CN117956540B - Indoor environment monitoring method, device, equipment and storage medium - Google Patents
Indoor environment monitoring method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN117956540B CN117956540B CN202410354012.8A CN202410354012A CN117956540B CN 117956540 B CN117956540 B CN 117956540B CN 202410354012 A CN202410354012 A CN 202410354012A CN 117956540 B CN117956540 B CN 117956540B
- Authority
- CN
- China
- Prior art keywords
- grids
- class
- monitoring data
- nodes
- wireless sensor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 160
- 238000000034 method Methods 0.000 title claims abstract description 29
- 241000854291 Dianthus carthusianorum Species 0.000 claims abstract description 66
- 238000013461 design Methods 0.000 claims abstract description 20
- 238000010586 diagram Methods 0.000 claims abstract description 13
- 238000012806 monitoring device Methods 0.000 claims abstract description 6
- 238000004364 calculation method Methods 0.000 claims description 15
- 238000004891 communication Methods 0.000 claims description 10
- 230000007613 environmental effect Effects 0.000 claims description 8
- 230000005856 abnormality Effects 0.000 description 6
- 238000005457 optimization Methods 0.000 description 6
- 230000002159 abnormal effect Effects 0.000 description 4
- 230000003044 adaptive effect Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
- H04W40/32—Connectivity information management, e.g. connectivity discovery or connectivity update for defining a routing cluster membership
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/18—Network planning tools
- H04W16/20—Network planning tools for indoor coverage or short range network deployment
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Arrangements For Transmission Of Measured Signals (AREA)
Abstract
The invention belongs to the field of environment monitoring, and discloses an indoor environment monitoring method, an indoor environment monitoring device and a storage medium, wherein the method comprises the following steps of S1, obtaining a plane design diagram of an indoor space needing environment monitoring; s2, dividing the plane design diagram into a plurality of grids with the same size; s3, acquiring a first wireless sensor network; s4, receiving monitoring data which are sent by a first wireless sensor network and are acquired by member nodes in a preset time interval; s5, counting the total amount of monitoring data obtained by member nodes in each class of grids in a preset time interval; s6, the base acquires a class II grid; s7, acquiring a second wireless sensor network based on the class II grids; and S8, receiving monitoring data which are sent by the second wireless sensor network and are acquired by the member node. The invention effectively reduces the occurrence probability of the event that the single cluster head node loses the capability of data acquisition and forwarding in advance.
Description
Technical Field
The present invention relates to the field of environmental monitoring, and in particular, to a method, an apparatus, a device, and a storage medium for indoor environmental monitoring.
Background
Indoor environment monitoring refers to the acquisition of temperature, humidity and other data at different indoor positions by utilizing wireless sensor nodes, so that the indoor abnormal environment can be timely found.
In the prior art, when the wireless sensor node is adopted to monitor the indoor environment, the indoor area to be monitored is generally divided into a plurality of grids with the same size, and then cluster head nodes are selected in each grid, so that the wireless sensor node is clustered, and the problem of nonuniform cluster head distribution caused by the traditional leach algorithm can be effectively solved.
However, the clustering method does not consider the data amount in different grids, because the sampling frequencies of the wireless sensor nodes at different indoor positions are not completely the same, and thus the data amount in different grids is not the same in one clustering operation period, so that the cluster head nodes in grids with larger data amount may lose the capability of acquiring and forwarding data in advance due to too high power consumption speed, and a blind area for indoor environment monitoring occurs prematurely.
Disclosure of Invention
The invention aims to disclose an indoor environment monitoring method, an indoor environment monitoring device and a storage medium, and solves the problem of how to effectively avoid the occurrence of a blind area of indoor environment monitoring when indoor environment monitoring is carried out by adopting a wireless sensor node.
In order to achieve the above purpose, the present invention provides the following technical solutions:
In a first aspect, the present invention provides an indoor environment monitoring method, including:
s1, acquiring a plane design diagram of an indoor space needing environment monitoring;
s2, dividing the plane design diagram into a plurality of grids with the same size;
S3, selecting cluster head nodes and member nodes for each type of grids, wherein the member nodes are configured to send acquired monitoring data to the cluster head nodes, and the cluster head nodes are configured to send the acquired monitoring data to a wireless gateway so as to obtain a first wireless sensor network;
S4, receiving monitoring data which are sent by a first wireless sensor network and are acquired by member nodes in a preset time interval;
s5, counting the total amount of monitoring data obtained by member nodes in each class of grids in a preset time interval;
S6, dividing a class of grids based on the total amount of monitoring data obtained by each member node to obtain a class II grid;
S7, selecting cluster head nodes and member nodes for each class II grid, wherein the member nodes are configured to send acquired monitoring data to the cluster head nodes, and the cluster head nodes are configured to send the acquired monitoring data to the wireless gateway so as to obtain a second wireless sensor network;
s8, receiving monitoring data obtained by the member node and sent by the second wireless sensor network;
Wherein S6 includes:
Calculating the average value of the total amount of the monitoring data obtained by the member nodes in all the types of grids in a preset time interval ；
For the class of grids b, the total amount of monitoring data obtained by member nodes in the class of grids b in a preset time interval is expressed as；
If it isDividing b into a plurality of class-two grids,/>, andRepresenting a preset judgment coefficient; otherwise, b is directly used as the class II grid.
