CN102014147A - Positioning system in Internet of things as well as deploying method and device thereof - Google Patents

Abstract

The invention discloses a positioning system in the Internet of Things and its deployment method and device. The method includes determining the coverage of the electronic landmarks; determining the deployment density of the electronic landmarks according to the coverage of the electronic landmarks; and deploying the electronic landmarks according to the deployment density of the electronic landmarks. The invention also discloses a device, which includes a coverage determination module for determining the coverage of electronic landmarks; a deployment density determination module for determining the deployment density of electronic landmarks according to the coverage of electronic landmarks; a deployment module for determining the deployment density of electronic landmarks according to the coverage of electronic landmarks The deployment density of electronic landmarks is used to deploy electronic landmarks. The invention also discloses a positioning system, comprising: a wireless gateway, a landmark management server and an electronic landmark node deployed according to the above method. Aiming at the characteristics of huge number of items in the Internet of Things, wide circulation fields, and frequent location changes, the present invention constructs a global item positioning system to realize high-precision and low-cost positioning of items worldwide.

Description

Positioning system in internet of things and deployment method and device thereof

technical field

The present invention relates to the technical field of the Internet of Things, in particular to a positioning system in the Internet of Things and its deployment method and device.

Background technique

The Internet of Things uses information sensing equipment such as radio frequency identification, infrared sensors, global positioning systems, and laser scanners to connect any item with the Internet for information exchange and communication with the help of existing wired and wireless communication protocols. A network for intelligent identification, positioning, tracking, monitoring and management. At present, the Internet of Things has been widely used in the fields of intelligent transportation, environmental monitoring, logistics tracking and positioning, etc. However, all these applications are inseparable from the support of the geographic location information of the item, so how to locate the item and obtain the geographic location of the item Information has become an important direction of IoT research.

In the prior art, there have been some researches related to item positioning, but these studies focus on item positioning algorithms. In addition, the positioning of items is limited to the industry and does not have a large scale. Only when the application of the Internet of Things has a scale can the sharing and use of a large amount of item information become possible.

In the process of realizing the present invention, the inventor finds that there are at least the following problems in the prior art:

In view of the characteristics of the huge number of items in the Internet of Things, wide circulation areas, and frequent location changes, it is necessary to build a global item positioning system to achieve high-precision and low-cost positioning of items worldwide.

Contents of the invention

In order to build a global item positioning system and realize high-precision and low-cost positioning of items worldwide, an embodiment of the present invention provides a deployment method of a positioning system in the Internet of Things, and the method includes:

Determine coverage of electronic landmarks;

determining the deployment density of the electronic landmarks according to the coverage of the electronic landmarks;

The electronic landmarks are deployed according to the deployment density of the electronic landmarks.

The embodiment of the present invention also provides a device for deploying a positioning system in the Internet of Things, and the device includes:

a coverage determination module, configured to determine the coverage of the electronic landmark;

a deployment density determination module, configured to determine the deployment density of the electronic landmarks according to the coverage of the electronic landmarks;

A deployment module, configured to deploy the electronic landmarks according to the deployment density of the electronic landmarks.

An embodiment of the present invention also provides a positioning system in the Internet of Things, wherein the system includes: a wireless gateway, a landmark management server, and an electronic landmark node deployed according to the above method.

The beneficial effect brought by the technical solution provided by the embodiment of the present invention is: by determining the coverage of the electronic landmark; determining the deployment density of the electronic landmark according to the coverage of the electronic landmark, finally realizing the deployment of the positioning system in the Internet of Things, and then realizing It enables high-precision, low-cost positioning of items around the world.

Description of drawings

Fig. 1 is the method flowchart provided in the embodiment 1 of the present invention;

Fig. 2 is a flow chart of the method provided in Embodiment 2 of the present invention;

Fig. 3 is a flow chart of the method provided in Embodiment 3 of the present invention;

Fig. 4 is a flow chart of a method for determining coverage of electronic landmarks according to weights in Embodiment 4 of the present invention;

Figure 5 is a schematic structural view of the device provided in Embodiment 5 of the present invention;

Detailed ways

In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

Example 1

As shown in Figure 1, the present invention provides a deployment method of a positioning system in the Internet of Things, the method comprising the following steps:

S101: Determine the coverage of the electronic landmark;

S102: Determine the deployment density of the electronic landmarks according to the coverage of the electronic landmarks;

S103: Deploy the electronic landmarks according to the deployment density of the electronic landmarks.

The method provided in this embodiment, by determining the coverage of electronic landmarks; determining the deployment density of electronic landmarks according to the coverage of electronic landmarks, finally realizes the deployment of positioning systems in the Internet of Things, thereby realizing high-precision, Low cost positioning.

The present invention provides a device for deploying a positioning system in the Internet of Things, the device comprising:

a coverage determination module, configured to determine the coverage of the electronic landmark;

a deployment density determination module, configured to determine the deployment density of the electronic landmarks according to the coverage of the electronic landmarks;

A deployment module, configured to deploy the electronic landmarks according to the deployment density of the electronic landmarks.

The present invention provides a positioning system in the Internet of Things, which includes: a wireless gateway, a landmark management server and electronic landmark nodes deployed according to the above method. The landmark management server is an indoor landmark management server, and the electronic landmark node is an indoor electronic landmark node; or the landmark management server is an outdoor landmark management server, and the electronic landmark node is an outdoor electronic landmark node.

