JP2011069637A - Shape estimation system, server device, method and program for estimating shape - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a shape estimation system for estimating shape information to be detected from information relating to a detection target detected by a sensor node of which position has not been located. <P>SOLUTION: The shape estimation system includes a plurality of sensor nodes and a server device. Each of the plurality of sensor nodes includes: a sensor part for detecting presence or absence of detection targets within a plurality of predetermined sensing areas; and a first communication part for transmitting the detection result by the sensor part to the server device. The plurality of sensor nodes include a plurality of types of sensor nodes having different setting conditions of the plurality of sensing areas. The server device includes: a second communication part for receiving detection results transmitted from the plurality of sensor nodes; and a processing part for calculating an estimation value of shape information relating to the shape of the detection target, based on the detection results received from the plurality of sensor nodes, information on the plurality of sensing areas of the plurality of sensor nodes, and information on average density of the plurality of sensing areas. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a shape estimation system, a server device, a shape estimation method, and a shape estimation that estimate shape information that is information about a shape such as a circumference and size of a detection target from detection results of each sensor node in a sensor network. Regarding the program.

  Many small sensor nodes with wireless communication functions (network devices that have sensors and communication functions) are distributed in various locations to form sensor networks, measure the status of various locations, and use the measurement results in various applications. There have been many attempts to use it (for example, Non-Patent Documents 1 and 2). Under such circumstances, it is considered to determine the type of the detection target based on the size and shape estimation of the detection target and the estimated information. For example, the size or shape of a vehicle entering a certain area is estimated, and the type of vehicle as a detection target is determined based on the estimated information.

I. F. Akyildiz, W.M. Su, Y .; Sankarasuburamaniam, and E.I. Cayirci, “A Survey on Sensor Networks”, IEEE Communications Magazine, 40, 8, pp. 191 102-114, 2002. Ben W. Cook, Steven Lanzisera, and Kristofer S. J. et al. Pister, “SoC Issues for RF Smart Dust”, Proceedings of the IEEE, 94, 6, pp. 1177-1196, June 2006.

  In the sensor network as described above, when a sensor node is provided at each determined position, it takes time and effort to grasp the position when the sensor node is installed. In addition, after each sensor node is appropriately deployed, the position of the sensor node is autonomously specified and registered by GPS (Global Positioning System) attached to the sensor node, etc., GPS is required for each sensor node. Additional costs are incurred. In a sensor network, since it is considered that a very large number of sensor nodes may be used, in such a case, it is desirable to be able to use them without designing or registering the positions of individual sensor nodes. .

  The present invention has been made in view of such circumstances, and a shape estimation system and server capable of estimating shape information of a detection target from information related to the detection target detected by a sensor node whose position is not specified An object is to provide a device, a shape estimation method, and a shape estimation program.

  The present invention has been made to solve the above-described problem, and the invention according to claim 1 is a shape estimation system including a plurality of sensor nodes and a server device, and each of the plurality of sensor nodes includes: A sensor unit that detects presence / absence of a detection target in a plurality of predetermined sensing areas, and a first communication unit that transmits a detection result by the sensor unit to the server device. The sensor node includes a plurality of types of sensor nodes having different setting conditions for the plurality of predetermined sensing areas, and the server device receives the detection result transmitted from the plurality of sensor nodes. Communication unit, the detection results received from the plurality of sensor nodes, and the predetermined plurality of sensings of the plurality of sensor nodes. A shape estimation system comprising: a processing unit that calculates an estimated value of shape information related to the shape of the detection target based on information related to the area and information related to an average density of the plurality of sensing areas. It is.

  The invention according to claim 2 is related to the plurality of predetermined sensing areas of the plurality of sensor nodes, wherein the processing unit totals the detection results for each type of the sensor node. The shape estimation system according to claim 1, wherein an estimated value of shape information related to the shape of the detection target is calculated using information and information related to an average density of the plurality of sensing areas.

  The invention according to claim 3 is characterized in that the sensor section is composed of two binary sensors arranged with a predetermined distance. It is a shape estimation system.