Preferably, S2 comprises:
s21, obtaining a minimum circumscribed rectangle A of a plane design drawing;
S22, dividing the length and the width of the minimum circumscribed rectangle A into L1 and L2, and calculating the number of the first type of grids as follows:
N represents the number of the class of grids, and R represents the communication radius of the member node;
S23, judging If it is 0, if it is not, the length of A is extended/>If yes, the length of the A is not changed; judgment/>If it is 0, if it is not, the width of A is extended/>If yes, the length of the B is not changed;
S24, dividing the rectangle obtained in the S23 into N grids with the same size, wherein each grid is square with the side length of 2R.
Preferably, selecting a cluster head node and a member node for each class of grids includes:
Respectively calculating a clustering judgment value of each wireless sensor node in each class of grids;
and respectively taking the wireless sensor node with the largest clustering judgment value in each class of grids as a cluster head node, and taking the rest wireless sensor nodes as member nodes.
Preferably, the calculation formula of the clustering judgment value is:
clustering judgment value representing wireless sensor node k,/> Representing the current charge of k,/>Representing the maximum charge of k,/>Represents the number of wireless sensor nodes having a communication radius with k that is less than k,Representing a preset quantity comparison value; /(I)Representing the reference weight of the electric quantity,/>Representing the quantitative reference weights.
Preferably, sending the acquired monitoring data to the cluster head node includes:
and the member node sends the acquired monitoring data to a cluster head node of the cluster where the member node is located.
Preferably, S5 comprises:
In the class of grids, the calculation formula of the total amount of monitoring data obtained by member nodes is as follows:
Representing the total amount of monitoring data obtained by member nodes in a class of grids,/> Representing a set of member nodes in a class of grids; /(I)The number of times of receiving monitoring data sent by the member node c in a preset time interval is shown; /(I)Indicating the size of the monitoring data sent from the member node c received the ith time.
Preferably, dividing b into a plurality of class two grids includes:
Calculating the number Z of the class II grids:
representing a preset number;
The length and width of a class of grids are denoted wid and len, respectively;
The length and width of the second class of grids are respectively And/>；
Dividing b into a plurality of sizesIs a second class grid of (c).
In a second aspect, the invention provides an indoor environment monitoring device, which comprises an acquisition module, a first dividing module, a first selecting module, a receiving module, a statistics module, a second dividing module and a second selecting module;
the acquisition module is used for acquiring a plane design diagram of an indoor space needing environment monitoring;
the first dividing module is used for dividing the plane design drawing into a plurality of grids with the same size;
The first selecting module is used for selecting cluster head nodes and member nodes for each type of grids, the member nodes are configured to send acquired monitoring data to the cluster head nodes, and the cluster head nodes are configured to send the acquired monitoring data to the wireless gateway so as to obtain a first wireless sensor network;
The receiving module is used for receiving monitoring data which are sent by the first wireless sensor network and are acquired by the member node in a preset time interval;
the statistics module is used for counting the total amount of monitoring data obtained by member nodes in each class of grids in a preset time interval;
the second dividing module is used for dividing the first class grids based on the total amount of the monitoring data obtained by each member node to obtain second class grids;
the second selecting module is used for selecting cluster head nodes and member nodes for each class II grid, the member nodes are configured to send the acquired monitoring data to the cluster head nodes, and the cluster head nodes are configured to send the acquired monitoring data to the wireless gateway so as to obtain a second wireless sensor network;
the receiving module is also used for receiving monitoring data which are sent by the second wireless sensor network and are acquired by the member node;
Dividing a class-one grid based on the total amount of monitoring data obtained by each member node to obtain a class-two grid, wherein the method comprises the following steps:
Calculating the average value of the total amount of the monitoring data obtained by the member nodes in all the types of grids in a preset time interval ；
For the class of grids b, the total amount of monitoring data obtained by member nodes in the class of grids b in a preset time interval is expressed as；
If it isDividing b into a plurality of class-two grids,/>, andRepresenting a preset judgment coefficient; otherwise, b is directly used as the class II grid.