Example 2

As shown in Figure 2, taking the indoor positioning system in the Internet of Things as an example, the positioning system in the indoor Internet of Things is composed of indoor electronic landmark nodes, wireless gateways and indoor landmark management servers deployed indoors by different organizations, institutions and individuals. The indoor electronic landmark is an intelligent terminal that stores landmark information, that is, the geographic location information of the electronic landmark, and has wireless communication capabilities. The indoor electronic landmark node sends landmark information to the area within its communication range at regular intervals, and the item can calculate its own position according to the landmark information from different landmarks. Indoor electronic landmarks are deployed indoors at a certain density to achieve multiple landmark information coverage in indoor areas, that is, any location in the room can receive landmark information sent from multiple electronic landmarks. After the item receives landmark information from different indoor electronic landmarks, it can locate its own position through existing positioning algorithms such as TOA (Time of Arriving, Time of Arrival Algorithm), TDOA (Time Difference Of Arrival, Time Difference of Arrival Algorithm), preferably Yes, the item receives at least three landmark information from different indoor electronic landmarks. The indoor electronic landmark communicates with the indoor landmark management server through the wireless gateway. Preferably, the indoor electronic landmark can form an ad hoc (multi-hop mobile wireless network) network with other wireless terminals such as mobile phones and readers. When the electronic landmark is far away from the wireless gateway, the mobile phone in its ad hoc network can , The reader is connected to the wireless gateway, thereby improving the connection effect between the indoor electronic landmark and the wireless gateway. The indoor landmark management server receives information from indoor electronic landmarks, discovers and reports faulty electronic landmark nodes in time, and maintains the normal operation of the indoor electronic landmark system.

The deployment method of the positioning system in the indoor Internet of Things specifically includes:

S201: Determine the coverage of the electronic landmark;

Specifically, for any indoor position P ₀ , P ₀ can be covered by h different landmark signals, and h is the coverage of the electronic landmark. Wherein, the communication radius of the landmark is R ₀ . If any indoor position P ₀ is abstracted as a point, then at least h electronic landmarks should be deployed in a circle with point P ₀ as the center and R ₀ as the radius, and the preferred coverage h of electronic landmarks is greater than or equal to 3.

确定电子地标的部署密度；S202: According to

Determine the deployment density of electronic landmarks;

即

因此，满足h重覆盖的室内电子地标系统，电子地标的部署密度向上取整，至少为个/平方米。Among them, R ₀ is the communication radius of the electronic landmark, h is the coverage of the electronic landmark, and n ₀ is the deployment density of the electronic landmark. Specifically, if the electronic landmarks are evenly deployed, and the deployment density of the electronic landmarks is n ₀ per square meter, then

Right now

Therefore, for an indoor electronic landmark system that satisfies h-fold coverage, the deployment density of electronic landmarks is rounded up, at least piece/square meter.

S203: Deploy the electronic landmarks according to the deployment density of the electronic landmarks.

Specifically, the deployment density of electronic landmarks is adjusted according to the circulation of goods in different areas in the positioning system. Since the landmark signal is covered by a circle centered on the electronic landmark, and the farther the physical object is from the electronic landmark, the weaker the signal is. Therefore, for areas with a large number of physical circulation, in order to ensure that all physical objects can receive stronger landmark signals, More electronic landmarks need to be deployed to enhance the signal strength of the landmarks. In addition, for areas with a large amount of physical circulation, more accurate item location information is required to more accurately locate the physical object among a large number of physical objects, which requires multiple coverage of landmark signals. Therefore, the value of h can take different values according to the quantity of physical objects in circulation. For example, for ordinary households, the preferred h=3 can meet the requirements of physical location. For factories or shopping malls with a large amount of physical circulation, h can take a larger value. Meet the needs of a large number of item positioning.

In this embodiment, the deployment density of electronic landmarks is set according to the circulation of indoor items, so as to realize the coverage of multiple electronic landmark information in indoor areas. Therefore, the items in the room can calculate their position information with high precision.

Example 3

As shown in Figure 3, taking the outdoor positioning system in the Internet of Things as an example, the outdoor positioning system in the Internet of Things is composed of outdoor electronic landmark nodes and public landmark management servers. An outdoor electronic landmark is an intelligent terminal that stores landmark information, that is, the geographic location information of the electronic landmark, and has wireless communication capabilities. The outdoor electronic landmark node sends landmark information to the area within the communication radius at regular intervals, and the item can calculate its own position according to the received landmark information from different landmarks. In cities, the circulation area of outdoor items is mainly roads. Therefore, outdoor electronic landmarks are arranged at a certain density on both sides of the roads in the city to achieve multiple landmark information coverage for any position in the road, that is, any position in the road can receive information from Landmark information of multiple electronic landmarks. After the item receives landmark information from different outdoor electronic landmarks, it can locate its own position through existing positioning algorithms such as TOA and TDOA. Among them, the landmark information received by the item from different outdoor electronic landmarks is at least three . The outdoor electronic landmark communicates with the public landmark management server through the wireless gateway. Preferably, the outdoor electronic landmark can form an ad hoc network with other wireless terminals such as mobile phones and readers. connection, thereby improving the connection effect between the outdoor electronic landmark and the wireless gateway. Every once in a while, the outdoor electronic landmark reports its working status to the public landmark management server. The public landmark management server receives information from outdoor electronic landmarks, discovers and reports faulty electronic landmark nodes in time, and maintains the normal operation of the outdoor electronic landmark system.