  According to a fourth aspect of the present invention, the server device stores in advance information related to the sensing area and information related to the average density in association with identification information that identifies the type of the sensor node, The first communication unit included in each of the plurality of sensor nodes identifies the type of the own sensor node together with the detection result when transmitting the detection result by the sensor unit to the server device. The processing unit included in the server device transmits the identification information to be transmitted to the server device, and the processing unit provided in the server device matches the identification information stored in the storage unit with the identification information received from the first communication unit. Information related to the area and information related to the average density are read from the storage unit, and the information related to the read sensing area 4. The estimated value of the shape information related to the shape of the detection target is calculated based on the information related to the average density and the received detection result. 5. This is a shape estimation system.

  The invention according to claim 5 is a sensor unit that detects the presence or absence of a detection target in a plurality of predetermined sensing areas, and a first communication unit that transmits a detection result by the sensor unit to a server device. Each of the server devices in a shape estimation system including a plurality of types of sensor nodes having different setting conditions for the plurality of predetermined sensing areas and a server device, each of which is transmitted from the plurality of sensor nodes. A second communication unit that receives the detection results; the detection results received from the plurality of sensor nodes; information about the plurality of predetermined sensing areas of the plurality of sensor nodes; A process for calculating an estimated value of shape information related to the shape of the detection object using information related to an average density of the sensing area A server apparatus, characterized in that it comprises and.

  The invention described in claim 6 includes a sensor unit that detects the presence or absence of a detection target in a plurality of predetermined sensing areas, and a communication unit that transmits a detection result of the sensor unit to a server device. A shape estimation method in a shape estimation system comprising a plurality of types of sensor nodes having different setting conditions for the plurality of predetermined sensing areas and the server device, wherein the server device includes the plurality of sensors. A communication process for receiving the detection results transmitted from a node; the detection results received from the plurality of sensor nodes; information on the plurality of predetermined sensing areas of the plurality of sensor nodes; Based on the information on the average density of the sensing area, the estimation of the shape information on the shape of the detection object is performed. A shape estimating method characterized by comprising a process of calculating the value.

  The invention described in claim 7 includes a sensor unit that detects the presence or absence of a detection target in a plurality of predetermined sensing areas, and a communication unit that transmits a detection result of the sensor unit to a server device. A shape estimation program in the server device of a shape estimation system comprising a plurality of types of sensor nodes having different setting conditions for the plurality of predetermined sensing areas, and the server device, wherein the plurality of sensor nodes A communication process for receiving the detection results transmitted from the plurality of sensor nodes; the detection results received from the plurality of sensor nodes; information about the plurality of predetermined sensing areas of the plurality of sensor nodes; Shape information on the shape of the detection object based on information on the average density of the sensing area A shape estimating program for executing a process of calculating the estimated value to the computer.

  According to the present invention, each sensor node has a plurality of sensing areas, the sensor node types are set to a plurality of types having different setting conditions of the sensing area, and the detection result received from the plurality of sensor nodes in the sensor data server; Based on information on a plurality of predetermined sensing areas of a plurality of sensor nodes and information on an average density of the plurality of sensing areas, an estimated value of the shape information on the shape of the detection target is calculated. Therefore, without designing and deploying the position of each sensor node, and without specifying the sensor node position using a position sensor node such as GPS, the shape information of each object is specified for the object. Can be calculated.

It is a top view which shows the structural example of the sensor node in one Embodiment of the shape estimation system of this invention. It is a system diagram which shows the structural example of one Embodiment of the shape estimation system of this invention. It is a graph which shows the simulation result of one Embodiment of the shape estimation system of this invention.

  Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a plan view showing a configuration example of a sensor node in an embodiment of the shape estimation system of the present invention. FIG. 2 is a system diagram showing a configuration example of an embodiment of the shape estimation system of the present invention.