In a third aspect, the present invention provides an apparatus for indoor environmental monitoring, comprising at least one processor and a memory storing computer executable instructions, the processor implementing the steps of the indoor environmental monitoring method of the first aspect when executing the instructions.
In a fourth aspect, the present invention provides a computer readable storage medium for indoor environment monitoring, comprising a memory for storing processor executable instructions which when executed by the processor implement the steps of the indoor environment monitoring method of the first aspect.
The beneficial effects are that:
Compared with the existing mode of directly dividing a monitored area into a plurality of grids with the same size, and then selecting cluster head nodes and member nodes from the grids, the size of the grids is not the same, but the first wireless sensor network obtained based on the grids with the same time is operated in a preset time interval, and then one type of grids are divided based on the total amount of the monitoring data obtained in each type of grids, so that two types of grids are obtained, and in the subsequent process of monitoring the indoor environment, the second wireless sensor network generated based on the two types of grids can be used for acquiring the monitoring data, in this way, the size of the grids is smaller in the area with larger data amount, so that the consumption speed of the cluster head nodes in the grids with different sizes is as close as possible, the occurrence probability of the event that a single cluster head node loses the capability of acquiring and forwarding data in advance is effectively reduced, and the blind area of monitoring the indoor environment is prevented from happening prematurely in the process of normal operation of the wireless sensor network.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of an indoor environment monitoring method according to the present invention.
Fig. 2 is a schematic diagram of an indoor environment monitoring device according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In one embodiment as shown in fig. 1, the present invention provides an indoor environment monitoring method, including:
s1, acquiring a plane design diagram of an indoor space needing environment monitoring;
s2, dividing the plane design diagram into a plurality of grids with the same size;
S3, selecting cluster head nodes and member nodes for each type of grids, wherein the member nodes are configured to send acquired monitoring data to the cluster head nodes, and the cluster head nodes are configured to send the acquired monitoring data to a wireless gateway so as to obtain a first wireless sensor network;
S4, receiving monitoring data which are sent by a first wireless sensor network and are acquired by member nodes in a preset time interval;
s5, counting the total amount of monitoring data obtained by member nodes in each class of grids in a preset time interval;
S6, dividing a class of grids based on the total amount of monitoring data obtained by each member node to obtain a class II grid;
S7, selecting cluster head nodes and member nodes for each class II grid, wherein the member nodes are configured to send acquired monitoring data to the cluster head nodes, and the cluster head nodes are configured to send the acquired monitoring data to the wireless gateway so as to obtain a second wireless sensor network;
s8, receiving monitoring data obtained by the member node and sent by the second wireless sensor network;
Wherein S6 includes:
Calculating the average value of the total amount of the monitoring data obtained by the member nodes in all the types of grids in a preset time interval ；
For the class of grids b, the total amount of monitoring data obtained by member nodes in the class of grids b in a preset time interval is expressed as；
If it isDividing b into a plurality of class-two grids,/>, andRepresenting a preset judgment coefficient; otherwise, b is directly used as the class II grid.
According to the implementation process, the first wireless sensor networks obtained based on the grids with the same time size are operated in the preset time interval, and then the first type of grids are divided based on the total amount of monitoring data obtained in each type of grids to obtain the second type of grids, so that in the subsequent process of monitoring the indoor environment, the second wireless sensor network generated based on the second type of grids can acquire monitoring data, and therefore the size of the grids is smaller in the area with larger data size, consumption speeds of cluster head nodes in grids with different sizes are as close as possible, the occurrence probability of events that a single cluster head node loses the capability of acquiring and forwarding data in advance is effectively reduced, and the blind area of indoor environment monitoring is avoided in the normal operation process of the wireless sensor network.
Preferably, before S3, the method further includes:
and setting wireless sensor nodes and wireless gateways in indoor spaces needing environment monitoring, and recording coordinates of each wireless sensor node and coordinates of the wireless gateways.
Preferably, the preset time interval is，/>And indicating the moment of obtaining the first wireless sensor network, wherein T indicates the preset time length.
Preferably, T has a value of 1 day.
Preferably, the preset judgment coefficient is 1.3.
Preferably, S2 comprises:
s21, obtaining a minimum circumscribed rectangle A of a plane design drawing;
S22, dividing the length and the width of the minimum circumscribed rectangle A into L1 and L2, and calculating the number of the first type of grids as follows:
N represents the number of the class of grids, and R represents the communication radius of the member node;
S23, judging If it is 0, if it is not, the length of A is extended/>If yes, the length of the A is not changed; judgment/>If it is 0, if it is not, the width of A is extended/>If yes, the length of the B is not changed;
S24, dividing the rectangle obtained in the S23 into N grids with the same size, wherein each grid is square with the side length of 2R.