If the road in the positioning system is abstracted as an edge, the starting point, end point and turning point of the road are abstracted as vertices, an undirected graph G(V, E) is composed of edges and vertices, where V represents the set of vertices in the graph, and E represents The set of edges in the figure, N is the number of vertices in the figure, as shown in Figure 2, the deployment method of the outdoor positioning system in the Internet of Things specifically includes:

S301: Determine the weight of the road in the positioning system, and determine the coverage of the electronic landmark according to the weight;

确定定位系统中道路的权值，e_ij表示顶点i和j之间边的长度，w_ij为长度为e_ij的边的权值，

为边e_ij的度中心性，

为边e_ij的邻近中心性，

为边e_ij的介数中心性，

为边e_ij的聚集中心性，

为边e_ij的直线中心性，

为边e_ij的信息中心性。Among them, determining the weight value of the road in the positioning system specifically includes: according to

Determine the weight of the road in the positioning system, e _ij represents the length of the edge between vertices i and j, w _ij is the weight of the edge whose length is e _ij ,

is the degree centrality of edge e _ij ,

is the proximity centrality of edge e _ij ,

is the betweenness centrality of edge e _ij ,

is the aggregation centrality of edge e _ij ,

is the straight-line centrality of side e _ij ,

is the information centrality of edge e _ij .

定义为

用于表示边e_ij实际具有的邻边数，即e_ij两顶点所连接的边数之和与e_ij可能具有的邻边数的比值。边的度中心性越大，说明图中较多的边可直接与该边相连，因此，该边在整个图中处于较为中心的位置。例如，边e_ij的两个顶点为i和j，

表示顶点i所连接的边数，

表示顶点j所连接的边数，

(e_ik+e_jk)表示边e_ij的两个顶点所实际连接的边数和。而在理想情况下，边e_ij最多可以连接2(N-2)条边，即顶点i可连接(N-2)条边，顶点j也可连接(N-2)条边，因为顶点i或j可以与图中除去i和j的N-2个顶点相连接。这个公式是不考虑边e_ij的，因为

中没有考虑边e_ij，2(N-2)中也没有考虑边e_ij，所有的边在计算度中心性时都不考虑自身的边，则对所有的边都是公平的。Degree centrality of edge e _ij

defined as

It is used to indicate the number of adjacent sides that edge e _ij actually has, that is, the ratio of the sum of the number of sides connected by two vertices of e _ij to the number of possible adjacent sides that e _ij may have. The greater the degree centrality of an edge, the more edges in the graph can be directly connected to the edge, so the edge is in a relatively central position in the entire graph. For example, the two vertices of edge e _ij are i and j,

Indicates the number of edges connected to vertex i,

Indicates the number of edges connected to vertex j,

(e _ik +e _jk ) represents the sum of the number of edges actually connected by the two vertices of edge e _ij . In an ideal situation, edge e _ij can connect up to 2 (N-2) edges, that is, vertex i can connect (N-2) edges, and vertex j can also connect (N-2) edges, because vertex i Or j can be connected with N-2 vertices except i and j in the graph. This formula does not consider the side e _ij , because

The edge e _ij is not considered in , and the edge e _ij is not considered in 2(N-2). All edges do not consider their own edges when calculating degree centrality, so it is fair to all edges.

定义为

表示网络的总边数与边e_ij到网络中其它边的最短距离之和的比值。其中，两条边的最短距离定义为从一条边到另一条边所要经过的最少的边数，若两条边相邻，则这两条边的的最短距离为2，

表示边e_ij与边e_pq的最短距离。边的邻近中心性越大，说明该边与其它边的最短距离越小，即从网络中的任意位置到达该边越方便，因此，该边在整个网络中处于较为中心的位置，其中，两条边的最短距离定义为从一条边到另一条边所要经过的最少的边数，若两条边相邻，则这两条边的的最短距离为2，

表示边e_ij与边e_pq的最短距离，表示边e_ij与网络中所有其他边的最短距离之和。Proximity centrality of edge e _ij

defined as

Indicates the ratio of the total number of edges in the network to the sum of the shortest distances from edge e _ij to other edges in the network. Among them, the shortest distance between two sides is defined as the minimum number of sides to pass from one side to another side. If two sides are adjacent, the shortest distance between these two sides is 2.

Indicates the shortest distance between edge e _ij and edge e _pq . The greater the proximity centrality of an edge, the smaller the shortest distance between this edge and other edges, that is, the more convenient it is to reach this edge from any position in the network. Therefore, this edge is in a relatively central position in the entire network, and the two The shortest distance between two sides is defined as the minimum number of sides to pass from one side to another side. If two sides are adjacent, the shortest distance between these two sides is 2.

Indicates the shortest distance between side e _ij and side e _pq , Indicates the sum of the shortest distances between edge e _ij and all other edges in the network.

