage module is used for storing the received information and calculating the flow data of the information sent by each sink node in a set period;
and the early warning module is used for sending early warning information to the corresponding mobile terminal according to a preset mobile terminal list when the flow data exceeds a preset flow threshold value.
According to an implementable manner of the second aspect of the present invention, the storage module is specifically configured to:
and carrying out partition storage according to the identification information of the corresponding sink node.
According to an implementable manner of the second aspect of the invention, the apparatus further comprises:
the second receiving module is used for receiving the login account information sent by the first terminal;
the first matching module is used for matching the login account information with the login account information stored in advance;
and the terminal adding module is used for adding the corresponding identification information of the first terminal into the mobile terminal list if the matching is successful.
According to an implementable manner of the second aspect of the invention, the apparatus further comprises:
a third receiving module, configured to receive an access request of a second terminal, where the access request includes identification information of the second terminal;
the second matching module is used for matching the identification information of the second terminal with the identification information in the mobile terminal list;
the interface providing module is used for providing an operation interface for data query to the second terminal if the matching is successful;
and the response module is used for responding to the operation of the second terminal based on the operation interface.
The third aspect of the present invention provides an information collecting apparatus based on big data, including:
a memory to store instructions; the instruction is an instruction which can implement the steps of the big data-based information acquisition method according to any one of the above embodiments;
a processor to execute the instructions in the memory.
A fourth aspect of the present invention provides a computer-readable storage medium, which stores thereon a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the big-data-based information collecting method according to any one of the above embodiments.
According to the technical scheme, the invention has the following advantages:
the embodiment of the invention receives the information collected by each sink node, stores the received information to form a big data platform based on the information, calculates the flow data of the information sent by each sink node in a set period, and sends early warning information to a preset intelligent mobile terminal when the flow data exceeds a preset flow threshold; the embodiment of the invention utilizes a big data technology, can realize high-efficiency and timely acquisition of information, and realizes timely early warning through analysis of information flow data.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a flowchart of an information collecting method based on big data according to an alternative embodiment of the present invention;
fig. 2 is a schematic structural connection diagram of an information acquisition system based on big data according to an alternative embodiment of the present invention.
Description of the drawings:
1-a first receiving module; 2-a storage module; and 3, an early warning module.
Detailed Description
The embodiment of the invention provides an information acquisition method, system and device based on big data, which are used for solving the technical problems that the existing information acquisition mode is low in efficiency and cannot realize timely and efficient information acquisition.
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It is noted that relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Referring to fig. 1, fig. 1 is a flowchart illustrating an information collecting method based on big data according to an embodiment of the present invention.
The invention discloses an information acquisition method based on big data, which comprises the following steps:
s1, receiving information sent by each aggregation node; the sink node is used for collecting information collected by each sensor node in the area in charge.
The information acquisition of the embodiment of the invention is realized by a wireless sensor network mode and is managed based on a big data technology.
Each sensor node has a corresponding communication capacity value according to initial setting, namely, the communication distance is larger than a certain value, so that the sensor nodes can at least keep communication with the sink node or one sensor node.
Initially, when the communication distance of a sensor node is greater than the distance between the sensor node and a sink node, the sensor node directly communicates with the sink node; otherwise, the sensor node selects one sensor node in the communication range as a next hop node;
every time a preset period is reached, the sensor node calculates the communication capacity value of the sensor node according to the following formula, and if the communication capacity value is smaller than a preset communication capacity value threshold value, the sensor node reselects a next hop node:
in the formula (I), the compound is shown in the specification,
representing sensor nodes
The value of the communication capability of (c),
in order to preset the influence coefficient,
the value range is set as
，
Representing sensor nodes
The initial energy of the energy of,
representing sensor nodes
The current remaining energy of the energy storage device,
representing sensor nodes
The communication distance of (a) is set,
representing the minimum of the distances of each sensor node from the sink node.