In the above process, the length of a may not be just an integer multiple of the length of the class of grids, and the width of a may not be just an integer multiple of the width of the class of grids, so the invention uses mod algorithm to make a remainder on the result of dividing L1 by 2R, when the remainder is 0, it means that the length of a does not need to be adjusted, otherwise, by lengthening the length of a, the length of a in the rectangle obtained after the change can be just divided by 2R, and the processing of the width is the same theory, thus, the clustering algorithm of the invention has wider application range, instead of just clustering wireless sensor nodes in the area with the length and the width just being an integer multiple of the class of grids.
Preferably, selecting a cluster head node and a member node for each class of grids includes:
Respectively calculating a clustering judgment value of each wireless sensor node in each class of grids;
and respectively taking the wireless sensor node with the largest clustering judgment value in each class of grids as a cluster head node, and taking the rest wireless sensor nodes as member nodes.
By calculating the clustering judgment value, the wireless sensor node with the best forwarding capacity and forwarding effect can be selected to be used as the cluster head node in the class-I grid.
Preferably, the calculation formula of the clustering judgment value is:
clustering judgment value representing wireless sensor node k,/> Representing the current charge of k,/>Representing the maximum charge of k,/>Represents the number of wireless sensor nodes having a communication radius with k that is less than k,Representing a preset quantity comparison value; /(I)Representing the reference weight of the electric quantity,/>Representing the quantitative reference weights.
The cluster determination value takes into account, on the one hand, the current power level, and, on the other hand, the number of other wireless sensor nodes within the range of the communication radius,The larger the/>The larger the clustering judgment value is, so that the wireless sensor node with the best forwarding capacity and forwarding effect can be selected.
Preferably, the preset number comparison value is the total number of wireless sensor nodes in a class of grids.
Preferably, the charge reference weight is 0.61 and the number reference weight is 0.39.
Specifically, the two weights can be set according to actual needs, and the larger the electric quantity reference weight is, the more preferentially the wireless sensor node with high current electric quantity is used as the cluster head node.
Preferably, sending the acquired monitoring data to the cluster head node includes:
and the member node sends the acquired monitoring data to a cluster head node of the cluster where the member node is located.
After the wireless sensor node is successfully selected as the cluster head, a notification is sent to the member nodes in the class-one grid, so that the member nodes know which cluster head node of the cluster is in during the subsequent operation process.
Preferably, the detection data includes temperature, humidity, CO concentration, etc. in the room.
Preferably, S5 comprises:
In the class of grids, the calculation formula of the total amount of monitoring data obtained by member nodes is as follows:
Representing the total amount of monitoring data obtained by member nodes in a class of grids,/> Representing a set of member nodes in a class of grids; /(I)The number of times of receiving monitoring data sent by the member node c in a preset time interval is shown; /(I)Indicating the size of the monitoring data sent from the member node c received the ith time.
Preferably, dividing b into a plurality of class two grids includes:
Calculating the number Z of the class II grids:
representing a preset number;
The length and width of a class of grids are denoted wid and len, respectively;
The length and width of the second class of grids are respectively And/>；
Dividing b into a plurality of sizesIs a second class grid of (c).
In dividing a class of grids, the number of class of grids is not specified in advance, but can followAdaptively change according to the change of (1)/>The larger the two-class grids are, the larger the number of the two-class grids is, so that the area of the two-class grids in the area with larger data volume can be divided into smaller areas, and the electric quantity consumption speeds of cluster head nodes in the two-class grids with different sizes can be more approximate.
Preferably, the preset number is 4.
Preferably, selecting a cluster head node and a member node for each class two grid includes:
periodically calculating a clustering judgment value of the wireless sensor nodes in each class II grid;
and taking the line sensor node with the largest clustering judgment value as a cluster head node, and taking the rest wireless sensor nodes as member nodes.
Preferably, after S8, further comprising:
and S9, judging whether the monitoring data exceeds a corresponding threshold value, and if so, sending out an indoor environment abnormality prompt.
According to the invention, the corresponding threshold value is set in advance according to the type of the monitoring data, for example, the threshold value of the temperature is 35 ℃, so that the condition of abnormal indoor environment can be timely found.
Preferably, issuing the indoor environment abnormality prompt includes:
Playing the pre-recorded prompt record.
Preferably, determining whether the monitored data exceeds a corresponding threshold value includes:
first, for the monitoring data D, the member node acquiring the monitoring data D is expressed as ；
Acquisition and acquisition ofThe distance between them is less than/>Set of member nodes/>；
The optimized value of D is calculated using the following formula:
Representing the optimized value of D,/> Representation/>And/>The distance between the member nodes j of (a),Representation/>And/>Maximum value of distances between member nodes in (a)/>Representing j obtained monitoring data of the same type and same acquisition time as D,/>Represent D and/>Maximum value of absolute value of difference value between monitoring data which are obtained by member nodes in the network and have the same acquisition time and the same type as D,/>Representing a first optimization weight,/>Representing a second optimization weight,/>Representing an optimized reference value of D; r represents the communication radius of the member node.