  The sensor node shown in FIG. 1 is configured as a composite sensor node (that is, a sensor node having a plurality of sensors) 1_j in which a plurality of (in this case, two) sensors 11a and 11b are arranged in a predetermined shape. Yes. In the shape estimation system 100 of the present invention, as shown in FIG. 2, multiple types (type j) of composite sensor nodes 1_j (with different arrangement shapes of the sensors 11a and 11b (that is, setting conditions of the sensing areas 12a and 12b)) are used. In FIG. 2, a plurality of 1_1 to 1_3) are arranged together.

  The composite sensor node 1_j includes sensors 11a and 11b, a CPU (central processing unit) 13, a wireless communication device 14, a power supply circuit (not shown), and the like. Further, the pair of sensors 11a and 11b constitutes a sensor unit that detects the presence or absence of a detection target in a plurality of predetermined sensing areas 12a and 12b.

  The sensor 11a is a binary sensor that detects whether or not a detection target exists in the sensing area 12a, that is, the presence or absence of the detection target. The sensor 11b is the same sensor as the sensor 11a, and is a binary sensor that detects the presence or absence of a detection target in the sensing area 12b. The sensing area 12a is a circular area having a radius r_j determined in advance for each type j of the composite sensor node 1_j from the center 121a of the sensing area 12a. However, although the sensing area 12a is circular in plan, it is a spherical, hemispherical, or generally spherical area in three dimensions. Similarly to the sensing area 12a, the sensing area 12b is a circular area having a radius r_j determined in advance for each type j of the composite sensor node 1_j from the center 121b of the sensing area 12b. The inter-sensor distance l_j between the center 121a and the center 121b is set to a predetermined length for each type j of the composite sensor node 1_j.

  The CPU 13 processes the detection results of the sensors 11a and 11b, and controls the wireless communication device 14 based on the processing results. The wireless communication device 14 transmits the detection results of the sensors 11a and 11b to the center data server (server device) 2 (see FIG. 2) by wireless communication at regular intervals. Using this communication, the composite sensor node 1_j sends 2-bit sensing data representing the sensing results I_2 (t) and I_1 (t) at the same time to the sensor data server 2 at each time t. It is transmitted together with its own type number (own type number) j indicating the type of the node 1_j. The sensing result I_2 (t) is “1” when the detection target is detected by the two sensors 11a and 11b, and “0” otherwise. The sensing result I_1 (t) is “1” when only one of the sensors 11a or 11b is detected, and “0” otherwise.

  As described above, in this embodiment, the composite sensor node 1_j of type j includes two binary sensors 11a and 11b having circular sensing areas (sensing area radius r_j) at both ends of a line segment having a length l_j. (J = 1,..., J_c). As a result, from the composite sensor node 1_j, the detection information is detected by both of the two sensors 11a and 11b, the case where only one is detected, and the case where neither is detected, the ternary information is obtained. Can be obtained.

  On the other hand, the shape estimation system 100 shown in FIG. 2 includes composite sensor nodes 1_1 to 1_3 and a sensor data server 2 that communicates with the composite sensor nodes 1_1 to 1_3. The composite sensor nodes 1_1 to 1_3 in FIG. 2 correspond to the composite sensor node 1_j (j = 1 to 3) described with reference to FIG. 1 (however, there are three types of composite sensor node 1_j). .

  The sensor data server 2 includes a communication unit 21 and a processing unit 22. The communication unit 21 performs wireless communication with the composite sensor nodes 1_1 to 1_3, and outputs information representing the sensing results received from the composite sensor nodes 1_1 to 1_3 to the processing unit 22. The processing unit 22 controls the communication unit 21 and performs predetermined processing using the sensing results from the composite sensor nodes 1_1 to 1_3 input from the communication unit 21, and relates to the shape such as the circumference and size of the detection target. The shape information which is information is estimated. Although details will be described later, the processing unit 22 aggregates the detection results received from the plurality of sensor nodes 1_1 to 1_3 for each type of the plurality of sensor nodes 1_1 to 1_3, and the aggregation result and the plurality of sensor nodes 1_1 to 1_3. Using the information related to the sensing area and the information related to the average density of the plurality of sensing areas, a process of calculating estimated values of shape information related to the shapes of the plurality of detection objects is executed. The processing unit 22 includes a computer, a memory, other peripheral devices, and the like, and by executing a program stored in the memory, predetermined processing such as control of the communication unit 21, shape information is calculated, and the like is calculated. I do.