According to the embodiment of the invention, the sensor node judges whether the next hop node needs to be reselected or not according to the communication capacity value by setting the reference index of the communication capacity value. The energy consumption of the sensor nodes is considered in the calculation of the communication capacity value, and by the method, the reliability of sending the information collected by the sensor nodes to the next hop nodes can be improved, and the energy consumption rate of the sensor nodes is reduced.
The sensor nodes are provided with corresponding processing units for calculation, judgment, selection and other operations.
In one implementation, the selecting, by the sensor node, one sensor node as a next-hop node in a communication range of the sensor node includes:
the sensor nodes take the sensor nodes with the distance smaller than the communication distance as candidate nodes, and calculate the association degree with each candidate node:
in the formula (I), the compound is shown in the specification,
representing sensor nodes and their candidate nodes
The degree of association of (c);
indicating both belonging to sensor nodes
Communication range and belonging to candidate node
The number of sensor nodes of the communication range,
to belong to sensor nodes
The number of sensor nodes in the communication range belongs to the sensor nodes
The number of sensor nodes within communication range,
as sensor nodes
The distance from its candidate node(s),
representing sensor nodes
The maximum value of the distance from each candidate node is the first influence coefficient,
is a second influence coefficient, and
；
and the sensor node selects the sensor node with the minimum relevance degree from all the candidate nodes as a next hop node.
According to the embodiment of the invention, the sensor node which is not associated with the sensor node is selected as the next hop node, so that the data conflict is reduced, and the efficiency of sending information to the sink node is improved.
In one implementation, the method for reselecting a next-hop node by a sensor node includes:
the sensor node will be less than its distance
The sensor node of (2) is used as a candidate node;
the sensor node sends a request to each alternative node and receives the current communication capacity value fed back by each alternative node;
the sensor node calculates the communication fault probability of each alternative node according to the following formula:
in the formula (I), the compound is shown in the specification,
representing alternative nodes
The probability of a communication failure of (2),
representing alternative nodes
The value of the communication capability of (c),
represents the preset communication capability value threshold value,
to determine the value function, when
When the temperature of the water is higher than the set temperature,
when is coming into contact with
When the temperature of the water is higher than the set temperature,
，
representing the sensor node to the candidate node
The distance of (a) to (b),
represents the maximum of the distances from the sensor node to each candidate node,
for the fault influence coefficient based on the communication capability value,
for the distance-based fault impact coefficient,
；
and the sensor node selects the node with the smallest communication fault probability from the candidate nodes as a next hop node.
The embodiment of the invention self-defines the reference index of the communication fault probability. By reselecting the next hop node in the above manner, the reliability of communication between the sensor node and the selected next hop node can be effectively guaranteed, and the stability of information acquisition is guaranteed.
S2 stores the received information and calculates the flow data of the information sent by each aggregation node in a set period.
The embodiment of the invention calculates the flow data of the information by taking a set period as a time unit. The specific value of the set period may be set by a user according to actual conditions, for example, 5 minutes is used as one period, timing is started when the information of the sink node is received, and the traffic of the information of the sink node received within 5 minutes is calculated as traffic data of the information sent by the period.
In one implementation, the storing the received information includes:
and carrying out partition storage according to the identification information of the corresponding sink node.
The partition design can facilitate information use and query, fully mobilize the acquired information and accelerate data retrieval and processing.
And S3, when the flow data exceeds the preset flow threshold, sending early warning information to the corresponding mobile terminal according to the preset mobile terminal list.
The early warning information comprises a sink node identifier and a specific value of corresponding flow data.
The mobile terminal can be one of a computer, a mobile phone, an IPad, a server, a wearable device and the like. In some embodiments, the wearable device may include a smart bracelet, a smart helmet, a smart watch, a smart accessory, or any combination thereof.
In one implementation, the method further comprises:
receiving login account information sent by a first terminal;
matching the login account information with login account information stored in advance;
and if the matching is successful, adding the corresponding identification information of the first terminal into the mobile terminal list.
The embodiment of the invention adds the mobile terminal in a login account information verification mode, and the added mobile terminal can receive the early warning information when the information flow data of the sink node is abnormal.
In one implementation, the method further comprises:
receiving an access request of a second terminal, wherein the access request comprises identification information of the second terminal;
matching the identification information of the second terminal with the identification information in the mobile terminal list;
if the matching is successful, providing an operation interface for data query to the second terminal;
and responding to the operation of the second terminal based on the operation interface.
The embodiment of the invention realizes the query operation of the stored information and can facilitate the information management personnel to query the stored information through the mobile terminal.
Fig. 2 is a schematic structural connection diagram of an information acquisition device based on big data according to an embodiment of the present invention.
As shown in fig. 2, the apparatus includes:
the first receiving module 1 is used for receiving information sent by each aggregation node; the sink node is used for collecting information collected by each sensor node in the responsible area;
the storage module 2 is used for storing the received information and calculating the flow data of the information sent by each sink node in a set period;
and the early warning module 3 is used for sending early warning information to the corresponding mobile terminal according to a preset mobile terminal list when the flow data exceeds a preset flow threshold.
Each sensor node has a corresponding communication capacity value according to initial setting, namely, the communication distance is larger than a certain value, so that the sensor nodes can at least keep communication with the sink node or one sensor node.
The sensor node comprises a processing module, and the processing module is specifically configured to:
initially, when the communication distance of the sensor node is greater than the distance between the sensor node and the sink node, the sensor node directly communicates with the sink node; otherwise, one sensor node is selected as the next hop node in the communication range.
The processing module comprises:
the first calculating unit is used for calculating the communication capacity value per preset period according to the following formula:
in the formula (I), the compound is shown in the specification,
representing sensor nodes
The value of the communication capability of (c),
for presetting the influence coefficient, the value range is set to
，
Representing sensor nodes
The initial energy of the energy of,
representing sensor nodes
The current remaining energy of the energy storage device,
representing sensor nodes
The communication distance of (a) is set,
representing the minimum value in the distances between each sensor node and the aggregation node;
and the first communication selection unit is used for reselecting the next hop node for communication if the communication capacity value is smaller than the preset communication capacity value threshold.
In an implementation manner, the selecting a sensor node within a communication range thereof as a next hop node specifically includes:
taking the sensor nodes with the distance smaller than the communication distance as candidate nodes, and calculating the association degree of each candidate node:
in the formula (I), the compound is shown in the specification,
representing sensor nodes and their candidate nodes
The degree of association of (c);
indicating both belonging to sensor nodes
Communication range and belonging to candidate node
The number of sensor nodes of the communication range,
to belong to sensor nodes
The number of sensor nodes within communication range,
belonging to sensor node
The number of sensor nodes within communication range,
is a sensor node and a candidate node thereof
The distance of (a) to (b),
representing sensor nodes
The maximum value of the distance from each candidate node,
as a first influence coefficient, is selected,
is a second influence coefficient, and
；
and selecting the sensor node with the minimum relevance degree from the candidate nodes as a next hop node.
In an implementation manner, the first communication selecting unit is specifically configured to:
will be at a distance less than
As an alternative to the sensor nodeA node;
sending a request to each alternative node, and receiving the current communication capacity value fed back by each alternative node;
and calculating the communication fault probability of each alternative node according to the following formula:
in the formula (I), the compound is shown in the specification,
representing alternative nodes
The probability of a communication failure of (2),
representing alternative nodes
The value of the communication capability of (c),
represents the preset communication capability value threshold value,
to determine the value function, when
When the temperature of the water is higher than the set temperature,
when is coming into contact with
When the temperature of the water is higher than the set temperature,
，
representing the sensor node to the candidate node
The distance of (a) to (b),
represents the maximum of the distances from the sensor node to each candidate node,
for the fault influence coefficient based on the communication capability value,
for the distance-based fault impact coefficient,
；
and selecting the node with the smallest communication fault probability from the candidate nodes as a next hop node.
According to an implementation manner of the embodiment of the present invention, the storage module is specifically configured to:
and carrying out partition storage according to the identification information of the corresponding sink node.
According to an implementable manner of the embodiment of the present invention, the apparatus further includes:
the second receiving module is used for receiving the login account information sent by the first terminal;
the first matching module is used for matching the login account information with the login account information stored in advance;
and the terminal adding module is used for adding the corresponding identification information of the first terminal into the mobile terminal list if the matching is successful.
According to an implementable manner of the embodiment of the present invention, the apparatus further includes:
a third receiving module, configured to receive an access request of a second terminal, where the access request includes identification information of the second terminal;
the second matching module is used for matching the identification information of the second terminal with the identification information in the mobile terminal list;
the interface providing module is used for providing an operation interface for data query to the second terminal if the matching is successful;
and the response module is used for responding to the operation of the second terminal based on the operation interface.
The invention also provides an information acquisition device based on big data, which comprises:
a memory to store instructions; the instruction is an instruction which can implement the steps of the big data-based information acquisition method according to any one of the above embodiments;
a processor to execute the instructions in the memory.
The present invention further provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the big data based information collecting method according to any one of the above embodiments.
In the embodiment of the invention, the information collected by each sink node is received, the received information is stored to form a big data platform based on the information, the flow data of the information sent by each sink node in a set period is calculated, and when the flow data exceeds a preset flow threshold value, early warning information is sent to a preset intelligent mobile terminal; the embodiment of the invention utilizes a big data technology, can realize high-efficiency and timely acquisition of information, and realizes timely early warning through analysis of information flow data.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. An information acquisition method based on big data, which is characterized by comprising the following steps:
receiving information sent by each aggregation node; the sink node is used for collecting information collected by each sensor node in the responsible area;
storing the received information, and calculating the flow data of the information sent by each sink node in a set period;
and when the flow data exceeds a preset flow threshold, sending early warning information to the corresponding mobile terminal according to a preset mobile terminal list.
2. The big data-based information collection method according to claim 1, wherein the storing the received information comprises:
and carrying out partition storage according to the identification information of the corresponding sink node.
3. The big data based information gathering method as recited in claim 1, further comprising:
receiving login account information sent by a first terminal;
matching the login account information with login account information stored in advance;
and if the matching is successful, adding the corresponding identification information of the first terminal into the mobile terminal list.
4. The big data based information gathering method as recited in claim 3, further comprising:
receiving an access request of a second terminal, wherein the access request comprises identification information of the second terminal;
matching the identification information of the second terminal with the identification information in the mobile terminal list;
if the matching is successful, providing an operation interface for data query to the second terminal;
and responding to the operation of the second terminal based on the operation interface.
5. An information acquisition device based on big data, the device comprising:
the first receiving module is used for receiving information sent by each aggregation node; the sink node is used for collecting information collected by each sensor node in the responsible area;
the storage module is used for storing the received information and calculating the flow data of the information sent by each sink node in a set period;
and the early warning module is used for sending early warning information to the corresponding mobile terminal according to a preset mobile terminal list when the flow data exceeds a preset flow threshold value.
6. The big-data-based information acquisition device according to claim 5, wherein the storage module is specifically configured to:
and carrying out partition storage according to the identification information of the corresponding sink node.
7. The big data based information gathering device as recited in claim 5, wherein the device further comprises:
the second receiving module is used for receiving the login account information sent by the first terminal;
the first matching module is used for matching the login account information with the login account information stored in advance;
and the terminal adding module is used for adding the corresponding identification information of the first terminal into the mobile terminal list if the matching is successful.
8. The big data based information gathering device as recited in claim 7, wherein the device further comprises:
a third receiving module, configured to receive an access request of a second terminal, where the access request includes identification information of the second terminal;
the second matching module is used for matching the identification information of the second terminal with the identification information in the mobile terminal list;
the interface providing module is used for providing an operation interface for data query to the second terminal if the matching is successful;
and the response module is used for responding to the operation of the second terminal based on the operation interface.
9. An information acquisition device based on big data, comprising:
a memory to store instructions; the instruction is an instruction which can realize the steps of the big data-based information acquisition method according to any one of claims 1 to 4;
a processor to execute the instructions in the memory.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program, which when executed by a processor implements the steps of the big data based information collecting method according to any of claims 1-4.
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