Representing monitoring data D at/>Serial number in the obtained monitoring data,/>Representing an adaptive interval parameter greater than 0,/>Representation/>The h monitoring data are obtained;
and secondly, judging whether the monitoring data D exceeds a corresponding threshold value.
When judging whether the threshold value is exceeded or not, the invention does not directly compare the value of D with the corresponding threshold value, because D is possibly erroneous monitoring data obtained after the member node is interfered.
Therefore, the invention can effectively improve the accuracy of abnormal prompt and avoid the influence of the excessively high false alarm probability on the normal activities of indoor personnel by obtaining the optimized value based on D. Specifically, in calculating the optimal value, the present invention is based on the fact that the distance from V is smaller thanThe member nodes of the system can obtain the monitoring data with the same type as the D at the same time and calculate the optimized value based on the monitoring data with the same type as the D, which is obtained by the V in advance, so that the optimized value can be comprehensively calculated based on the reference data in time and space, and the result is more accurate. If it is based on the distance from V being smaller than/>The same type of monitoring data as D obtained by the member nodes of (a) at the same time to calculate an optimal value, the obtained optimal value may not be accurate enough because bursty interference due to a local range may occur, resulting in/>The invention also adds the monitoring data which is obtained by V and has the same type as D to calculate the optimized value together, thereby effectively reducing the difference between the calculated optimized value and the true value.
At a distance from V smaller thanWhen the member nodes of (1) calculate the monitoring data which are obtained at the same time and have the same type as D, the smaller the distance between j and V is, D and/>The smaller the gap between them, the/>The greater the impact on the final calculated optimized value, thereby avoiding grant/>The same influence as the monitoring data with the same type of D is obtained by the member nodes in the network at the same time, so that the situation that the value of the monitoring data obtained by the member nodes with the too far distance V is too small to cause the finally obtained optimized value to be too small is avoided when the temperature abnormality occurs in a small range.
While calculations are made based on the same type of monitoring data as D previously obtained by V,The smaller the difference between the sequence number of D and the sequence number of D, the D and/>The smaller the gap between them, the/>The larger the influence on the finally calculated optimized value is, the larger the influence degree of the previously obtained monitoring data with early acquisition time and the interfered monitoring data on the calculation result of the optimized value can be avoided, so that the accuracy of the calculated optimized value is further improved.
Preferably, the first optimization weight is 0.4 and the second optimization weight is 0.6.
The foregoing is only one of the preferred embodiments, and the first optimization weight and the second optimization weight may be set according to actual needs.
Preferably, the calculation formula of the adaptive interval parameter is:
Represents the/>, obtained at V Monitoring data to/>Maximum value in the individual monitoring data,/>Indicating the set constant.
In the present invention, when the calculation is performed based on the monitoring data of the same type as D previously obtained by V, the number of data to be referred to, i.e., the value of the adaptive interval parameter is not fixed in advance but can be obtained with VTo/>The change amplitude in the monitoring data is obtained through self-adaptive calculation, and the larger the change amplitude is, the smaller the value of the self-adaptive interval parameter is, so that the optimal value obtained through calculation can be changed along with the change of the environment where V is located in time, the optimal value can reflect the current environment change situation more timely, and abnormal prompt can be made timely; the smaller the variation amplitude is, the larger the value of the self-adaptive interval parameter is, so that more data can be referred to when the calculation is performed based on the monitoring data which is obtained by V and has the same type as D, and the accuracy of the calculated optimized value is further improved.
Preferably, the constant is set to 20.
