CN113746681B - Method, device, equipment and storage medium for detecting perception holes - Google Patents
Method, device, equipment and storage medium for detecting perception holes Download PDFInfo
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Abstract
The invention provides a detection method, a device, equipment and a storage medium for a perception cavity, wherein the method comprises the following steps: firstly, determining at least one sub-network contained in the Internet of things according to network topological relations of a plurality of sensor nodes in the Internet of things, then determining the gravity center of the sub-network, then taking the gravity center of the sub-network as a center point, simulating gas diffusion, then obtaining gas values detected by each sensor node in the sub-network, and finally determining whether a perception hole exists in the sub-network according to each gas value. According to the sensing boundary theory, the method starts from the center of gravity of the irregular polygon through the topological relation of the sensor nodes, simulates gas diffusion and determines whether a sensing cavity exists or not, so that the method not only improves the detection efficiency, but also saves manpower and energy consumption, and accordingly the overall economic cost is reduced.
Description
Technical Field
The present invention relates to the field of mobile communications, and in particular, to a method, apparatus, device, and storage medium for detecting a sensing cavity.
Background
In recent years, with the development of communication technology and sensor technology, the technology of internet of things has been rapidly developed, and has gradually entered into various industries. The Internet of things greatly changes the current life style of people, becomes a driver for promoting economic development, and opens up a development opportunity with endless potential for industry. In planning and deployment of the nodes of the internet of things, various objective reasons such as faults of a sensor and a communication transceiver exist, so that a perception hole of the internet of things is inevitably caused, and how to detect the perception hole of the internet of things becomes very important.
In the prior art, a mobile sensor is generally adopted to detect a perception hole of the internet of things. The detection method has low detection efficiency and high energy consumption.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a detection method, a detection device, detection equipment and a storage medium for a perception cavity.
In a first aspect, the present invention provides a method for detecting a sensing cavity, applied to the internet of things, where the internet of things includes a plurality of sensor nodes, including:
determining at least one sub-network contained in the Internet of things according to network topological relations of the plurality of sensor nodes;
the following operations are performed for each sub-network:
determining the center of gravity of the sub-network;
simulating gas diffusion by taking the center of gravity of the sub-network as a center point;
acquiring gas values detected by each sensor node in the sub-network;
and determining whether a sensing cavity exists in the sub-network according to the values of the gases.
In a possible implementation manner, determining a sub-network included in the internet of things according to network topological relations of a plurality of sensor nodes includes: determining gateway equipment contained in the Internet of things; according to the network topological relation between the plurality of sensor nodes and the gateway equipment, determining a sub-network contained in the Internet of things, wherein the sensor nodes in the sub-network are connected to the same gateway equipment.
In a possible implementation manner, determining the center of gravity of the sub-network includes: connecting the sensor nodes at the outermost layer in the sub-network to form a polygon; the center of gravity of the polygon is determined as the center of gravity of the sub-network.
In a possible implementation manner, determining whether a sensing cavity exists in the sub-network according to each gas value includes: if the gas values are all larger than or equal to a preset threshold value, determining that no sensing cavity exists in the sub-network; if the gas value which is smaller than the preset threshold value exists in the gas values which correspond to the sensor nodes in the sub-network, determining that a sensing cavity exists in the sub-network.
In a possible embodiment, the method further comprises: after determining that a perceptual hole exists in the sub-network, the location of the perceptual hole is determined based on: for the sensor nodes with the gas values being greater than or equal to a preset threshold value, determining the sensor node positioned at the outermost layer as an inner boundary node of the sensing cavity; for the sensor nodes with the gas values smaller than the preset threshold value, determining the sensor node positioned at the innermost layer as an outer boundary node of the sensing cavity; connecting all the inner boundary nodes to determine an inner boundary area of the sensing cavity; and connecting the outer boundary nodes to determine the outer boundary area of the perception cavity.
In a possible embodiment, the method further comprises: after determining the location of the perceptual hole, the perceptual hole is pinpointed according to the following: determining interpolation points between the outer boundary region and the inner boundary region according to a radial base point interpolation method; and connecting interpolation points to determine a refined boundary line.
In a possible embodiment, the method further comprises: and determining whether the sensing holes exist in the Internet of things according to the detection result of whether the sensing holes exist in at least one sub-network included in the Internet of things.
In a second aspect, the present invention provides a sensing device for sensing a cavity, applied to the internet of things, where the internet of things includes a plurality of sensor nodes, including:
the determining module is used for determining at least one sub-network contained in the Internet of things according to the network topological relation of the plurality of sensor nodes; and determining a center of gravity of the sub-network;
the simulation module is used for simulating gas diffusion by taking the gravity center of the sub-network as a center point;
the acquisition module is used for acquiring the gas values detected by each sensor node in the sub-network;
and the determining module is also used for determining whether a sensing cavity exists in the sub-network according to the values of the gases.