  The number of types and the number of the composite sensor nodes 1_1 to 1_3 illustrated in FIG. 2 are examples, and the present embodiment is not limited to this. Further, the objects 3_1, 3_2, and 3_3 illustrated in FIG. 2 are three types of detection objects having different shapes, and are the detection objects of the composite sensor nodes 1_1 to 1_3. However, the number and number of types (shapes) of the objects 3_1, 3_2, and 3_3 are also examples. The objects 3_1, 3_2, and 3_3 are not limited to tangible objects (tangible objects), and may be intangible objects such as sound, aroma, electricity, light, and heat.

  Next, the operation of the shape estimation system 100 in FIG. 2 will be described. Here, as an example, it is assumed that the shape information of the objects 3_1, 3_2, and 3_3 estimated by the processing unit 22 is the size of the radius when the objects 3_1, 3_2, and 3_3 are circular. That is, in the following description, it is generalized and expressed by the shape estimation system 100 in FIG. 2, and n_T circular objects 3_1, 3_2, 3_3,..., 3_ {n_T} = 1,..., N_T) is estimated.

  Further, it is assumed that the category of the objects 3_1, 3_2, 3_3,..., 3_ {n_T} is a circle and the number of objects n_T is known. In this embodiment, it is assumed that J_c type (kind) of composite sensor nodes 1_j (j = 1,..., J_c) are used. Each of these types of composite sensor node 1_j is randomly set within the detection target range so that the average density d_j (j = 1,..., J_c) is a predetermined value for each type of the sensing areas 12a and 12b. It is assumed that many are dispersed, that is, they are arranged in a distributed manner. Here, the average density d_j is the sum of the areas (or volumes) of the sensing areas 12a and 12b of the sensors 11a and 11b of the composite sensor node 1_j of each type j in the observation region (all regions to be observed). On the other hand, it is the rate of creaking.

  The center data server 2 holds in advance the parameters (average density d_j, inter-sensor distance l_j, sensing area radius r_j, j = 1,..., J_c) of each type of composite sensor node 1_j in the storage unit. This storage unit is, for example, a storage unit provided in the center data server 2. Then, the data is received from each composite sensor node 1_j, and the center data server 2 calculates the sum of the sensing results I_1 (t) and the sum of the sensing results I_2 (t) at each time t for each type. . The sum of the sensing results I_1 (t) of type j and the sum of the sensing results I_2 (t) is set as N_ {1, j} (t) and N_ {2, j} (t). At a certain time, the time average of N_ {1, j} (t) and N_ {2, j} (t) is calculated. This time average is set as K_ {1, j} and K_ {2, j}. The center data server 2 holds an expression of the following form for the “object category circle” in advance.

  First and second equations: For two types j1, j2 suitable (for example, having the largest sensing area radius r_j1 and the smallest sensing area radius r_j2),

  Here, K_ {1, j1} and K_ {2, j1} are the sum N_ of the sensing results I_1 (t) and I_2 (t) at a certain time based on the detection result of the composite sensor node 1_j1 of type j1. Each time average of {1, j1} (t) and N_ {2, j1} (t). K_ {1, j2} and K_ {2, j2} are the sum N_ {1, sensing results I_1 (t) and I_2 (t) at a certain time based on the detection result of the composite sensor node 1_j2 of type j2. Each time average of j2} (t) and N_ {2, j2} (t). d_j1 is the average density of the composite sensor node 1_j1, and d_j2 is the average density of the composite sensor node 1_j2. r_j1 and r_j2 are the sensing area radii of the composite sensor nodes 1_j1 and 1_j2. R_1, ..., R_ {n_T} are the radii of the objects 3_1, ..., 3_ {n_T}.

  For the third to Jc equations: type j = 1,..., Jc-2 (each type 1,..., Jc minus types j1 and j2),

  However, f_1 (x) represents “1” when x is true and “0” otherwise. r (i, j) = min (R_i, r_j) (that is, a function that takes the smaller variable of R_i and r_j).

  Then, the values obtained from the detection results are input to the above K_ {1, j} and K_ {2, j}, and the simultaneous nonlinear equations are solved with respect to the unknown R_i (i = 1,..., N_T). Obtain an estimate of the object radius R_i.

  The first and second equations are

  That is, it is obtained by calculation of the integral geometry that the left side “expected value of the number of object detection sensors” is equal to the right side “(sensor density 2d_j) × Σi {radius r_j1 (or r_j2) + R_i circle area}”. It is based on. That is, instead of the expected value E [•] obtained by calculation of integral geometry, measured values K_ {1, j1} + 2K_ {2, j1}, K_ {1, j2} + 2K_ {2, j2} are used. It is.

  Similarly, for other equations, it can be derived from the calculation of geometric integration that the expected value of the left side “the number of composite sensor nodes in which both sensors detect the object” is the right side. Therefore, the left side is replaced with an actual measurement value instead of an expected value.

  If the object is not a circle but a rectangle with two sides a_i and b_i (i = 1,..., N_T), the nonlinear simultaneous equations can be rewritten as follows.

  First and second equations: For two types j1, j2 suitable (for example, having the largest sensing area radius r_j1 and the smallest sensing area radius r_j2),

  Here, a_1,..., A_ {n_T} are the lengths of each side of the rectangular object i (i = 1,..., N_T). b_1,..., b_ {n_T} are the lengths of the other sides of the rectangular object i (i = 1,..., n_T).

  The third to Jc equations: using a report on detection results from the composite sensor node 1_j of types j = 1,..., Jc-2 (each type 1,..., Jc minus types j1 and j2),

  However, α (i, j) = min (a_i + 2r_j, b_i + 2r_j) and β (i, j) = max (a_i + 2r_j, b_i + 2r_j).

  As described above, according to the present embodiment, parameters (size, circumference, etc.) for each target object can be estimated for the plurality of detection target objects under the following conditions. That is, it is possible to estimate without designing and deploying the position of each sensor and without specifying the sensor position using a position sensor such as GPS. Each sensor is a binary sensor, and can only report whether there is any object in the sensing area. According to this, since parameter estimation for a plurality of detection objects can be realized with a simple binary sensor without the sensor design and position detection function, it is economical and versatile.

  In the present embodiment, each sensor node is a composite sensor node having a plurality of sensors, and a plurality of detection conditions are set by setting a plurality of types (multiple types) of sensing area setting conditions for the plurality of sensors. Shape information about the object can be estimated. If a single type of sensor node having only one sensor is used, the size and circumference of each sensor are detected only by information about whether or not each sensor has detected an object, without the position information of each sensor. Can be estimated, but a plurality of objects cannot be handled.

  The embodiment of the present invention is not limited to the above. For example, the sensor data server 2 in FIG. 2 performs data processing for a plurality of observation areas, or a plurality of sensor data servers 2 are provided for communication. It is possible to appropriately make changes such as performing processing in a shared manner via a network. In addition, the individual shape information of the detection target is not limited to the radius when the detection target is circular as described above, and the length of each side when the detection target is rectangular, but also other areas such as area and outer peripheral length It may be a thing. Further, the sensors 12a and 12b do not need to be arranged or mounted in the same housing or the same substrate of the composite sensor node 1_j, and one or both of the sensors 12a and 12b may be in a housing or a substrate different from the CPU 13. It may be provided above. In that case, the sensors 12a and 12b and the CPU 13 can be connected by wired or wireless control lines, signal lines or communication lines. In addition, it is not always necessary to use the independent sensors 11a and 11b for the sensing area 12a and the sensing area 12b. For example, a configuration in which two or more sensing areas can be set for one sensor is combined. It is also possible to detect the presence or absence of an object in the two sensing areas in a time division manner.

  The relative relationship in the observation region between the composite sensor node 1_j and the object 3_i (i = 1, 2,...) Is that the object 3_i moves while the composite sensor node 1_j is fixed. The composite sensor node 1_j may move, and the object 3_i may be fixed, or may be a combination thereof. Further, the composite sensor node 1_j and the sensor data server 2 can be configured using a computer and a program executed by the computer. In this case, part or all of the program is recorded in a computer-readable record. It can be provided via a medium or a communication line.

  Next, a simulation result of the shape information estimation process using this embodiment will be described. Computer simulation was performed under the following conditions. FIG. 3 shows estimated values (indicated by “^” in the figure) of the circle radii R_1 to R_4 of the object obtained by changing the setting conditions to the setting numbers 1 to 5 in five ways. In setting numbers 1 to 5, five types of simulations are performed by changing the setting of the inter-sensor distance l_j and the sensing area radius r_j. Conditions (1) to (10) common to the settings and changed setting conditions (11a) to (11e) are as follows.

  (1) Simulation time: 20000, (2) Observation region: 20000.00 × 100.00, (3) Average density of composite sensor node 1_j: d_j = 0.5 (for all j), (4) Composite sensor Number of sensors constituting the node: 2, (5) Sensing area shape: circle, (6) Generation interval of the object: 1000.00, (7) Moving speed of the object: 1.00, (8) Object Type: 4, (9) Number of objects: 4, (10) Shape of object: Circle (radius: R_1 = 25, R_2 = 10, R_3 = 5, R_4 = 3), (11a) Used with setting number 1 (Inter-sensor distance l_j, sensing area radius r_j) = (30, 1), (20, 1), (10, 1), (11b) of the composite sensor node (l_j, r_j) = (30, 5) , (20, 5), (10, 5), (11c) (l_j, r_j) = (20, 1), (20, 5), (11d) setting number 4 of the composite sensor node used in setting number 3 (L_j, r_j) = (30,1), (20,1), (20,5), (11e) of the composite sensor node used in (1) = (l_j, r_j) = of the composite sensor node used in setting number 5 (30, 5), (20, 1), (20, 5).

  The number of composite sensor nodes 1_j for each type j varies (calculated) depending on the area of the observation region, the average density d_j of the composite sensor node 1_j, and the area of the sensing area (sensing area radius r_j). ing).

From this simulation result, according to this embodiment, it is possible to design a plurality of sensor nodes without designing the positions of individual sensor nodes and specifying the sensor node position using a position sensor node such as GPS. The estimated value of the shape information of each target object can be calculated for the target object.
In addition, assuming that each sensor node includes a plurality of binary sensors and only reports whether there is any object in the sensing area, it is possible to simply estimate the shape information for the plurality of objects. Since such a binary sensor can be realized without the sensor node design and deployment and the position detection function, it is economical and versatile.
In the above description, the case of detecting a plurality of objects having a two-dimensional spread has been described. Similarly, it is also possible to detect a plurality of objects having a three-dimensional spread.

  Further, the program for realizing the function of the sensor data server 2 in FIG. 1 is recorded on a computer-readable recording medium, and the program recorded on the recording medium is read into a computer system and executed, thereby executing sensor data. The function of the server 2 may be executed. Here, the “computer system” includes an OS and hardware such as peripheral devices.

Further, the “computer system” includes a homepage providing environment (or display environment) if a WWW system is used.
The “computer-readable recording medium” refers to a storage device such as a flexible medium, a magneto-optical disk, a portable medium such as a ROM and a CD-ROM, and a hard disk incorporated in a computer system. Furthermore, the “computer-readable recording medium” dynamically holds a program for a short time like a communication line when transmitting a program via a network such as the Internet or a communication line such as a telephone line. In this case, a volatile memory in a computer system serving as a server or a client in that case, and a program that holds a program for a certain period of time are also included. The program may be a program for realizing a part of the functions described above, and may be a program capable of realizing the functions described above in combination with a program already recorded in a computer system.

1_j, 1_1, 1_2, 1_3 Composite sensor node 2 Sensor data server 3_1, 3_2, 3_3 Object 11a, 11b Sensor (binary sensor)
12a, 12b Sensing area 13 CPU
14 Wireless communication device r_j Radius of sensing area l_j Distance between sensors

Claims (7)

A shape estimation system comprising a plurality of sensor nodes and a server device,
Each of the plurality of sensor nodes is
A sensor unit for detecting the presence or absence of a detection object in a plurality of predetermined sensing areas;
A first communication unit that transmits a detection result by the sensor unit to the server device;
Have
The plurality of sensor nodes are composed of a plurality of types of sensor nodes having different setting conditions for the plurality of predetermined sensing areas,
The server device
A second communication unit that receives the detection results transmitted from the plurality of sensor nodes;
The detection based on the detection results received from the plurality of sensor nodes, information on the plurality of predetermined sensing areas of the plurality of sensor nodes, and information on an average density of the plurality of sensing areas. A shape estimation system comprising: a processing unit that calculates an estimated value of shape information related to the shape of an object. The processing unit is
The detection results are aggregated for each type of sensor node, the aggregation results, information on the plurality of predetermined sensing areas of the plurality of sensor nodes, and information on an average density of the plurality of sensing areas; The shape estimation system according to claim 1, wherein an estimated value of shape information related to the shape of the detection target is calculated using the method. The shape estimation system according to claim 1, wherein the sensor unit includes two binary sensors arranged with a predetermined distance. The server device
A storage unit that stores information related to the sensing area and information related to the average density in advance in association with identification information that identifies the type of the sensor node;
With
The first communication unit included in each of the plurality of sensor nodes includes:
When transmitting the detection result by the sensor unit to the server device, the identification information for identifying the type of the own sensor node is transmitted to the server device together with the detection result,
The processing unit included in the server device includes:
The information on the sensing area and the information on the average density, in which the identification information stored in the storage unit matches the identification information received from the first communication unit, are read from the storage unit and read The estimated value of the shape information related to the shape of the detection object is calculated based on the information related to the sensing area, the information related to the average density, and the received detection result. The shape estimation system according to any one of claims. A sensor unit that detects the presence or absence of a detection target in a plurality of predetermined sensing areas; and a first communication unit that transmits a detection result of the sensor unit to a server device. A server device in a shape estimation system comprising a plurality of types of sensor nodes having different setting conditions for a plurality of sensing areas, and a server device,
A second communication unit that receives the detection results transmitted from the plurality of sensor nodes;
Using the detection results received from the plurality of sensor nodes, information on the plurality of predetermined sensing areas of the plurality of sensor nodes, and information on an average density of the plurality of sensing areas, the detection target And a processing unit that calculates an estimated value of shape information related to the shape of the object. Each of the plurality of predetermined units includes a sensor unit that detects presence / absence of a detection target in a plurality of predetermined sensing areas, and a communication unit that transmits a detection result of the sensor unit to a server device. A shape estimation method in a shape estimation system comprising a plurality of types of sensor nodes having different sensing area setting conditions, and the server device,
The server device is
A communication process for receiving the detection results transmitted from the plurality of sensor nodes;
The detection based on the detection results received from the plurality of sensor nodes, information on the plurality of predetermined sensing areas of the plurality of sensor nodes, and information on an average density of the plurality of sensing areas. And a process for calculating an estimated value of shape information related to the shape of the object. Each of the plurality of predetermined units includes a sensor unit that detects presence / absence of a detection target in a plurality of predetermined sensing areas, and a communication unit that transmits a detection result of the sensor unit to a server device. A shape estimation program in the server device of a shape estimation system comprising a plurality of types of sensor nodes having different sensing area setting conditions, and the server device,
A communication process for receiving the detection results transmitted from the plurality of sensor nodes;
The detection based on the detection results received from the plurality of sensor nodes, information on the plurality of predetermined sensing areas of the plurality of sensor nodes, and information on an average density of the plurality of sensing areas. A shape estimation program for causing a computer to execute a process of calculating an estimated value of shape information related to the shape of an object.

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