In a second aspect, as shown in fig. 2, the present invention provides an indoor environment monitoring device, which includes an acquisition module, a first division module, a first selection module, a receiving module, a statistics module, a second division module and a second selection module;
the acquisition module is used for acquiring a plane design diagram of an indoor space needing environment monitoring;
the first dividing module is used for dividing the plane design drawing into a plurality of grids with the same size;
The first selecting module is used for selecting cluster head nodes and member nodes for each type of grids, the member nodes are configured to send acquired monitoring data to the cluster head nodes, and the cluster head nodes are configured to send the acquired monitoring data to the wireless gateway so as to obtain a first wireless sensor network;
The receiving module is used for receiving monitoring data which are sent by the first wireless sensor network and are acquired by the member node in a preset time interval;
the statistics module is used for counting the total amount of monitoring data obtained by member nodes in each class of grids in a preset time interval;
the second dividing module is used for dividing the first class grids based on the total amount of the monitoring data obtained by each member node to obtain second class grids;
the second selecting module is used for selecting cluster head nodes and member nodes for each class II grid, the member nodes are configured to send the acquired monitoring data to the cluster head nodes, and the cluster head nodes are configured to send the acquired monitoring data to the wireless gateway so as to obtain a second wireless sensor network;
the receiving module is also used for receiving monitoring data which are sent by the second wireless sensor network and are acquired by the member node;
Dividing a class-one grid based on the total amount of monitoring data obtained by each member node to obtain a class-two grid, wherein the method comprises the following steps:
Calculating the average value of the total amount of the monitoring data obtained by the member nodes in all the types of grids in a preset time interval ；
For the class of grids b, the total amount of monitoring data obtained by member nodes in the class of grids b in a preset time interval is expressed as；
If it isDividing b into a plurality of class-two grids,/>, andRepresenting a preset judgment coefficient; otherwise, b is directly used as the class II grid.
Preferably, the system also comprises an abnormality alarm module;
The abnormality warning module is used for judging whether the monitoring data exceeds the corresponding threshold value, and if so, sending out an indoor environment abnormality prompt.
In a third aspect, the present invention provides an apparatus for indoor environmental monitoring, comprising at least one processor and a memory storing computer executable instructions, the processor implementing the steps of the indoor environmental monitoring method of the first aspect when executing the instructions.
In a fourth aspect, the present invention provides a computer readable storage medium for indoor environment monitoring, comprising a memory for storing processor executable instructions which when executed by the processor implement the steps of the indoor environment monitoring method of the first aspect.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (5)
1. An indoor environment monitoring method, comprising:
s1, acquiring a plane design diagram of an indoor space needing environment monitoring;
s2, dividing the plane design diagram into a plurality of grids with the same size;
S3, selecting cluster head nodes and member nodes for each type of grids, wherein the member nodes are configured to send acquired monitoring data to the cluster head nodes, and the cluster head nodes are configured to send the acquired monitoring data to a wireless gateway so as to obtain a first wireless sensor network;
S4, receiving monitoring data which are sent by a first wireless sensor network and are acquired by member nodes in a preset time interval;
s5, counting the total amount of monitoring data obtained by member nodes in each class of grids in a preset time interval;
S6, dividing a class of grids based on the total amount of monitoring data obtained by each member node to obtain a class II grid;
S7, selecting cluster head nodes and member nodes for each class II grid, wherein the member nodes are configured to send acquired monitoring data to the cluster head nodes, and the cluster head nodes are configured to send the acquired monitoring data to the wireless gateway so as to obtain a second wireless sensor network;
s8, receiving monitoring data obtained by the member node and sent by the second wireless sensor network;
Wherein S6 includes:
Calculating the average value of the total amount of the monitoring data obtained by the member nodes in all the types of grids in a preset time interval ；
For the class of grids b, the total amount of monitoring data obtained by member nodes in the class of grids b in a preset time interval is expressed as；
If it isDividing b into a plurality of class-two grids,/>, andRepresenting a preset judgment coefficient; otherwise, directly taking b as a class II grid;
S2 comprises the following steps:
s21, obtaining a minimum circumscribed rectangle A of a plane design drawing;
S22, dividing the length and the width of the minimum circumscribed rectangle A into L1 and L2, and calculating the number of the first type of grids as follows:
；
N represents the number of the class of grids, and R represents the communication radius of the member node;
S23, judging If it is 0, if it is not, the length of A is extended/>If yes, the length of the A is not changed; judgment/>If it is 0, if it is not, the width of A is extended/>If yes, the length of the B is not changed;
s24, dividing the rectangle obtained in the S23 into N grids with the same size, wherein each grid is square with the side length of 2R;
selecting cluster head nodes and member nodes for each class of grids, including:
Respectively calculating a clustering judgment value of each wireless sensor node in each class of grids;
The wireless sensor node with the largest clustering judgment value in each class of grids is used as a cluster head node, and the rest wireless sensor nodes are used as member nodes;
The calculation formula of the clustering judgment value is as follows:
；
clustering judgment value representing wireless sensor node k,/> Representing the current charge of k,/>Representing the maximum charge of k,/>Represents the number of wireless sensor nodes having a communication radius with k that is less than k,Representing a preset quantity comparison value; /(I)Representing the reference weight of the electric quantity,/>Representing a quantity reference weight;
s5 comprises the following steps:
In the class of grids, the calculation formula of the total amount of monitoring data obtained by member nodes is as follows:
；
Representing the total amount of monitoring data obtained by member nodes in a class of grids,/> Representing a set of member nodes in a class of grids; /(I)The number of times of receiving monitoring data sent by the member node c in a preset time interval is shown; /(I)The size of the monitoring data sent by the member node c received for the ith time is represented;
Dividing b into a plurality of class-two grids, including:
Calculating the number Z of the class II grids:
；
representing a preset number;
The length and width of a class of grids are denoted wid and len, respectively;
The length and width of the second class of grids are respectively And/>；
Dividing b into a plurality of sizesIs a second class grid of (c).