In a possible implementation manner, the determining module is specifically configured to: determining gateway equipment contained in the Internet of things; according to the network topological relation between the plurality of sensor nodes and the gateway equipment, determining a sub-network contained in the Internet of things, wherein the sensor nodes in the sub-network are connected to the same gateway equipment.
In a possible implementation manner, the determining module is specifically configured to: connecting the sensor nodes at the outermost layer in the sub-network to form a polygon; the center of gravity of the polygon is determined as the center of gravity of the sub-network.
In a possible implementation manner, the determining module is specifically configured to: if the gas values are all larger than or equal to a preset threshold value, determining that no sensing cavity exists in the sub-network; if the gas value which is smaller than the preset threshold value exists in the gas values which correspond to the sensor nodes in the sub-network, determining that a sensing cavity exists in the sub-network.
In a possible implementation manner, the determining module is further configured to: after determining that a perceptual hole exists in the sub-network, the location of the perceptual hole is determined based on: for the sensor nodes with the gas values being greater than or equal to a preset threshold value, determining the sensor node positioned at the outermost layer as an inner boundary node of the sensing cavity; for the sensor nodes with the gas values smaller than the preset threshold value, determining the sensor node positioned at the innermost layer as an outer boundary node of the sensing cavity; connecting all the inner boundary nodes to determine an inner boundary area of the sensing cavity; and connecting the outer boundary nodes to determine the outer boundary area of the perception cavity.
In a possible implementation manner, the determining module is further configured to: after determining the location of the perceptual hole, the perceptual hole is pinpointed according to the following: determining interpolation points between the outer boundary region and the inner boundary region according to a radial base point interpolation method; and connecting interpolation points to determine a refined boundary line.
In a possible implementation manner, the determining module is further configured to: and determining whether the sensing holes exist in the Internet of things according to the detection result of whether the sensing holes exist in at least one sub-network included in the Internet of things.
In a third aspect, the present invention provides an electronic device comprising:
a memory and a processor;
the memory is used for storing program instructions;
the processor is configured to invoke program instructions in the memory to perform the method of detecting a perceptual hole of the first aspect.
In a fourth aspect, the present invention provides a computer readable storage medium, where computer program instructions are stored, and when the computer program instructions are executed, the method for detecting a perception hole according to the first aspect is implemented.
The invention provides a detection method, a device, equipment and a storage medium for a perception hole, which are used for determining at least one sub-network contained in the Internet of things according to network topological relations of a plurality of sensor nodes in the Internet of things; then determining the center of gravity of the sub-network; then the center of gravity of the sub-network is taken as a center point to simulate gas diffusion; then acquiring the gas values detected by each sensor node in the sub-network; and finally, determining whether a perception cavity exists in the sub-network according to the values of the gases. According to the sensing boundary theory, the method starts from the center of gravity of the irregular polygon through the topological relation of the sensor nodes, simulates gas diffusion and determines whether the sensing cavity exists or not, so that the method not only improves the detection efficiency, but also saves manpower and energy consumption, and therefore the economic cost for detecting the sensing cavity is reduced.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to the drawings without inventive effort to a person skilled in the art.
Fig. 1 is a schematic view of an application scenario provided in an embodiment of the present invention;
FIG. 2 is a flowchart of a method for detecting a sensing cavity according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating a sub-network of a method for detecting a sensing cavity according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating an example of the location of the center of gravity of the sub-network structure shown in FIG. 3;
FIG. 5 is an exemplary diagram of inner and outer border areas of the subnetwork structure shown in FIG. 3;
FIG. 6 is a diagram illustrating an example of a refined boundary line of the sub-network structure shown in FIG. 3;
FIG. 7 is a schematic structural diagram of a sensing device for detecting a sensing cavity according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of 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 apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. 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.
First, some technical terms related to the present invention will be explained:
the perceptual cavity, namely the cavity of signal transmission, has the problems of distortion, low signal-to-noise ratio, low gain and the like of the signal received by the receiver in the cavity area. Meanwhile, the signals transmitted by the cavity area transmitter also have the problems of low signal gain, short transmission distance and incapability of being transmitted to the target antenna.
Currently, in the prior art, a moving sensor is often used to detect the position of a sensing cavity, and the detection method requires manpower and long detection time, so that the detection efficiency is low. Meanwhile, the method is high in energy consumption.
Based on the above problems, the embodiments of the present invention provide a method, apparatus, device, and storage medium for detecting a sensing cavity, which starts from the center of gravity of an irregular polygon to simulate gas diffusion according to the topology relationship of sensor nodes and determine whether a sensing cavity exists, thereby saving manpower and energy consumption, and reducing overall economic cost.
Fig. 1 is a schematic view of an application scenario provided in an embodiment of the present invention. As shown in fig. 1, in the present application scenario. The method comprises the steps of inputting a topological network of sensor nodes in the Internet of things to a computer 100, determining at least one sub-network contained in the Internet of things according to network topological relations of a plurality of sensor nodes in the computer 100, determining the center of gravity of the sub-network, simulating gas diffusion by taking the center of gravity of the sub-network as a center point, acquiring gas values detected by all the sensor nodes in the sub-network, and finally determining whether a sensing cavity exists in the sub-network according to all the gas values. If the existence of the sensing cavity is determined, taking the area where the sensing cavity exists as an output result; and if the fact that the sensing holes do not exist is determined, outputting a result that the sensing holes do not exist in the topological network.
It should be noted that fig. 1 is only a schematic diagram of an application scenario provided by an embodiment of the present invention, and the embodiment of the present invention does not limit the devices included in fig. 1 or limit the positional relationship between the devices in fig. 1. For example, in the application scenario shown in fig. 1, a data storage device may be further included, where the data storage device may be an external memory with respect to the computer 100 or may be an internal memory integrated into the computer 100. The computer 100 may be a PC, that is, a computer, a terminal device such as a mobile phone or a notebook, or a mainframe computer such as a server or a server cluster.
Next, a method for detecting a sensing hole is described by way of a specific embodiment.
Fig. 2 is a flowchart of a method for detecting a perception hole according to an embodiment of the present invention, where the method is applied to the internet of things, and the internet of things includes a plurality of sensor nodes, as shown in fig. 2:
s201, determining at least one sub-network contained in the Internet of things according to network topological relations of the plurality of sensor nodes.
The invention firstly processes the topology network formed by the sensor nodes in the Internet of things, and the whole topology network is divided into a plurality of sub-networks before processing because the perception boundary theory is needed. Optionally, the rule of division is determined by each sensor node.
Step S202 to step S205 are performed for each sub-network.
It can be understood that if the area corresponding to the internet of things is smaller, the following operations may be executed for the internet of things without performing the process of dividing into a plurality of sub-networks.
S202, determining the gravity center of the sub-network.
Since the location of the sensing cavity needs to be determined based on the sensing boundary theory and in a way that simulates the gas diffusion, the center of the gas diffusion is the center of gravity of the sub-network. Therefore, in performing the analog calculation, it is first necessary to determine the position of the center of gravity of the sub-network.
S203, taking the center of gravity of the sub-network as a center point, and simulating gas diffusion.
S204, acquiring gas values detected by each sensor node in the sub-network.
In the subnetwork, the distance from the center of gravity of each sensor node is different. Specifically, when gas diffusion is simulated, a sensor node which is closer to the center of gravity detects a relatively high value of gas; sensor nodes further from the center of gravity detect relatively low values of gas.
Still further, the simulated gas diffusion corresponds to a sensing cavity of the internet of things, the lower the detected gas value is, the lower the strength of a transmitted and received signal is, and the more serious the signal is shielded; conversely, the higher the gas value, the higher the strength of the transmitted and received signal, and the lighter the signal is shielded.
S205, determining whether a sensing cavity exists in the sub-network according to the values of the gases.
After each gas value is obtained, the area where the cavity is located needs to be determined first.
For example, a definition of a perceptual hole is, in a broad sense, an area where a signal is masked or where a signal cannot be emitted or received. In the present invention, it may be an area where a signal under a certain area is shielded or where a signal cannot be emitted or received, in other words, when the distance from the center of gravity is far enough, the value of the detected gas must be small enough, so that it can be derived from the above deduction that the perception holes are theoretically infinite, but since the sub-network is not infinite and it is no longer significant for hole studies beyond a certain distance, the main purpose of the present invention is to determine the perception holes at the boundary area. Still further, if a sensory hole in a certain area has been determined, an area other than the sensory hole (an area far from the center of gravity) necessarily belongs to the sensory hole area of the sub-network.
In the embodiment of the invention, at least one sub-network contained in the Internet of things is determined according to the network topological relation of a plurality of sensor nodes in the Internet of things; then determining the center of gravity of the sub-network; then the center of gravity of the sub-network is taken as a center point to simulate gas diffusion; then acquiring the gas values detected by each sensor node in the sub-network; and finally, determining whether a perception cavity exists in the sub-network according to the values of the gases. According to the sensing boundary theory, the method starts from the center of gravity of the irregular polygon through the topological relation of the sensor nodes, simulates gas diffusion and determines whether a sensing cavity exists or not, so that the method not only improves the detection efficiency, but also saves manpower and energy consumption, and accordingly the overall economic cost is reduced.
Optionally, on the basis of the foregoing embodiment, for step S201, determining at least one sub-network included in the internet of things according to the network topology relationship of the plurality of sensor nodes may include: determining gateway equipment contained in the Internet of things; according to the network topological relation between the plurality of sensor nodes and the gateway equipment, determining a sub-network contained in the Internet of things, wherein the sensor nodes in the sub-network are connected to the same gateway equipment.
When the topological network of the Internet of things is divided, the topological network is divided according to the relation between the sensor nodes and the gateways, the sensor nodes connected with the same gateway are divided into the same sub-network, and the dividing method meets the perception boundary theory and the definition of perception hollows.
Illustratively, the method is: firstly, determining the positions and information of all gateways in a topology network of the whole Internet of things; then according to each sensor node, finding out the gateway connected with the sensor node; and finally, all the sensor nodes connected with the same gateway are divided into a sub-network. After the method is executed, the whole topological network is divided into a plurality of sub-networks, further, whether a sensing hole exists or not is determined in each sub-network, and if the sensing hole exists, a specific area of the sensing hole is determined.
Based on the above embodiment, further, determining the center of gravity of the sub-network may include: connecting the sensor nodes at the outermost layer in the sub-network to form a polygon; the center of gravity of the polygon is determined as the center of gravity of the sub-network.
Because the subnetwork is only a scopy concept, if the gas diffusion needs to be simulated at the center of gravity, a closed graph needs to be determined first, and therefore, the sensor nodes at the outermost periphery of the subnetwork need to be connected sequentially first. After a closed figure is determined, the position of its center of gravity is determined geometrically.
For example, in determining the center of gravity, according to the theorem, for any two polygons, after determining the positions of the centers of gravity of the two polygons, the centers of gravity of the graphics of the combination thereof may also be determined. Specifically, the position of the center of gravity thereof must be on a line segment connecting the centers of gravity of the two polygons. Further, if the area of the polygon a is Sa, the area of the polygon B is Sb, the center of gravity of the polygon a is the point a, the center of gravity of the polygon B is the point B, the center of gravity of the polygon combined by the two polygons is the point c, and the following relationship exists: sa=sb×bc, from which the position of the center of gravity c can be obtained, where ac is used to represent the distance between the points a and c; bc is used to represent the distance between point b and point c.
In the invention, for a complex sub-network, which can be an irregular concave polygon, in order to determine the position of the gravity center according to the method, the irregular polygon can be divided into a plurality of triangles, the triangles are gradually combined by the method, the gravity center of the combined graph is determined, and finally the gravity center of the whole irregular polygon can be calculated.
In some embodiments, the determining whether a sensing hole exists in the sub-network according to each gas value may include: if the gas values are all larger than or equal to a preset threshold value, determining that no sensing cavity exists in the sub-network; if the gas value which is smaller than the preset threshold value exists in the gas values which correspond to the sensor nodes in the sub-network, determining that a sensing cavity exists in the sub-network.
Before the simulation of the gas by the gravity center, a threshold value needs to be preset, which has no meaning in the gas simulation, but the threshold value can be represented by the signal strength just meeting the signal receiving and transmitting in the signal transmission corresponding to the Internet of things. If the signal transmission and reception are less than the threshold, the signal transmission and signal coverage cannot be well realized in the area below the threshold, and the area can be used as a perception hole area. Specifically, if in the sub-network, the gas values detected by all the sensor nodes are greater than a preset threshold, that is, there is no area in the sub-network where the signal cannot cover, so that the sub-network does not have a sensing cavity area; if a part of sensor nodes (outer sensor nodes) of the sub-network have the condition that the gas value is smaller than a preset threshold value, the existence of a sensing cavity in the sub-network can be determined, and then the area where the sensing cavity is located is specifically determined.
In the embodiment of the invention, the coverage mode of the signals is reflected by the mode of simulating gas diffusion, so that the accuracy of a calculation result can be ensured while the calculation mode is simplified.
On the basis of the above embodiment, the detection method of a perception hole of the present invention may further include: after determining that a perceptual hole exists in the sub-network, the location of the perceptual hole is determined based on: for the sensor nodes with the gas values being greater than or equal to a preset threshold value, determining the sensor node positioned at the outermost layer as an inner boundary node of the sensing cavity; for the sensor nodes with the gas values smaller than the preset threshold value, determining the sensor node positioned at the innermost layer as an outer boundary node of the sensing cavity; connecting all the inner boundary nodes to determine an inner boundary area of the sensing cavity; and connecting the outer boundary nodes to determine the outer boundary area of the perception cavity.
For the sub-network with the sensing cavity, the method aims to roughly determine the approximate area where the sensing cavity is located according to the gas value provided by the existing sensor nodes, specifically, when determining the inner boundary and the outer boundary, the sensor nodes with the gas value larger than or equal to the preset threshold value and the sensor nodes with the gas value smaller than the preset threshold value are distinguished, and further, the sensor nodes on the outermost layer of the sensor nodes with the gas value larger than or equal to the preset threshold value are determined to be the inner boundary nodes, so that the sensing cavity can be determined to be positioned outside the inner boundary nodes (the position farther from the center of gravity); among the sensor nodes whose gas values are smaller than the preset threshold, the sensor node of the innermost layer is determined to be the outer boundary node, and it can also be determined that the sensing cavity is located inside the outer boundary node (a position closer to the center of gravity). Since the sensor nodes are discretely distributed, in order to determine the closed area where the sensing cavity is located, it is also necessary to connect all inner boundary nodes and all outer boundary nodes, so as to determine the inner boundary area and the outer boundary area respectively. At this time, the perceptual hole is in a ring-like region surrounded by the inner boundary region and the outer boundary region.
Still further, the method for detecting a perception hole may further include: after determining the location of the perceptual hole, the perceptual hole is pinpointed according to the following: determining interpolation points between the outer boundary region and the inner boundary region according to a radial base point interpolation method; and connecting interpolation points to determine a refined boundary line. The region comprised by the refined boundary line and the outer boundary region is determined as a perceptual hole.
In order to refine the boundary line, the position of the sensing cavity is further accurately determined, which cannot be satisfied by only adopting the existing sensor node. Therefore, the invention adopts a radial base point interpolation method, and the position of an interpolation point is determined through a radial interpolation function, wherein the interpolation point is used as a critical point of a perception cavity, and the region outside the critical point is the perception cavity.
Illustratively, the interpolation function employed by the present invention is:
wherein X is the distance from the center of gravity point of the position needing interpolation. Xi is the distance of the position of the known sensor from the center of gravity point. f (X) represents the gas value required.
Wherein, the liquid crystal display device comprises a liquid crystal display device,
with respect to c 0 And c 1 The method can be determined according to the existing sensor node and the gas value by a least square method, and specifically, a regression linear equation of the least square method can be written as:
f(X 1 )＝c 0 +c 1 X 1
f(X 2 )＝c 0 +c 1 X 2
f(X n )＝c 0 +c 1 X n
in the above expression, X and f (X) values of a plurality of sensor nodes are substituted; at the same time, also calculate the known X 1 To X n Average value of (2)
F (X) 1 ) To f (X) n ) Mean value of>
Is provided with->
The value of (2) is c +>
D, then:
wherein n is the number of the sensing nodes.
Calculating c 1 After the value of (2), by the expression:
can further determine c 0 Is a value of (2).
In addition, in the interpolation function,
x c longitude, y representing center of gravity c A latitude indicating a center of gravity point; x is x i Longitude, y representing interpolation point i Representing the latitude of the interpolation point;
when interpolation points are calculated by a radial base point interpolation method, the sub-network is required to be subjected to grid division, and firstly, sensor nodes of the sub-network are required to be quantized so as to obtain the abscissa, wherein the abscissa can be a longitude value and the ordinate can be a latitude value; the second is that interpolation can be performed only after grid division, and the interpolation function is discrete, so that the grid is more suitable for the interpolation function relative to a coordinate system. Further, the finer the meshing, the more interpolation points the more accurate the final result.
The previous embodiments have already discussed that the gas value of the interpolation point is just at the point of the preset threshold value when the interpolation point is located, therefore, f (X) needs to be equal to the preset threshold value when the interpolation point is calculated, on the basis of determining the interpolation point according to the function, there are innumerable interpolation points theoretically, and when the number of the interpolation points is larger, the finer boundary line is more accurate, and finally the finally determined perception hole is more accurate. In addition, when the interpolation points are connected to determine the refined boundary line, the connection mode may be line segment connection or smooth curve connection, and when the number of interpolation points is large enough, the curves drawn by the two points are identical.
After the definition boundary line is determined, the position of the perception cavity is accurately determined, and the determination method is that the definition boundary line and the outer boundary region enclose an annular area, and the annular area is smaller than the annular area enclosed by the outer boundary region and the inner boundary region.
In the embodiment of the invention, the irregularity of the boundary area is considered, the nonlinear interpolation is realized by adopting a radial base point interpolation method, and the spatial characteristics (c 0, c1 and the spatial characteristics of a plurality of known values of an interpolation function are combined
) Also consider the distance lambda between the desired interpolation position and the center of gravity i Therefore, the obtained interpolation result is closer to the real numerical value, and compared with the method for determining the cavity area by adopting the mobile sensor, the energy consumption is reduced to a great extent, and the efficiency is improved.
In some implementations, the method for detecting a sensing cavity in the present invention may further include: and determining whether the sensing holes exist in the Internet of things according to the detection result of whether the sensing holes exist in at least one sub-network included in the Internet of things.
In the actual processing, the final output result is whether the whole internet of things has a sensing hole or not and the position of the sensing hole, so that after the position of the sensing hole in each sub-network is determined, the sensing hole in the internet of things is finally determined through integration.
Next, the method for detecting a sensing hole provided by the present invention is described by a specific image, and fig. 3, 4, 5 and 6 are exemplary diagrams of relevant structures of sub-networks of the method for detecting a sensing hole in the embodiment of the present invention.
Firstly, dividing a sub-network, namely dividing the whole large topological network into a plurality of sub-networks, wherein the principle of dividing the sub-networks is as follows: if each sensor node can be connected to the same gateway in a certain area, the network topology formed by the sensor nodes is divided into a sub-network. Fig. 3 is a diagram showing a structural example of a sub-network of a sensing cavity detection method in an embodiment of the present invention, where, as shown in fig. 3, circles represent sensor nodes, and the outermost sensor nodes (S2, S3, O1 to O15) are connected to form an irregular polygon.
And secondly, determining the gravity center of the sub-network, and finding the gravity center of the irregular polygon. The method for determining the network gravity center of the irregular polygon is more, and the method for finding the gravity center of the irregular polygon can be as follows: the intersection point of the three central lines of the triangle is the gravity center of the triangle, the gravity center of any polygon can be found out by a ruler-rule drawing method through the following theorem for any polygon, and a sub-network behind the gravity center is determined. Fig. 4 is a diagram illustrating an example of a center of gravity of the sub-network structure shown in fig. 3, and Xc is a center of gravity in the diagram as shown in fig. 4.
And thirdly, finding out a sub-network boundary area, taking the center of gravity of the irregular polygon of the sub-network as a center point, simulating gas diffusion into the sub-network area, and then detecting and acquiring the gas value detected by each sensor node. And sensor nodes with gas values smaller than a preset threshold value exist in the sub-network, namely, a sensing cavity exists. At this time, for the case that the gas value is greater than the preset threshold, the sensor node whose outermost layer is greater than the preset threshold is set as the inner boundary node; and setting the sensor node of which the innermost layer is smaller than the preset threshold value as an outer boundary node under the condition that the gas value is smaller than the preset threshold value. FIG. 5 is an exemplary diagram of inner and outer boundary regions of the subnetwork structure of FIG. 3, as shown in FIG. 5, sensor nodes numbered I1, I2, I3, I4, I5 are inner boundary nodes; the sensor nodes numbered S1 to S12 are outer boundary nodes; o1 to O15, S12 and S13 are outermost sensor nodes of the subnetwork. Connecting sensor nodes of the inner boundary nodes to determine an inner boundary area; and connecting the sensor nodes of the outer boundary nodes to determine an outer boundary area. The connection mode of the sensor nodes can be a line segment connection mode.
And fourthly, refining the boundary line, drawing the boundary line, and determining the perception cavity. Interpolation is performed at a position where the detected gas value is just a preset threshold value by a radial base point interpolation method, and interpolation points are connected to obtain a refined boundary line. After the definition boundary line is determined, the area surrounded by the definition boundary line and the outer boundary area is the perception cavity of the sub-network. FIG. 6 is a diagram illustrating an example of a refined boundary line of the subnetwork structure shown in FIG. 3, as shown in FIG. 6, the sensor nodes labeled I1, I2, I3, I4, I5 are internal boundary nodes; the sensor nodes numbered S1 to S12 are outer boundary nodes; o1 to O15, S12 and S13 are outermost sensor nodes of the subnetwork. The enclosed area surrounded by the refined boundary line and the outer boundary area is a perception hole. Through the method, the area where the sensing holes in each sub-network are located can be determined, and then the sensing holes of the whole Internet of things are determined.
Fig. 7 is a schematic structural diagram of a sensing cavity detection device according to an embodiment of the invention. The detection device for the perception holes is applied to the Internet of things, and the Internet of things comprises a plurality of sensor nodes. As shown in fig. 7, the sensing device 700 for sensing a cavity includes:
a determining module 701, configured to determine at least one sub-network included in the internet of things according to network topology relationships of the plurality of sensor nodes; and determining a center of gravity of the sub-network.
A simulation module 702, configured to simulate gas diffusion with the center of gravity of the subnetwork as a center point;
an acquiring module 703, configured to acquire a gas value detected by each sensor node in the subnetwork;
the determining module 701 is further configured to determine whether a sensing hole exists in the sub-network according to each gas value.
In some embodiments, the determining module 701 is specifically configured to: determining gateway equipment contained in the Internet of things; according to the network topological relation between the plurality of sensor nodes and the gateway equipment, determining a sub-network contained in the Internet of things, wherein the sensor nodes in the sub-network are connected to the same gateway equipment.
In some embodiments, the determining module 701 is specifically configured to: connecting the sensor nodes at the outermost layer in the sub-network to form a polygon; the center of gravity of the polygon is determined as the center of gravity of the sub-network.
In some embodiments, the determining module 701 is specifically configured to: if the gas values are all larger than or equal to a preset threshold value, determining that no sensing cavity exists in the sub-network; if the gas value which is smaller than the preset threshold value exists in the gas values which correspond to the sensor nodes in the sub-network, determining that a sensing cavity exists in the sub-network.
In some embodiments, the determining module 701 is further configured to: after determining that a perceptual hole exists in the sub-network, the location of the perceptual hole is determined based on: for the sensor nodes with the gas values being greater than or equal to a preset threshold value, determining the sensor node positioned at the outermost layer as an inner boundary node of the sensing cavity; for the sensor nodes with the gas values smaller than the preset threshold value, determining the sensor node positioned at the innermost layer as an outer boundary node of the sensing cavity; connecting all the inner boundary nodes to determine an inner boundary area of the sensing cavity; and connecting the outer boundary nodes to determine the outer boundary area of the perception cavity.
In some embodiments, the determining module 701 is further configured to: after determining the location of the perceptual hole, the perceptual hole is pinpointed according to the following: determining interpolation points between the outer boundary region and the inner boundary region according to a radial base point interpolation method; and connecting interpolation points to determine a refined boundary line.
In some embodiments, the determining module 701 is further configured to: and determining whether the sensing holes exist in the Internet of things according to the detection result of whether the sensing holes exist in at least one sub-network included in the Internet of things.
The device provided in the embodiment of the present invention may be used to execute the method of the foregoing embodiment, and its implementation principle and technical effects are similar, and will not be described herein.
It should be noted that, it should be understood that the division of the modules of the above apparatus is merely a division of a logic function, and may be fully or partially integrated into a physical entity or may be physically separated. And these modules may all be implemented in software in the form of calls by the processing element; or can be realized in hardware; the method can also be realized in a form of calling software by a processing element, and the method can be realized in a form of hardware by a part of modules. For example, the processing module may be a processing element that is set up separately, may be implemented in a chip of the above-mentioned apparatus, or may be stored in a memory of the above-mentioned apparatus in the form of program codes, and the functions of the above-mentioned processing module may be called and executed by a processing element of the above-mentioned apparatus. The implementation of the other modules is similar. In addition, all or part of the modules can be integrated together or can be independently implemented. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in a software form.
For example, the modules above may be one or more integrated circuits configured to implement the methods above, such as: one or more specific integrated circuits (application specific integrated circuit, ASIC), or one or more microprocessors (digital signal processor, DSP), or one or more field programmable gate arrays (field programmable gate array, FPGA), or the like. For another example, when a module above is implemented in the form of a processing element scheduler code, the processing element may be a general purpose processor, such as a central processing unit (central processing unit, CPU) or other processor that may invoke the program code. For another example, the modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present invention, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), etc.
Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. The electronic device may be provided as a server or computer, for example. Referring to fig. 8, an electronic device 800 includes a processing component 801 that further includes one or more processors and memory resources represented by memory 802 for storing instructions, such as applications, executable by the processing component 801. The application program stored in the memory 802 may include one or more modules each corresponding to a set of instructions. Further, processing component 801 is configured to execute instructions to perform any of the method embodiments described above.
The electronic device 800 may also include a power component 803 configured to perform power management of the electronic device 800, a wired or wireless network interface 804 configured to connect the electronic device 800 to a network, and an input output (I/O) interface 805. The electronic device 800 may operate based on an operating system stored in the memory 802, such as Windows Server, mac OS XTM, unixTM, linuxTM, freeBSDTM, or the like.
The invention also provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and when the processor executes the computer execution instructions, the scheme of the detection method of the perception holes is realized.
The invention also provides a computer program product comprising a computer program which, when executed by a processor, implements the solution of the above method for detecting a perception hole.
The computer readable storage medium described above may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk. A readable storage medium can be any available medium that can be accessed by a general purpose or special purpose computer.
An exemplary readable storage medium is coupled to the processor such the processor can read information from, and write information to, the readable storage medium. In the alternative, the readable storage medium may be integral to the processor. The processor and the readable storage medium may reside in an application specific integrated circuit (Application Specific Integrated Circuits, ASIC for short). Of course, the processor and the readable storage medium may reside as discrete components in a sensing device for a perception hole.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution 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,
those of ordinary skill in the art will appreciate that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (9)
1. The detection method of the sensing cavity is characterized by being applied to the Internet of things, wherein the Internet of things comprises a plurality of sensor nodes, and the detection method of the sensing cavity comprises the following steps:
determining at least one sub-network contained in the Internet of things according to the network topological relation of the plurality of sensor nodes;
the following operations are performed for each of the subnetworks:
determining a center of gravity of the sub-network;
simulating gas diffusion by taking the gravity center of the sub-network as a center point;
acquiring gas values detected by each sensor node in the sub-network;
determining whether a sensing cavity exists in the sub-network according to each gas value;
the determining the center of gravity of the sub-network includes:
connecting the sensor nodes at the outermost layer in the sub-network to form a polygon;
and determining the gravity center of the polygon as the gravity center of the sub-network.
2. The method for detecting a sensing hole according to claim 1, wherein determining a sub-network included in the internet of things according to network topology relations of the plurality of sensor nodes comprises:
determining gateway equipment contained in the Internet of things;
and determining a sub-network contained in the Internet of things according to the network topological relation between the plurality of sensor nodes and the gateway equipment, wherein the sensor nodes in the sub-network are connected to the same gateway equipment.
3. The method for detecting a sensing hole according to any one of claims 1 to 2, wherein determining whether a sensing hole exists in the sub-network according to each of the gas values comprises:
if the gas values are all larger than or equal to a preset threshold value, determining that no sensing cavity exists in the sub-network;
and if the gas value which is smaller than the preset threshold value exists in the gas values corresponding to the sensor nodes in the sub-network, determining that a sensing cavity exists in the sub-network.
4. A method of detecting a perception void according to claim 3, further comprising:
after determining that a sensory hole exists in the sub-network, determining a location of the sensory hole based on:
for the sensor nodes with the gas values larger than or equal to a preset threshold value, determining the sensor node positioned at the outermost layer as an inner boundary node of the sensing cavity;
for the sensor nodes with the gas values smaller than a preset threshold value, determining the sensor node positioned at the innermost layer as an outer boundary node of the sensing cavity;
connecting the inner boundary nodes and determining an inner boundary area of the perception cavity;
and connecting the outer boundary nodes to determine the outer boundary area of the perception cavity.
5. The method for detecting a perception hole as claimed in claim 4, further comprising:
after determining the location of the perceptual hole, the perceptual hole is refined to be located according to the following:
determining interpolation points between the outer boundary region and the inner boundary region according to a radial base point interpolation method;
connecting the interpolation points to determine a refined boundary line;
and determining the area contained in the refined boundary line and the outer boundary area as the perception hole.
6. The method for detecting a perception hole according to any one of claims 1 to 2, further comprising:
and determining whether a sensing hole exists in the Internet of things according to a detection result of whether the sensing hole exists in at least one sub-network included in the Internet of things.
7. The utility model provides a detection device of perception hole, its characterized in that is applied to the thing networking, the thing networking contains a plurality of sensor nodes, detection device of perception hole includes:
the determining module is used for determining at least one sub-network contained in the Internet of things according to the network topological relation of the plurality of sensor nodes; and determining a center of gravity of the sub-network;
the simulation module is used for simulating gas diffusion by taking the gravity center of the sub-network as a center point;
the acquisition module is used for acquiring the gas values detected by each sensor node in the sub-network;
the determining module is further configured to determine whether a sensing hole exists in the sub-network according to each gas value;
the determining module is specifically configured to connect sensor nodes on an outermost layer in the subnetwork to form a polygon; and determining the gravity center of the polygon as the gravity center of the sub-network.
8. An electronic device, comprising: a memory and a processor;
the memory is used for storing program instructions;
the processor is configured to invoke program instructions in the memory to perform the method of detecting a perceptual hole as defined in any one of claims 1 to 6.
9. A computer readable storage medium, wherein computer program instructions are stored in the computer readable storage medium, which when executed, implement the method of detecting a perceptual hole as defined in any one of claims 1 to 6.
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