定义为表示边e_ij出现在所有节点间的最短路径上的概率。其中，n_pq表示顶点p与q之间的最短路径数，m_pq(e_ij)表示顶点p与q之间的最短路径中经过边e_ij的最短路径数。边的介数中心性越大，表示该边存在于较多的最短路径中，因此承载的实物流量也较大，该边处于较为中心的位置，n_pq表示顶点p与q之间的最短路径数。例如，网络中有1，2，3，4四个顶点，那么从1到4的最短路径数可能有多条，比如从1直接到4，也可能从2直接到4。m_pq(e_ij)表示顶点p与q之间的最短路径中经过边e_ij的最短路径数，例如p与q之间有多条最短路径，但可能有些经过边e_ij，有些不经过边e_ij。m_pq(e_ij)/n_pq表示p与q之间的最短路径中经过边e_ij的概率。

网络中任意一对顶点间的最短路径经过边e_ij的概率之和。然而，网络中共有N(N-1)/2对顶点，因此

除以N(N-1)/2表示网络中平均每对顶点的最短路径经过边e_ij的概率。Betweenness centrality of edge e _ij

defined as Indicates the probability that edge e _ij appears on the shortest path between all nodes. Among them, n _pq represents the number of shortest paths between vertices p and q, and m _pq (e _ij ) represents the number of shortest paths passing through edge e _ij among the shortest paths between vertices p and q. The greater the betweenness centrality of an edge, it means that the edge exists in more shortest paths, so the material flow it carries is also larger, and the edge is in a relatively central position, and n _pq represents the shortest path between vertices p and q number. For example, if there are four vertices 1, 2, 3, and 4 in the network, there may be multiple shortest paths from 1 to 4, such as from 1 to 4 directly, or from 2 to 4 directly. m _pq (e _ij ) indicates the number of shortest paths passing through edge e _ij in the shortest path between vertices p and q, for example, there are multiple shortest paths between p and q, but some may pass through edge e _ij and some may not pass through edge e _ij . m _pq (e _ij )/n _pq represents the probability of passing through edge e _ij in the shortest path between p and q.

The sum of the probabilities that the shortest path between any pair of vertices in the network passes through the edge e _ij . However, there are N(N-1)/2 pairs of vertices in the network, so

Dividing by N(N-1)/2 represents the probability that the shortest path of each pair of vertices in the network passes through the edge e _ij .

定义为

表示顶点i和j所有邻节点间实际存在的边数与可能具有的最大边数的比值。其中，k_ij表示顶点i与顶点j具有的邻节点的总数，EN_ij表示顶点i与j的邻节点间存在的边数。边的聚集中心性越大，表示顶点i和j的所有邻节点彼此相连的概率较低，因此，需要较多的邻边直接连接到该边，以保证城市路网的连通性，所以，该边处于较为中心的位置；若某个顶点s与顶点i间有边，则s为i的邻节点。k_ij表示顶点i与顶点j具有的邻节点的总数，k_ij个邻节点互联，最多具有k_ij(k_ij-1)/2条边，EN_ij表示顶点i与j的邻节点间实际存在的边数。

表示顶点i和j所有邻节点间实际存在的边数EN_ij与可能具有的最大边数k_ij(k_ij-1)/2的比值。Aggregation centrality of edge e _ij

defined as

Indicates the ratio of the actual number of edges between all adjacent nodes of vertices i and j to the maximum possible number of edges. Among them, k _ij represents the total number of adjacent nodes of vertex i and vertex j, and EN _ij represents the number of edges existing between the adjacent nodes of vertex i and j. The greater the aggregation centrality of an edge, the lower the probability that all adjacent nodes of vertices i and j are connected to each other. Therefore, more adjacent edges need to be directly connected to this edge to ensure the connectivity of the urban road network. Therefore, the The edge is in a relatively central position; if there is an edge between a vertex s and a vertex i, then s is a neighboring node of i. k _ij represents the total number of neighbor nodes between vertex i and vertex j, k _ij neighbor nodes are interconnected, and there are at most k _ij (k _ij -1)/2 edges, EN _ij represents the actual existence between the neighbor nodes of vertex i and j the number of sides.

Indicates the ratio of the actual number of edges EN _ij between all adjacent nodes of vertices i and j to the maximum possible number of edges k _ij (k _ij -1)/2.

定义为

表示顶点i与j到达网络中其他顶点的欧式距离与顶点i与j到达网络中其他顶点的最短路径的长度之比。其中，表示顶点i与k沿直线的欧氏距离，欧式距离表示两顶点间的直线距离，l_ik表示顶点i与k的最短路径长度，当路是直的时候，其路径长度为两顶点的欧式距离，当路是弯的时候，则计算路径长度了。边的直线中心性表示了边上的两顶点到达其他顶点的最短路径偏离直线的程度。边的直线中心性越大，表示到达该边越为快速、便利，因此该边的地理位置越为重要。具体的，

表示顶点i到达网络中其他N-1个顶点的欧式距离与顶点i到达网络中其他N-1个顶点的最短路径的长度之比，对他们求和。

良示顶点j到达网络中其他N-1个顶点的欧式距离与顶点j到达网络中其他N-1个顶点的最短路径的长度之比，对他们求和。之所以除以2(N-1)，是因为对上述这两个和求平均值，因为

是N-1个比值相加，

也是N-1个比值相加除以N-1，即得到均值。Straight line centrality of edge e _ij

defined as

Indicates the ratio of the Euclidean distance between vertices i and j to reach other vertices in the network and the length of the shortest path between vertices i and j to reach other vertices in the network. in, Represents the Euclidean distance between vertices i and k along the straight line, Euclidean distance represents the straight-line distance between two vertices, l _ik represents the shortest path length between vertices i and k, when the road is straight, its path length is the Euclidean distance between two vertices , when the road is curved, the path length is calculated. The straight-line centrality of an edge indicates the degree to which the shortest paths from two vertices on an edge to other vertices deviate from a straight line. The greater the linear centrality of an edge, the faster and more convenient it is to reach the edge, so the geographical location of the edge is more important. specific,

Indicates the ratio of the Euclidean distance from vertex i to other N-1 vertices in the network to the length of the shortest path from vertex i to other N-1 vertices in the network, and sums them.

Show the ratio of the Euclidean distance from vertex j to other N-1 vertices in the network and the length of the shortest path from vertex j to other N-1 vertices in the network, and sum them. The reason for dividing by 2(N-1) is because the above two sums are averaged, because

is the addition of N-1 ratios,

It is also the sum of N-1 ratios and divided by N-1, which is the mean value.

定义为

表示删除边e_ij后，图中所有边的直线中心性的变化。其中，

G’表示删除边e_ij后的图，若删除边e_ij后，顶点p与q间不可达，则定义

边的信息中心性越大，则表示删除该边后，会造成不可达的顶点对较多或顶点间的最短路径长度增加较多，导致路网不完全连接或延时较长，因此，该边在整个路网中较为重要。

表示顶点p与q间的欧式距离，l_pq表示顶点p与q的最短路径长度，

表示网络中任意两个顶点间的欧式距离与这两个顶点间的最短路径的长度之比，对他们求和。因为共对N(N-1)/2对顶点求和，所以除以N(N-1)/2，得到任意两个顶点间的欧式距离与这两个顶点间的最短路径的长度之比的均值。E[G]-E[G’]表示网络中删除边e_ij后，任意两个顶点间的欧式距离与这两个顶点间的最短路径的长度之比的均值的变化，即减少了多少，除以E[G]表示变化率，即在E[G]的基础上减少了多少。Information centrality of edge e _ij

defined as

Indicates the change of the straight line centrality of all edges in the graph after deleting edge e _ij . in,

G' represents the graph after deleting the edge e _ij , if after deleting the edge e _ij , the vertex p and q are not reachable, then define

The greater the information centrality of an edge, it means that after deleting the edge, there will be more unreachable vertex pairs or the length of the shortest path between vertices will increase more, resulting in incomplete connection of the road network or longer delay. Therefore, the Edges are more important in the entire road network.

Indicates the Euclidean distance between vertices p and q, l _pq indicates the shortest path length between vertices p and q,

Indicates the ratio of the Euclidean distance between any two vertices in the network to the length of the shortest path between these two vertices, and sums them. Because a total of N(N-1)/2 pairs of vertices are summed, divide by N(N-1)/2 to get the ratio of the Euclidean distance between any two vertices to the length of the shortest path between these two vertices mean value. E[G]-E[G'] indicates the change in the mean value of the ratio of the Euclidean distance between any two vertices to the length of the shortest path between the two vertices after deleting the edge e _ij in the network, that is, how much it has decreased, Divided by E[G] to indicate the rate of change, that is, how much is reduced on the basis of E[G].

Wherein, as shown in Figure 4, determining the coverage of the electronic landmark according to the weight specifically includes the following steps:

S3011: Determine the coverage H(e _max ) of the side with the maximum weight in the positioning system;

Specifically, e _max is the edge with the largest weight, the coverage of e _max is H(e _max ), and the preset H(e _max ) is 3. According to the method of S302, the deployment density of electronic landmarks is calculated, and on the edge e _max Deploy electronic landmark nodes on the corresponding road Road _max to realize H(e _max ) re-coverage of the side;

S3012: Deploy physical objects on Road _max and test whether the H(e _max ) re-covered landmark system can meet the requirements of physical location. If yes, execute S3015, otherwise execute S3013;

S3013: H(e _max )←H(e _max )+1, that is, add one to the preset value of H(e _max ), deploy an electronic landmark node on the road according to the method of S302, and realize the H(e max ) of the road (e _max ) heavy coverage;

S3014: When testing H(e _max )←H(e _max )+1, whether the landmark system can meet the requirements of physical positioning, if yes, execute S3015; if not, execute S3013, through repeated tests until Determine the optimal coverage H(e _max ) of the road with the maximum weight;

S3015: For any edge, if e _ij ≠0, calculate the coverage H(e _ij )=(H(e _max )w _ij ) _/ w _max of edge e ij . Among them, w _max is the weight value of the side corresponding to Road _max , that is, the maximum weight value in the road, H(e _max ) is the coverage degree of the road with the largest weight value, w _ij is the starting point i is the end point or j is the starting point i is the weight of the road at the end point, H(e _ij ) is the electronic landmark coverage of the road with i as the starting point and j as the end point or j as the starting point and i as the end point. Specifically, the density of deploying electronic landmarks is determined according to the edge weights, that is, the larger the edge weights, the greater the deployment density, and the smaller the edge weights, the lower the deployment density, and the density of deploying electronic landmarks increases year-on-year with the edge weights.

确定电子地标的部署密度，其中(R₁＞L/2)，n为电子地标的部署密度；S302: Determine the communication radius _R1 of the electronic landmark and the width L of the road, according to

Determine the deployment density of the electronic landmarks, where (R ₁ > L/2), n is the deployment density of the electronic landmarks;

因此，

由于0≤r≤L，可以通过求导计算得出当r＝0时，|C₁C₂|+|C₃C₄|取最小值，最小值为

因此，

即在道路的两侧部署电子地标的密度向上取整，为

For example, if the intersection points of circle O and both sides of the road are C ₁ , C ₂ , C ₃ , and C ₄ respectively, then at least H(e _ij ) electrons are deployed between |C ₁ C ₂ | and |C ₃ C ₄ | landmark node. Among them, |C ₁ C ₂ | indicates the length of the section between C ₁ and C ₂ on one side of the road, and |C ₃ C ₄ | indicates the length of the section between C ₃ and C ₄ on the other side of the road. Suppose the distance from P ₁ to C ₁ and the road where C ₂ is located is r, then the distance from P ₁ to C ₃ and the road where C ₄ is located is Lr, therefore,

therefore,

Since 0≤r≤L, it can be calculated by derivation that when r=0, |C ₁ C ₂ |+|C ₃ C ₄ | takes the minimum value, and the minimum value is

therefore,

That is, the density of electronic landmarks deployed on both sides of the road is rounded up, which is

S303: Realize deploying the electronic landmarks according to the deployment density of the electronic landmarks.

The electronic landmark deployment method provided in this example calculates the centrality of roads in the city according to the structure of the road network in the city, and deploys electronic landmarks at different densities for roads with different centralities, which can meet the positioning requirements of objects on different roads. Therefore, the multi-coverage outdoor electronic landmark deployment method can enable items to calculate their own position information with high precision.

Example 4

As shown in FIG. 5, this embodiment provides a device for deploying a positioning system in the Internet of Things, which includes:

A coverage determination module 401, configured to determine the coverage of the electronic landmark;

Wherein, when the circulation of goods in each area of the system is balanced, preferably, the coverage of the electronic landmark is greater than or equal to 3;

When the circulation of goods in each area of the system is unbalanced, the coverage determination module 401 also includes:

A weight determination unit 4011, configured to determine the weight of the road in the positioning system;

确定定位系统中道路的权值，其中将定位系统中的道路抽象为边，道路的起点、终点以及转折点抽象为顶点，由边和顶点组成一个无向图，N为图中顶点的个数，e_ij表示顶点i和j之间边的长度，w_ij为长度为e_ij的边的权值，

为边e_ij的度中心性，为边e_ij的邻近中心性，

为边e_ij的介数中心性，为边e_ij的聚集中心性，

为边e_ij的直线中心性，

为边e_ij的信息中心性。Specifically, the weight determination unit 4011 is specifically configured to: according to

Determine the weight of the road in the positioning system, where the road in the positioning system is abstracted as an edge, the starting point, end point and turning point of the road are abstracted as vertices, an undirected graph is composed of edges and vertices, N is the number of vertices in the graph, e _ij represents the length of the edge between vertices i and j, w _ij is the weight of the edge whose length is e _ij ,

is the degree centrality of edge e _ij , is the proximity centrality of edge e _ij ,

is the betweenness centrality of edge e _ij , is the aggregation centrality of edge e _ij ,

is the straight-line centrality of side e _ij ,

is the information centrality of edge e _ij .

Wherein, the weight determination unit 4011 specifically includes:

确定边e_ij的度中心性；degree centrality subunit 40111 for

Determine the degree centrality of the edge e _ij ;

确定边e_ij的邻近中心性；Proximity centrality subunit 40112 for

Determine the proximity centrality of edges e _ij ;

确定边e_ij的介数中心性；betweenness centrality subunit 40113 for use according to

Determine the betweenness centrality of edges e _ij ;

Aggregation centrality subunit 40114, for according to Determine the aggregation centrality of edges e _ij ;

边e_ij的直线中心性，其中，

表示顶点i与k之间的直线距离，l_ik表示顶点i与k的最短路径长度；Straight line centrality subunit 40115 for use according to

The straight line centrality of edge e _ij , where,

Represents the straight-line distance between vertices i and k, l _ik represents the shortest path length between vertices i and k;

确定边e_ij的信息中心性，其中，

G′表示删除边e_ij后的无向图，

表示顶点p与q之间的直线距离，l_pq表示顶点p与q之间的最短路径长度。Information centrality subunit 40116 for

Determine the information centrality of edges e _ij , where,

G′ represents the undirected graph after deleting the edge e _ij ,

Indicates the straight-line distance between vertices p and q, and l _pq indicates the shortest path length between vertices p and q.

The coverage determination unit 4012 is configured to determine the coverage of the electronic landmark according to the weight.

Specifically, the coverage determination unit specifically includes:

The maximum road coverage determination subunit 40121 is used to determine the coverage of the road with the maximum weight in the positioning system, H(e _max );

The electronic landmark coverage determination subunit 40122 is used to determine the electronic landmark coverage according to H(e _ij )=(H(e _max )w _ij )/w _max ; wherein, w _max is the maximum weight, H(e _max ) is the coverage of the road with the largest weight, w _ij is the weight of the road starting from i and ending at j or j as the starting point and i is the end point, H(e _ij ) is the road starting from i and ending at j or j is Coverage of the electronic landmarks of the road whose starting point i is the ending point.

A deployment density determination module 402, configured to determine the deployment density of the electronic landmarks according to the coverage of the electronic landmarks;

确定所述电子地标的部署密度；其中，R₀为电子地标的通信半径，h为电子地标的覆盖度，n₀为电子地标的部署密度。Among them, when the circulation of goods in each area in the system is balanced, the deployment density determination module 402 is specifically used to: according to

Determine the deployment density of the electronic landmarks; wherein, R ₀ is the communication radius of the electronic landmarks, h is the coverage of the electronic landmarks, and n ₀ is the deployment density of the electronic landmarks.

When the circulation of goods in each area of the system is balanced, the deployment density determination module 402 specifically includes:

The parameter determining unit 4021 is configured to determine the communication radius R ₁ of the electronic landmark and the width L of the road.

确定电子地标的部署密度，其中(R₁＞L/2)，n为电子地标的部署密度。The deployment density determination unit 4022 of the electronic landmark is used for

Determine the deployment density of the electronic landmarks, where (R ₁ >L/2), n is the deployment density of the electronic landmarks.

The deployment module 403 is configured to deploy the electronic landmarks according to the deployment density of the electronic landmarks.

The deployment device provided in this embodiment determines the deployment density of the electronic landmarks according to the coverage of the electronic landmarks by determining the coverage of the electronic landmarks; finally realizes the deployment of the positioning system in the Internet of Things, and then realizes the high-speed distribution of items worldwide. Accurate, low-cost positioning.

The deployment device provided in this example deploys electronic landmarks according to the circulation of items in the system, which meets the needs of positioning items in areas with different circulation in the system, and realizes multiple coverage of the system by electronic landmarks, thus enabling The item calculates its own position information with high precision.

The system provided in this embodiment belongs to the same idea as the method embodiment, and its specific implementation process is detailed in the method embodiment, and will not be repeated here.

The system provided in this embodiment, by determining the coverage of electronic landmarks; determining the deployment density of electronic landmarks according to the coverage of electronic landmarks, finally realizes the deployment of positioning systems in the Internet of Things, thereby realizing high-precision, Low-cost positioning. At the same time, the system can self-monitor and maintain the normal operation of the landmark system. At the same time, items only need to be equipped with cheap electronic tags to complete their real-time positioning through indoor or outdoor electronic landmark systems.

All or part of the technical solutions provided by the above embodiments can be realized by software programming, and the software program is stored in a readable storage medium, such as a hard disk, an optical disk or a floppy disk in a computer.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection of the present invention. within range.

Claims (20)

1. A deployment method of a positioning system in the Internet of Things, characterized in that the method comprises: Determine coverage of electronic landmarks; determining the deployment density of the electronic landmarks according to the coverage of the electronic landmarks; The electronic landmarks are deployed according to the deployment density of the electronic landmarks. 2. The method according to claim 1, wherein the determining the deployment density of the electronic landmarks according to the coverage of the electronic landmarks specifically comprises: according to

determining a deployment density of the electronic landmarks; Among them, R ₀ is the communication radius of the electronic landmark, h is the coverage of the electronic landmark, and n ₀ is the deployment density of the electronic landmark. 3. The method according to claim 1 or 2, wherein the coverage of the electronic landmark is greater than or equal to 3. 4. according to the described method of claim 1 or 2, it is characterized in that, described method also comprises: The deployment density of the electronic landmarks is adjusted according to the circulation of goods in different areas in the positioning system. 5. The method according to claim 1, wherein said determining the coverage of the electronic landmark specifically comprises: Determine the weight of the road in the positioning system; According to the weight, the coverage of the electronic landmark is determined. 6. The method according to claim 5, wherein the determining the weight of the road in the positioning system specifically comprises: according to

Determine the weight of the road in the positioning system, wherein the road in the positioning system is abstracted as an edge, the starting point, end point and turning point of the road are abstracted as vertices, an undirected graph is formed by the edges and the vertices, and N is a graph The number of vertices described in , e _ij represents the length of the edge between vertices i and j, w _ij is the weight of the edge with length e _ij , σ _pq is the centrality of all roads in the system The proximity centrality of

is the betweenness centrality of edge e _ij ,

is the aggregation centrality of edge e _ij ,

is the straight-line centrality of side e _ij ,

is the information centrality of edge e _ij . 7. The method according to claim 6, wherein the

is the degree centrality of edge e _ij , is the proximity centrality of edge e _ij ,

is the betweenness centrality of edge e _ij , is the aggregation centrality of edge e _ij ,

is the straight-line centrality of side e _ij ,

The information centrality of edge e _ij is specifically:

Centrality, m _pq (e _ij ) indicates the number of shortest paths passing through edge e _ij in the shortest path between vertices p and q; according to

Determine the aggregation centrality of edge e _ij , EN _ij represents the number of edges existing between the adjacent nodes of vertex i and j; according to

Determine the straight line centrality of edge e _ij , where, Represents the straight-line distance between vertices i and k, l _ik represents the shortest path length between vertices i and k; according to Determine the information centrality of edges e _ij , where,

Indicates the mean value of the ratio of the Euclidean distance between any two vertices to the length of the shortest path between these two vertices, G' represents the undirected graph after deleting the edge e _ij , E[G'] represents the undirected graph after deleting the edge e _ij The mean value of the ratio of the Euclidean distance between any two vertices in the directed graph to the length of the shortest path between these two vertices, Indicates the straight-line distance between vertices p and q, and l _pq indicates the shortest path length between vertices p and q. 8. The method according to claim 5, wherein, according to the weight, determining the coverage of the electronic landmark comprises: Determining the coverage of the road with the maximum weight in the positioning system, H(e _max ); Determine the coverage of the electronic landmark according to H(e _ij )=(H(e _max )w _ij )/w _max ; Among them, w _max is the maximum weight, H(e _max ) is the coverage of the road with the maximum weight, w _ij is the weight of the road with i as the starting point and j as the end point or j as the starting point and i as the end point, H(e _ij ) is the coverage of the electronic landmark on the road with i as the starting point and j as the end point or j as the starting point and i as the end point. 9. The method according to claim 8, wherein the determining the deployment density of the electronic landmarks according to the coverage of the electronic landmarks comprises: determining the communication radius _R1 of the electronic landmark and the width L of the road; according to

Determining the deployment density of the electronic landmarks, where (R ₁ >L/2), n is the deployment density of the electronic landmarks. 10. A device for deploying a positioning system in the Internet of Things, characterized in that the device comprises: a coverage determination module, configured to determine the coverage of the electronic landmark; a deployment density determination module, configured to determine the deployment density of the electronic landmarks according to the coverage of the electronic landmarks; A deployment module, configured to deploy the electronic landmarks according to the deployment density of the electronic landmarks. 11. The device according to claim 10, wherein the deployment density determination module is specifically used for: according to

determining a deployment density of the electronic landmarks; Among them, R ₀ is the communication radius of the electronic landmark, h is the coverage of the electronic landmark, and n ₀ is the deployment density of the electronic landmark. 12. The device according to claim 10 or 11, wherein the coverage of the electronic landmark is greater than or equal to 3. 13. The device according to claim 10 or 11, wherein the device further comprises: An adjustment module, configured to adjust the deployment density of the electronic landmarks according to the circulation of goods in different areas in the positioning system. 14. The device according to claim 10, wherein the coverage determination module specifically comprises: a weight determination unit, configured to determine the weight of the road in the positioning system; The coverage determination unit is configured to determine the coverage of the electronic landmark according to the weight. 15. The device according to claim 14, wherein the weight determination unit is specifically configured to: according to

Determine the weight of the road in the positioning system, wherein the road in the positioning system is abstracted as an edge, the starting point, end point and turning point of the road are abstracted as vertices, an undirected graph is formed by the edges and the vertices, and N is a graph The number of vertices described in , e _ij represents the length of the edge between vertices i and j, w _ij is the weight of the edge with length e _ij , σ _pq is the centrality of all roads in the system

Proximity centrality of e _ij ,

is the betweenness centrality of edge e _ij ,

is the aggregation centrality of edge e _ij , is the straight-line centrality of side e _ij ,

is the information centrality of edge e _ij . 16. The device according to claim 15, wherein the weight determining unit specifically comprises: degree centrality subunit for

determining the degree centrality of said edge e _ij ;

Centrality, m _pq (e _ij ) indicates the number of shortest paths passing through edge e _ij in the shortest path between vertices p and q; Aggregate centrality subunits for Determine the aggregation centrality of edge e _ij , EN _ij represents the number of edges existing between the adjacent nodes of vertex i and j; The line centrality subunit is used according to

Determine the straight line centrality of edge e _ij , where,

Represents the straight-line distance between vertices i and k, l _ik represents the shortest path length between vertices i and k; Information centrality sub-unit, used according to

Determine the information centrality of edges e _ij , where,

Indicates the mean value of the ratio of the Euclidean distance between any two vertices to the length of the shortest path between these two vertices, G' represents the undirected graph after deleting the edge e _ij , E[G'] represents the undirected graph after deleting the edge e _ij The mean value of the ratio of the Euclidean distance between any two vertices in the directed graph to the length of the shortest path between these two vertices,

Indicates the straight-line distance between vertices p and q, and l _pq indicates the shortest path length between vertices p and q. 17. The method according to claim 14, wherein the coverage determining unit specifically comprises: The coverage determination subunit of the maximum road is used to determine the coverage of the road with the maximum weight in the positioning system, H(e _max ); The coverage determination subunit of the electronic landmark is used to determine the coverage of the electronic landmark according to H(e _ij )=(H(e _max )w _ij )/w _max ; Among them, w _max is the maximum weight, H(e _max ) is the coverage of the road with the maximum weight, w _ij is the weight of the road with i as the starting point and j as the end point or j as the starting point and i as the end point, H(e _ij ) is the coverage of the electronic landmark on the road with i as the starting point and j as the end point or j as the starting point and i as the end point. 18. The device according to claim 17, wherein the deployment density determination module specifically comprises: a parameter determination unit, configured to determine the communication radius _R1 of the electronic landmark and the width L of the road; Deployment density of electronic landmarks determines the unit for use according to

Determining the deployment density of the electronic landmarks, where (R ₁ >L/2), n is the deployment density of the electronic landmarks. 19. A positioning system in the Internet of Things, characterized in that the system comprises: a wireless gateway, a landmark management server, and an electronic landmark node deployed according to the method of claim 1. 20. The system according to claim 19, wherein the landmark management server is an indoor landmark management server, and the electronic landmark node is an indoor electronic landmark node; or the landmark management server is an outdoor landmark management server, and the The electronic landmark node is an outdoor electronic landmark node.

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