2. The indoor environment monitoring method according to claim 1, wherein transmitting the acquired monitoring data to the cluster head node comprises:
and the member node sends the acquired monitoring data to a cluster head node of the cluster where the member node is located.
3. The indoor environment monitoring device is characterized by comprising an acquisition module, a first dividing module, a first selecting module, a receiving module, a statistics module, a second dividing module and a second selecting module;
the acquisition module is used for acquiring a plane design diagram of an indoor space needing environment monitoring;
the first dividing module is used for dividing the plane design drawing into a plurality of grids with the same size;
The first selecting module is used for selecting cluster head nodes and member nodes for each type of grids, the member nodes are configured to send acquired monitoring data to the cluster head nodes, and the cluster head nodes are configured to send the acquired monitoring data to the wireless gateway so as to obtain a first wireless sensor network;
The receiving module is used for receiving monitoring data which are sent by the first wireless sensor network and are acquired by the member node in a preset time interval;
the statistics module is used for counting the total amount of monitoring data obtained by member nodes in each class of grids in a preset time interval;
the second dividing module is used for dividing the first class grids based on the total amount of the monitoring data obtained by each member node to obtain second class grids;
the second selecting module is used for selecting cluster head nodes and member nodes for each class II grid, the member nodes are configured to send the acquired monitoring data to the cluster head nodes, and the cluster head nodes are configured to send the acquired monitoring data to the wireless gateway so as to obtain a second wireless sensor network;
the receiving module is also used for receiving monitoring data which are sent by the second wireless sensor network and are acquired by the member node;
Dividing a class-one grid based on the total amount of monitoring data obtained by each member node to obtain a class-two grid, wherein the method comprises the following steps:
Calculating the average value of the total amount of the monitoring data obtained by the member nodes in all the types of grids in a preset time interval ；
For the class of grids b, the total amount of monitoring data obtained by member nodes in the class of grids b in a preset time interval is expressed as；
If it isDividing b into a plurality of class-two grids,/>, andRepresenting a preset judgment coefficient; otherwise, directly taking b as a class II grid;
Dividing the planar design drawing into a plurality of grids of the same type, including:
s21, obtaining a minimum circumscribed rectangle A of a plane design drawing;
S22, dividing the length and the width of the minimum circumscribed rectangle A into L1 and L2, and calculating the number of the first type of grids as follows:
；
N represents the number of the class of grids, and R represents the communication radius of the member node;
S23, judging Whether 0, if not, extending the length of A to 0If yes, the length of the A is not changed; judgment/>If it is 0, if it is not, the width of A is extended/>If yes, the length of the B is not changed;
s24, dividing the rectangle obtained in the S23 into N grids with the same size, wherein each grid is square with the side length of 2R;
selecting cluster head nodes and member nodes for each class of grids, including:
Respectively calculating a clustering judgment value of each wireless sensor node in each class of grids;
The wireless sensor node with the largest clustering judgment value in each class of grids is used as a cluster head node, and the rest wireless sensor nodes are used as member nodes;
The calculation formula of the clustering judgment value is as follows:
；
clustering judgment value representing wireless sensor node k,/> Representing the current charge of k,/>Representing the maximum charge of k,/>Represents the number of wireless sensor nodes having a communication radius with k that is less than k,Representing a preset quantity comparison value; /(I)Representing the reference weight of the electric quantity,/>Representing a quantity reference weight;
counting the total amount of monitoring data obtained by member nodes in each class of grids in a preset time interval, wherein the total amount comprises the following steps:
In the class of grids, the calculation formula of the total amount of monitoring data obtained by member nodes is as follows:
；
Representing the total amount of monitoring data obtained by member nodes in a class of grids,/> Representing a set of member nodes in a class of grids; /(I)The number of times of receiving monitoring data sent by the member node c in a preset time interval is shown; /(I)The size of the monitoring data sent by the member node c received for the ith time is represented;
Dividing b into a plurality of class-two grids, including:
Calculating the number Z of the class II grids:
；
representing a preset number;
The length and width of a class of grids are denoted wid and len, respectively;
The length and width of the second class of grids are respectively And/>；
Dividing b into a plurality of sizesIs a second class grid of (c).
4. An apparatus for indoor environmental monitoring, comprising at least one processor and a memory storing computer executable instructions that when executed by the processor implement the steps of the indoor environmental monitoring method of any one of claims 1-2.
5. A computer readable storage medium for indoor environment monitoring, comprising a memory for storing processor executable instructions which when executed by the processor implement the steps comprising the indoor environment monitoring method of any of claims 1-2.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410354012.8A CN117956540B (en) | 2024-03-27 | 2024-03-27 | Indoor environment monitoring method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410354012.8A CN117956540B (en) | 2024-03-27 | 2024-03-27 | Indoor environment monitoring method, device, equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117956540A CN117956540A (en) | 2024-04-30 |
| CN117956540B true CN117956540B (en) | 2024-06-14 |
Family
ID=90798101
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410354012.8A Active CN117956540B (en) | 2024-03-27 | 2024-03-27 | Indoor environment monitoring method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117956540B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106550422A (en) * | 2016-11-08 | 2017-03-29 | 华中科技大学 | A kind of wireless sensor network clustering routing based on harmonic search algorithm |
| CN115915327A (en) * | 2022-11-30 | 2023-04-04 | 昆明理工大学 | Double-cluster-head WSNs self-adaptive relay routing method based on optimized clustering |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7903631B2 (en) * | 2007-02-02 | 2011-03-08 | Lockheed Martin Corporation | Mesh-to-cluster protocol |
| CN103533595A (en) * | 2013-10-28 | 2014-01-22 | 天津工业大学 | Multi-hop clustering routing algorithm (GEEMHCR) for wireless sensor networks |
| DE112018003399T5 (en) * | 2017-07-01 | 2020-03-12 | Intel Corporation | METHOD AND DEVICES FOR VEHICLE RADIO COMMUNICATIONS |
| CN110602757B (en) * | 2019-09-18 | 2023-05-12 | 上海海事大学 | Wireless sensor network clustering routing method based on adaptive genetic algorithm |
| CN116828560B (en) * | 2023-08-28 | 2023-10-27 | 国网四川省电力公司电力应急中心 | Transformer substation anti-seismic state monitoring system based on wireless sensor network |
-
2024
- 2024-03-27 CN CN202410354012.8A patent/CN117956540B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106550422A (en) * | 2016-11-08 | 2017-03-29 | 华中科技大学 | A kind of wireless sensor network clustering routing based on harmonic search algorithm |
| CN115915327A (en) * | 2022-11-30 | 2023-04-04 | 昆明理工大学 | Double-cluster-head WSNs self-adaptive relay routing method based on optimized clustering |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117956540A (en) | 2024-04-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US7356548B1 (en) | System and method for remote monitoring and controlling of facility energy consumption | |
| CN107276999B (en) | Event detection method in wireless sensor network | |
| JP2017123124A (en) | Radio communication abnormality detection method, radio communication abnormality detection program, and radio communication abnormality detection device | |
| US12095797B1 (en) | Microservices anomaly detection | |
| CN111800751B (en) | Groundwater quality of water monitored control system | |
| CN115759450A (en) | Carbon emission accounting early warning analysis system based on big data | |
| CN107371175B (en) | Self-organizing network fault detection method using cooperative prediction | |
| EP2120181A1 (en) | A sensor node, a sensor network and a method for autonomous decision-making in sensor networks | |
| KR101738745B1 (en) | A Method for a Crime Prediction by Estimating a Cell Value and A System for the Same | |
| CN117956540B (en) | Indoor environment monitoring method, device, equipment and storage medium | |
| CN109211564B (en) | Self-adaptive threshold detection method for health assessment of ball screw pair | |
| CN112135269B (en) | Intelligent fire-fighting early warning system applied to production workshop | |
| CN111784989B (en) | Information security management system based on big data | |
| CN110505571B (en) | Risk topic analysis system based on artificial intelligence technology | |
| CN113709083A (en) | Network attack detection control method, device, base station and computer storage medium | |
| CN115048274B (en) | Operation and maintenance system based on big data | |
| CN111679050A (en) | Water quality monitoring and early warning system based on Internet of things | |
| CN114047693B (en) | Self-adaptive prevention method and system for fire disaster of automobile battery facing charging process | |
| CN109238716B (en) | Real-time intelligent mechanical bearing abnormity detection system | |
| CN111836228A (en) | Safety precaution analysis alarm system based on thing networking | |
| CN108961701B (en) | Intelligent monitoring system for environment of transformer substation | |
| CN109714792B (en) | Data collection method, device and system | |
| CN118226791B (en) | Industrial control computer self-checking control system and method | |
| CN111064606B (en) | Data dynamic transmission system and method based on time period characteristics | |
| Borisovskaya et al. | Numerical Calculation of Random Access Characteristics for Sensors with Correlated Activation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |