JP2018165899A - Sensor node arrangement system and sensor node arrangement method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a sensor node arrangement system capable of drastically reducing a load on an arranger to arrange sensor nodes when the sensor nodes are arranged in a house where a resident to be watched lives.SOLUTION: A sensor node arrangement system 1 for discriminating necessity of arrangement of multiple sensor nodes 11 to be arranged in a house where a resident to be watched lives includes: the sensor nodes 11 for transmitting sensor information obtained by measuring watching information and communication environment information obtained by measuring a communication environment state; a management server 12 for discriminating a sensor node that is not necessary to be arranged so as to output it as an unnecessary sensor node among the multiple sensor nodes 11 on the basis of sensor information and communication environment information respectively transmitted from the multiple sensor nodes 11 arranged in a house; and an unnecessary sensor node display device 13 for displaying an unnecessary sensor node output from the management server 12.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a sensor node installation system and a sensor node installation method, and more particularly to a sensor node installation system and a sensor node installation that support the installation of a sensor node that grasps the status of residents to be monitored in a monitoring system in an appropriate place. Regarding the method.

  In recent years, the elderly living alone has increased rapidly. In order for a family living away from the elderly to check the health status of the elderly, it is generally necessary to visit the elderly's residence or call the elderly. is there. However, frequent visits to senior citizens' homes are a time and financial burden for families. In addition, it is difficult to reliably check the health status of elderly people by phone alone. Furthermore, if the elderly person does not answer the phone when the elderly person is absent, the family will feel extra anxiety.

  In order to reduce the burden on the family like this, it is conceivable to arrange an emergency call device or a device for notifying the family of health, etc. in the elderly's residence. However, in the case of such a device, the elderly person's own operation is required, and the health condition of the elderly person cannot be properly grasped due to forgetting the operation or the like. Therefore, in recent years, development of a watching system for appropriately grasping the health condition of the elderly has been eagerly advanced.

  As a monitoring system in the current technology, for example, a method of measuring the amount of activity of a resident with a sensor arranged in the residence has been proposed in order to grasp the health condition of the resident who is to be monitored. Here, the sensor is usually configured as a device integrated with a module or the like for transmitting information. The device is called a sensor node.

  However, in order to properly install the sensor nodes constituting such a monitoring system in the residence where the inhabited residents live, the direction of the directional sensor, such as the human sensor or the illuminance sensor, It is necessary to consider the presence or absence of obstacles around the sensor node, the shape of the residence, etc. In the case of a sensor node that performs wireless communication, it is also necessary to consider the wireless characteristics to prevent communication failure It is necessary, and a person having specialized knowledge is required as an installer who installs the sensor node.

  In view of the problem of the monitoring system in the current technology as described above, a sensor node installation system that supports the installation of a sensor node at an appropriate installation location has been proposed.

  For example, in Japanese Patent Application Laid-Open No. 2009-282642 “Monitoring Area Setting Device” of Patent Document 1, a plan view of a house and an area indicating sensor characteristics (for example, a human sensor detection area) are overlapped. Thus, there has been proposed a technique for providing a user interface that allows an appropriate installation location to be easily determined without drawing expertise. Further, in Japanese Patent Application Laid-Open No. 2015-35806, “Method and System for Selecting Position and Orientation of Surveillance Camera” in Japanese Patent Laid-Open No. 2005-35806, a sensor node is automatically entered when a plan view of a residence and sensor characteristics are input. A technique has been proposed in which an appropriate installation location is automatically determined by repeating evaluation using an evaluation function while changing the position of the position.

  Further, in Japanese Patent Laid-Open No. 2013-31014 “Wireless Sensor Network and its Installation Method” of Patent Document 3, an arbitrary sensor node is temporarily installed, and the radio wave intensity of the temporarily installed sensor node is measured, whereby communication is performed. A technique has been proposed in which it is determined whether or not the installation position is appropriate from the viewpoint of the environment, and the installer is notified. A similar technique is also considered in which a sensor node is temporarily installed and a test is performed to determine whether surrounding obstacles or measurement by the sensor node is possible and notify the installer.

JP 2009-282644 A Japanese Patent Laying-Open No. 2015-35806 JP 2013-31014 A

  However, for example, in the current technology as described in Patent Document 1 and Patent Document 2, it is necessary to input an accurate plan view of a residence and sensor characteristics to a sensor node installation system. When a household is targeted, there is often no plan for the residence, and the installer who intends to install a sensor node in the residence will write down the plan of the residence when attempting to install it. There is a problem that the trouble of the becomes large. In addition, in the case of the current technology as described in Patent Document 3 and the current technology of performing a test by temporary setting of the sensor node, specialized knowledge is necessary to determine the optimum installation location, And it is necessary to repeat temporary installation and a test, changing an installation place, and there exists a problem that a burden of an installer becomes large.

  In addition, the monitoring system includes, for example, a sensor that monitors the human touch in the bathroom to monitor the fall of the residents to be watched and a human touch in the toilet to monitor urination behavior. It may be necessary to manage in which room type the node is installed. In the current technology, when the sensor node is installed, there is only a method in which the installer or the like writes down the room type in which the sensor node is installed. However, there is a problem that the method of leaving the record in the recording has a problem that a recording error occurs and takes time, so it is also important to incorporate a technique for automatically determining the room type in which the sensor node is installed as the sensor node installation system.

(Object of the present invention)
The present invention has been made in order to solve such problems, and when installing a sensor node in a residence where the inhabitant to be watched lives, the burden on the installer who installs the sensor node is greatly increased. It is an object of the present invention to provide a sensor node installation system and a sensor node installation method that can be easily reduced.

  In order to solve the above-described problems, the sensor node installation system and the sensor node installation method according to the present invention mainly adopt the following characteristic configuration.

(1) A sensor node installation system according to the present invention includes:
A sensor node installation system for determining whether or not it is necessary to install a plurality of sensor nodes to be installed in a residence where the inhabited residents live.
A sensor node that transmits sensor information that measures information for watching and communication environment information that measures the status of the communication environment; and
Based on the sensor information and the communication environment information transmitted from each of the plurality of sensor nodes installed in the residence, it is unnecessary to determine a sensor node that does not need to be installed from the plurality of sensor nodes. A management server that outputs as a sensor node;
And an unnecessary sensor node display device that displays the unnecessary sensor node output from the management server.

(2) The sensor node installation method according to the present invention includes:
A sensor node installation method for determining whether or not it is necessary to install a plurality of sensor nodes to be installed in a residence where the inhabited residents live.
Sensor node transmission step for transmitting sensor information for monitoring information and communication environment information for measuring the status of the communication environment from each of the plurality of installed sensor nodes;
A sensor information storage step for storing the sensor information and the communication environment information transmitted from each of the plurality of sensor nodes in the sensor node transmission step;
An unnecessary sensor node determining step of determining, as an unnecessary sensor node, a sensor node that does not need to be installed from among the plurality of sensor nodes based on the sensor information and the communication environment information stored in the sensor information storage step. It is characterized by having.

  According to the sensor node installation system and the sensor node installation method of the present invention, the following effects can be obtained.

  That is, according to the present invention, the burden on the installer who installs the sensor node can be greatly reduced when the sensor node is installed. The reason for this is that after installing a plurality of sensor nodes that monitor the situation of the residents in the residence where the inhabited residents live, sensors that do not need to be installed based on the sensor information and communication environment information transmitted from each sensor node This is because it has a mechanism that can automatically determine the node.

  Thus, when installing a sensor node, the installer does not need to create a plan view of the residence to be installed, and even in the case of a sensor node that performs wireless communication, repeated testing or communication failure due to temporary installation It is not necessary to have expertise such as wireless characteristics to prevent noise, and even when a directional sensor such as a human sensor or an illuminance sensor is used, It is also unnecessary to consider the presence of obstacles around the node, the shape of the residence, and the like.

It is a system configuration figure showing an example of the whole configuration of the sensor node installation system concerning a 1st embodiment of the present invention. It is explanatory drawing which shows an example of the sensor information and communication environment information which are accumulate | stored in the sensor information storage part in the management server shown in FIG. It is explanatory drawing which shows an example of the grouping information memorize | stored in the grouping information storage part in the management server shown in FIG. It is explanatory drawing which shows an example of the unnecessary sensor node discrimination rule memorize | stored in the unnecessary sensor node discrimination rule memory | storage part in the management server shown in FIG. It is a flowchart which shows an example of operation | movement of the sensor node installation system shown in FIG. It is a flowchart which shows an example of detailed operation | movement of the sensor node grouping means in the management server shown in FIG. It is explanatory drawing which shows an example of the result of having calculated the correlation function regarding the measured value of the human sensor in the combination of two sensor nodes in the sensor node grouping means in the management server shown in FIG. It is a flowchart which shows an example of detailed operation | movement of the unnecessary sensor node discrimination | determination means in the management server shown in FIG. It is explanatory drawing which shows an example of the evaluation result based on the unnecessary sensor node discrimination rule with respect to a sensor node in the unnecessary sensor node discrimination means in the management server shown in FIG. It is a system block diagram which shows an example of the whole structure of the sensor node installation system which concerns on the 2nd Embodiment of this invention. It is explanatory drawing which shows an example of the room classification discrimination rule memorize | stored in the room classification discrimination rule memory | storage part in the management server shown in FIG. It is a flowchart which shows an example of operation | movement of the sensor node installation system shown in FIG. It is a flowchart which shows an example of detailed operation | movement of the room classification discrimination means in the management server shown in FIG. It is a flowchart which shows the example different from FIG. 8 of the detailed operation | movement of the unnecessary sensor node discrimination | determination means in the management server shown in FIG. FIG. 2 is an explanatory diagram illustrating a result of calculating a correlation coefficient related to a measurement value of a human sensor in a combination of two sensor nodes installed in the same installation room in the unnecessary sensor node determination unit in the management server illustrated in FIG. 1. is there.

  Preferred embodiments of a sensor node installation system and a sensor node installation method according to the present invention will be described below with reference to the accompanying drawings. Note that the reference numerals in these drawings are added for convenience to the respective elements as an example for facilitating understanding, and it goes without saying that the present invention is not intended to be limited to the illustrated embodiments.

(Features of the present invention)
Prior to the description of the embodiments of the present invention, an outline of the features of the present invention will be described first. The present invention includes a plurality of sensor nodes that are installed at a plurality of locations that are assumed to be appropriate in a residence in which a resident to be watched resides, and that transmit sensor information and communication environment information measured by each, and the sensor node The transmitted sensor information and the communication environment information are received, and unnecessary sensor nodes are determined from the plurality of installed sensor nodes based on the received sensor information and communication environment information. A management server; and an unnecessary sensor node display device that displays unnecessary sensor nodes notified from the management server. Thus, the installer of the sensor node such as the inhabitant to be watched over or the person concerned with the inhabitant can easily grasp the unnecessary sensor node, and can greatly reduce the burden of installing the sensor node.

<First Embodiment>
Next, a sensor node installation system and a sensor node installation method according to the first embodiment of the present invention will be described in detail with reference to FIGS.

(Configuration example of the first embodiment)
First, a system configuration example of the sensor node installation system according to the first embodiment of the present invention will be described with reference to FIG. FIG. 1 is a system configuration diagram showing an example of the overall configuration of the sensor node installation system according to the first embodiment of the present invention. The sensor node installation system 1 of FIG. 1 installs a plurality of sensor nodes 11 constituting a monitoring system appropriately, and then, based on sensor information and communication environment information measured at each sensor node 11, By determining the installation effect, correlation, etc., and enabling automatic determination of unnecessary sensor nodes, there is a mechanism that can reduce the burden of sensor node installation.

  As shown in FIG. 1, the sensor node installation system 1 according to the first embodiment includes a sensor node 11, a management server 12, and an unnecessary sensor node display device 13. Here, at the time of installation, the sensor node 11 is installed in each of a plurality of places where installation is assumed to be appropriate according to the environmental conditions to be monitored by the monitoring system. Therefore, the sensor node installation system 1 has a plurality of sensor nodes 11.

  The sensor node 11 includes a sensor and a communication unit that form a monitoring system, and includes an arbitrary sensor 111, a communication environment sensor 112, and a transmission unit 113 as illustrated in FIG.

  Here, the arbitrary sensor 111 is a sensor that measures one or more kinds of information necessary for the monitoring system, that is, information necessary for watching the inhabitants to be monitored, and notifies the transmission unit 113 of the measured results as sensor information. For example, it is configured using a general human sensor, illuminance sensor, temperature sensor, or the like. In the following description, a case where the result of measurement using a human sensor for sensing the presence of a person to be watched as the arbitrary sensor 111 is described as sensor information to the transmission unit 113 will be described. May be used, or a plurality of types of sensors may be used in combination.

  The communication environment sensor 112 is a means for measuring the state of the communication environment between the sensor node 11 and the management server 12. For example, between the transmission means 113 on the sensor node 11 side and the reception means 121 on the management server 12 side. The radio field intensity in the communication, the number of transmission failures in the transmission unit 113 on the sensor node 11 side, and the like are measured, and the measurement result is notified to the transmission unit 113 as communication environment information.

  The transmission means 113 is a means for transmitting the sensor information received from the arbitrary sensor 111 and the communication environment information received from the communication environment sensor 112 to the reception means 121 on the management server 12 side, and is a wireless LAN (Local Area Network). Communication is performed using any communication medium such as wireless communication such as LTE or Long Term Evolution (LTE) or wired communication such as wired LAN.

  As shown in FIG. 1, the management server 12 includes a receiving unit 121, a sensor information storage unit 122, a sensor node grouping unit 123, a grouping information storage unit 124, an unnecessary sensor node determination unit 125, and an unnecessary sensor. And a node discrimination rule storage unit 126.

  Here, the receiving unit 121 is a unit that receives the sensor information and the communication environment information transmitted from the transmitting unit 113 on each sensor node 11 side and stores the sensor information and the communication environment information in the sensor information storage unit 122. Similar to the transmission unit 113, communication is performed using any communication medium such as wireless communication such as wireless LAN or LTE, or wired communication such as wired LAN.

  The sensor information storage unit 122 is a storage medium that stores sensor information and communication environment information of each sensor node 11 received by the receiving unit 121, and is configured by a hard disk or the like. Here, the sensor information storage unit 122 stores sensor information and communication environment information in a format as shown in FIG.

  FIG. 2 is an explanatory diagram illustrating an example of sensor information and communication environment information stored in the sensor information storage unit 122 in the management server 12 illustrated in FIG. 1, and illustrates an example of information sequentially stored in time series. ing. As shown in FIG. 2, the sensor information storage unit 122 includes a sensor node ID T101 for identifying each sensor node 11 that has transmitted sensor information and communication environment information, sensor information and communication environment by an arbitrary sensor 111 (human sensor or the like). A type T102 indicating the type of communication environment information by the sensor 112 (such as a radio wave intensity sensor), a measurement value T103 indicating the measurement result of the sensor information and the communication environment information, a measurement date and time T104 indicating the date and time when the sensor information and the communication environment information are measured, It is comprised from the information which contains at least.

  In the accumulation example of the sensor information accumulation unit 122 illustrated in FIG. 2, transmission is performed from each of the four sensor nodes 11 of the sensor node A, the sensor node B, the sensor node C, and the sensor node D as indicated by the sensor node ID T101. The sensor information and communication environment information that has been stored are accumulated. The sensor information measured at each sensor node 11 is a measurement result using a human sensor as shown in type T102, and the communication environment information measured at each sensor node 11 is a measurement result of radio wave intensity. The case is shown. In FIG. 2, as indicated by the type T <b> 102, the temperature information measured using the temperature sensor at each sensor node 11 is also transmitted from each sensor node 11 and accumulated in the sensor information accumulation unit 122. Examples are also shown for reference.

  Further, for example, as shown in the measurement date and time T104 in the sensor node A as shown in the first row (No. 1) to the third row (No. 3) of the accumulated data in FIG. As for the measurement value measured at 2017/2/1 17:01, as indicated by the measurement value T103, the measurement value of the human sensor is “0” indicating that it is not sensed, and the measurement value of the temperature sensor. Indicates that the temperature of the installed room is “20 degrees” and the measured value of the radio wave intensity is “−30 dBm”, which is a good communication environment.

  Next, returning to the description of each component of the management server 12 of FIG. 1, the sensor node grouping means 123 is a means for grouping (grouping) each installed sensor node 11 as a sensor node group for each room, Based on the correlation coefficient between the sensor information of each sensor node 11 acquired from the sensor information storage unit 122, it is determined whether or not the sensor node 11 is installed in the same room, and the sensor node determined as the same installation room 11 is grouped as a sensor node group, and the grouping result is stored in the grouping information storage unit 124 as grouping information.

  The grouping information storage unit 124 is a storage medium that stores grouping information regarding the sensor nodes 11 grouped for each room by the sensor node grouping unit 123, and includes a hard disk or the like. Here, the grouping information storage unit 124 stores the grouping information in a format as shown in FIG.

  FIG. 3 is an explanatory diagram showing an example of grouping information stored in the grouping information storage unit 124 in the management server 12 shown in FIG. 1, and shows the result of grouping the installed sensor nodes 11 for each room. An example of grouping information is shown. As illustrated in FIG. 3, the grouping information storage unit 124 includes information including at least a sensor node ID T201 that identifies each sensor node 11 and an installation room ID T202 that identifies a room in which the sensor node 11 is installed. Composed.

  In the example of the grouping information storage unit 124 illustrated in FIG. 3, four sensor nodes 11 of sensor node A, sensor node B, sensor node C, and sensor node D are installed as indicated by sensor node ID T201. Among the sensor nodes 11, three of the sensor node A, sensor node B, and sensor node D are shown installed in the same room A as shown in the installation room ID T202.

  Returning to the description of each component of the management server 12 in FIG. 1, the unnecessary sensor node determination unit 125 includes the sensor information and communication environment information acquired from the sensor information storage unit 122 and the grouping information acquired from the grouping information storage unit 124. And sensor information (human sensor information) and communication environment information (radio wave) measured by each of the plurality of installed sensor nodes 11 based on the unnecessary sensor node determination rule acquired from the unnecessary sensor node determination rule storage unit 126. Intensity information) is weighted in a comprehensive manner, unnecessary sensor nodes are determined, and information indicating the determined unnecessary sensor nodes is notified to the unnecessary sensor node display device 13.

  In other words, the unnecessary sensor node discriminating means 125 relates the correlation coefficient between the sensor information of each sensor node 11 and the communication environment information for each installed sensor node 11 or for each sensor node 11 grouped for each installation room. Based on the result of evaluating one radio wave intensity using an evaluation formula determined in advance as an unnecessary sensor node determination rule, it is determined whether or not it is an unnecessary sensor node, and information indicating the determined unnecessary sensor node is provided. The unnecessary sensor node display device 13 is notified.

  The unnecessary sensor node determination rule storage unit 126 is a storage medium that stores and stores in advance an unnecessary sensor node determination rule for determining whether or not each installed sensor node 11 is an unnecessary sensor node. Consists of. Here, the unnecessary sensor node determination rule storage unit 126 stores the unnecessary sensor node determination rule in a format as shown in FIG.

  FIG. 4 is an explanatory diagram showing an example of unnecessary sensor node determination rules stored in the unnecessary sensor node determination rule storage unit 126 in the management server 12 shown in FIG. As illustrated in FIG. 4, the unnecessary sensor node determination rule storage unit 126 comprehensively evaluates an evaluation expression T301 indicating an evaluation expression for determining the unnecessary sensor node 11 and each evaluation expression set in the evaluation expression T301. Information including at least a weight T302 for performing weighting.

  In the example of the unnecessary sensor node discrimination rule shown in FIG. 4, as shown in the evaluation formula T301, an example in which two evaluation formulas are used as the evaluation formula for discriminating the unnecessary sensor node 11 is shown. That is, as a first evaluation formula, when the correlation coefficient regarding the measured value of the arbitrary sensor 111 (human sensor) with any sensor node 11 in the same room is larger than “0.8”, When it is set to '1' indicating that the correlation between both sensor nodes 11 is strong, and the correlation coefficient with any sensor node 11 in the same room is '0.8' or less, The case where it is set to “0” indicating that the correlation between both sensor nodes 11 is weak is shown.

  Further, as the second evaluation formula, communication is impossible when the average of the radio field intensity, which is an example of the communication environment information of any sensor node 11 in the same room, that is, the average radio field intensity is lower than “−80 dBm”. In this case, the value is set to “1” indicating that the user is in an environment, and “−80 dBm” or more indicates that the user is set to “0” indicating that the user is in an environment where communication is possible.

  Then, as indicated by a weight T302, each of the first evaluation formula and the second evaluation formula is weighted by “0.5” to determine whether the sensor node is an unnecessary sensor node or not. It shows that it judges comprehensively. That is, an example is shown in which the correlation coefficient of the sensor information of each sensor node 11 and the communication environment information are equally weighted to make a comprehensive determination. Therefore, even if the sensor information can be appropriately measured, if the radio wave intensity is low and communication is not possible, or vice versa, the sensor node 11 is not suitable as an installation location and is unnecessary. The sensor node 11 is determined.

  Next, returning to the description of each component of the management server 12 in FIG. 1, the unnecessary sensor node display device 13 is a device that displays the unnecessary sensor node notified from the unnecessary sensor node determination unit 125 of the management server 12. For example, a liquid crystal display is used.

  As described above, the sensor node installation system 1 shown in FIG. 1 is based on a plurality of sensor nodes 11 that transmit measured sensor information and communication environment information to the management server 12, and the received sensor information and communication environment information. A management server 12 for determining an unnecessary sensor node 11 from a plurality of sensor nodes 11 installed in the server and notifying the unnecessary sensor node display device 13 and an unnecessary sensor for displaying the unnecessary sensor node notified from the management server 12 And a node display device 13.

  The management server 12 includes at least a reception unit 121, a sensor information storage unit 122, a sensor node grouping unit 123, a grouping information storage unit 124, an unnecessary sensor node determination unit 125, and an unnecessary sensor node determination rule storage unit 126. Is done.

  Here, the receiving means 121 receives sensor information and communication environment information from each of the plurality of sensor nodes 11 and stores them in the sensor information storage unit 122. The sensor information storage unit 122 stores the sensor information and communication environment information received by the receiving unit 121. The sensor node grouping unit 123 groups the plurality of sensor nodes 11 for each installed room based on the sensor information acquired from the sensor information storage unit 122, and records the grouped information in the grouping information storage unit 124. The grouping information storage unit 124 stores the grouping result of the sensor nodes 11 performed by the sensor node grouping unit 123 as grouping information.

  The unnecessary sensor node determination unit 125 includes sensor information and communication environment information acquired from the sensor information storage unit 122, grouping information acquired from the grouping information storage unit 124, and unnecessary sensor node acquired from the unnecessary sensor node determination rule storage unit 126. Based on the discrimination rule, the sensor information measurement status and communication environment information are weighted and comprehensively evaluated, and unnecessary sensor nodes are discriminated from the installed sensor nodes 11 and discriminated. Information on the sensor node is notified to the unnecessary sensor node display device 13.

  In some cases, the unnecessary sensor node determination unit 125 may be configured to determine unnecessary sensor nodes based on sensor information, communication environment information, and unnecessary sensor node determination rules, except for grouping information. good. Further, the unnecessary sensor node determination rule storage unit 126 comprehensively determines the sensor information measurement status and communication environment information from the sensor nodes 11 and determines whether the sensor node 11 is necessary or unnecessary. The discrimination rule is stored.

  The sensor node 11 includes an arbitrary sensor 111 that measures one or more types of sensor information necessary for the monitoring system, a communication environment sensor 112 that measures a communication environment between the sensor node 11 and the management server 12, and an arbitrary sensor. 111 and the communication environment sensor 112, and a transmission unit 113 configured to transmit the sensor information and the communication environment information measured by the communication environment sensor 112 to the management server 12. The unnecessary sensor node display device 13 displays the determination result of the unnecessary sensor node transmitted from the management server 12.

(Explanation of operation example of first embodiment)
Next, the operation of the sensor node installation system 1 shown in FIG. 1 as the first embodiment of the present invention will be described with reference to FIGS.

((Example of main operation of sensor node installation system 1))
First, a main operation example of the sensor node installation system 1 will be described with reference to the flowchart of FIG. FIG. 5 is a flowchart showing an example of the operation of the sensor node installation system 1 shown in FIG. In the flowchart of FIG. 5, first, each sensor node 11 is installed in a place where it is assumed that the installation of the sensor node 11 is appropriate in each room of the residence where the inhabitant to be watched lives. Node 11 is installed (step S1). Here, generally, by installing a plurality of sensor nodes 11, it is expected that at least some of the installed sensor nodes 11 are installed at appropriate positions for watching the residents to be watched over. Therefore, when installing each sensor node 11, it is not necessary to consider factors such as directivity and radio characteristics of each sensor node 11 in particular.

  Therefore, the installer who installs the sensor node 11 does not need to have any special knowledge, and may be an administrator of the watching system, or may be installed by a resident who is watching over or a person living there. There may be a case where a relative or an agent of the relative who wants to obtain the monitoring result of the resident is installed. As the sensor node 11 installed in each room, in the following description, as shown in FIG. 3, for example, “sensor node A” “sensor node B” “sensor” It is assumed that four sensor nodes 11 of “node C” and “sensor node D” are installed.

  After installing a plurality of sensor nodes 11 in the sensor node installation step of step S1, sensor information and communication environment information transmitted from each installed sensor node 11 to the management server 12 for a predetermined period of time are displayed. The data is received by the receiving means 121 and sequentially stored in the sensor information storage unit 122 in time series (step S2). Here, for example, a period of about one week as the predetermined period of time, the sensor information accumulating unit may be used so that the living situation of the resident to be watched can be sufficiently grasped and the necessity or necessity of the installed sensor node 11 can be evaluated. After the sensor information and the communication environment information are accumulated in 122, the process proceeds to step S3. Note that the timing of proceeding to step 3 may not be after the lapse of the predetermined period but may be a timing arbitrarily designated by an administrator or the like.

  Here, each of the four sensor nodes 11 of “sensor node A”, “sensor node B”, “sensor node C”, and “sensor node D” has sensor information (human sensor information), temperature, as shown in FIG. It is assumed that information and communication environment information (radio wave intensity information) are sequentially transmitted and stored in the sensor information storage unit 122 of the management server 12 in time series.

  Next, in the sensor information accumulation step of step S2, the sensor node grouping means 123 is installed in each room based on the sensor information (human sensor information) accumulated in the sensor information accumulation unit 122 as shown in FIG. The installed sensor nodes 11 are grouped for each installed room, and the grouping result is stored in the grouping information storage unit 124 as shown in FIG. 3 as grouping information (step S3). The detailed operation of the sensor node grouping step in step S3 for grouping each installed sensor node 11 for each room will be described later.

  Thereafter, based on the sensor information (human sensor information) and communication environment information (radio wave intensity information) accumulated in the sensor information accumulation step in step S2, and the grouping information grouped in the sensor node grouping step in step S3. The sensor information (human sensor information) measurement status and the communication environment information (radio wave intensity information) measurement status are weighted and comprehensively evaluated, so that each sensor room is installed in each sensor node in step S1. An unnecessary sensor node 11 is discriminated from the plurality of sensor nodes 11 (step S4). The detailed operation of the unnecessary sensor node determining step in step S4 for determining the unnecessary sensor node 11 will be described later.

  Here, the unnecessary sensor node discriminating means 125 selects the unnecessary sensor node 11 among the four sensor nodes 11 of “sensor node A”, “sensor node B”, “sensor node C”, and “sensor node D”. B ”is determined and notified to the unnecessary sensor node display device 13.

  When the unnecessary sensor node display device 13 receives, for example, information of “sensor node B” determined as the unnecessary sensor node 11 in the unnecessary sensor node determination step of step S4, the unnecessary sensor node display device 13 receives the received unnecessary sensor node 11. For example, the information of “sensor node B” is displayed on the screen (step S5).

  When the unnecessary sensor node 11 displayed on the display of the unnecessary sensor node display device 13 such as “sensor node B” is confirmed in the unnecessary sensor node display step of step S5, a plurality of sensors are installed in the residence where the inhabited residents live. The installer who installed the node 11 removes the corresponding unnecessary sensor node 11, for example, “sensor node B”. As described above, the installer who removes unnecessary sensor nodes may be a supervisor of the watching system, may be a resident who is watching, or may be the resident of the same, or may be a watcher of the resident. It may be the case of a relative who is trying to obtain a result or a representative of the relative.

((Detailed operation example of sensor node grouping means 123))
Next, the detailed operation of the sensor node grouping step in step S3 of the flow chart of FIG. 5, that is, the detailed operation of the sensor node grouping means 123 that groups the installed sensor nodes 11 for each room is shown in FIG. This will be described with reference to the flowchart of FIG. FIG. 6 is a flowchart showing an example of detailed operation of the sensor node grouping means 123 in the management server 12 shown in FIG.

  In the flowchart of FIG. 6, the sensor node grouping means 123 first searches the sensor node ID T101 of the sensor information storage unit 122 shown in FIG. 2 and identifies each of the installed sensor nodes 11 Are obtained as a list of sensor node IDs so that the same sensor node IDs do not overlap (step S301). Here, for example, sensor information (human sensor information), temperature information, and communication environment information (radio wave intensity information) for each sensor node ID as shown in FIG. Then, four sensor node IDs of “sensor node A”, “sensor node B”, “sensor node C”, and “sensor node D” are acquired as different sensor node IDs as a sensor node ID list.

  Next, the sensor node grouping unit 123 acquires all combinations of two sensor nodes 11 as a sensor node combination list based on the sensor node ID list acquired in the sensor node ID list acquisition step of step S301. (Step S302).

  Here, “sensor node A”, “sensor node B”, “sensor node C”, and “sensor node D” are two combinations of four sensor nodes 11, that is, “sensor node A and sensor node B”, “ Sensor node A and sensor node C ”,“ sensor node A and sensor node D ”,“ sensor node B and sensor node C ”,“ sensor node B and sensor node D ”,“ sensor node C and sensor node D ”6 A combination of types is acquired as a sensor node combination list.

  Next, the sensor node grouping unit 123 executes the processes of step S304 and step S305 for each combination of all combinations indicated by the sensor node combination list acquired in the sensor node combination list acquisition step of step S302 (step S303). ). Here, the processing step for each sensor node combination in step S303 includes, for example, “sensor node A and sensor node B”, “sensor node A and sensor node C”, “sensor node A and sensor” for six types of sensor node combinations. The processes of step S304 and step S305 are executed in the order of “node D”, “sensor node B and sensor node C”, “sensor node B and sensor node D”, and “sensor node C and sensor node D”.

  The sensor node grouping means 123 shows the measured values of the arbitrary sensors 111 (human sensors) of each of the two sensor nodes 11 in the sensor node combination extracted in order in the processing step for each sensor node combination in step S303 in FIG. Obtained from the measured value T103 of the sensor information storage unit 122 (step S304).

  Here, for example, in the case of the sensor node combination human measurement value acquisition step of step S304 regarding the combination of “sensor node A and sensor node B” which is the first sensor node combination, the sensor shown in FIG. When the sensor information of the information storage unit 122 is stored, the measured value of the arbitrary sensor 111 (human sensor) of “sensor node A” is set to “sensor” in the first row (No. 1) of FIG. “Node A, Human Feeling, 0, 2017/2/1 17:01”, “Sensor Node A, Human Feeling, 1, 2017/2/1 17:02” in the 13th line (No. 13), “ As a measured value of the arbitrary sensor 111 (human sensor) of “sensor node B”, “sensor node B, human sensor, 0, 2017/2/1 17:01”, 16th line of the fourth row (No. 4) Line (No.16) “Sensor Node B, Human Sensation, 1, 20 And 7/2/1 17:02 ", to get.

  Thereafter, the sensor node grouping unit 123 performs a combination based on the measured values of the arbitrary sensors 111 (human sensors) of the two sensor nodes 11 acquired in the sensor node combination human measurement value acquisition step of step S304. The correlation coefficient between the sensor nodes 11 is calculated (step S305). The correlation coefficient calculated in the human measurement value correlation coefficient calculation step in step S305 may be obtained using, for example, Pearson's product moment correlation coefficient.

  Here, for example, as the measurement value of each arbitrary sensor 111 (human sensor) in the combination of “sensor node A and sensor node B” which is the first sensor node combination, the sensor node combination human measurement value in step S304 described above. If the measured value is as shown in the acquisition step, “1” is calculated as the correlation coefficient.

  For example, “sensor node A and sensor node B”, “sensor node A and sensor node C”, “sensor node A” are processed for all combinations of sensor nodes. And sensor node D ”,“ sensor node B and sensor node C ”,“ sensor node B and sensor node D ”, and“ sensor node C and sensor node D ”. A correlation coefficient as shown in FIG. 7 is obtained.

  FIG. 7 shows an example of the result of calculating the correlation function regarding the measured value of the arbitrary sensor 111 (human sensor) in the combination of two sensor nodes 11 in the sensor node grouping means 123 in the management server 12 shown in FIG. FIG. 5 is an explanatory diagram illustrating the calculation result of each correlation coefficient when the measurement value of the arbitrary sensor 111 (human sensor) as illustrated in FIG. 2 is accumulated in the sensor information accumulation unit 122. Yes.

  That is, as shown in the explanatory diagram of FIG. 7, when the measured value of the arbitrary sensor 111 (human sensor) of each sensor node 11 as shown in FIG. 2 has been acquired, “sensor node A and sensor Node B, Sensor node A and sensor node C, Sensor node A and sensor node D, Sensor node B and sensor node C, Sensor node B and sensor node D, Sensor node C and sensor As correlation coefficients in each of the six types of combinations of “node D”, “1”, “−1”, “1”, “−1”, “1”, and “−1” are obtained.

  When the processing of step S304 and step S305 is completed for all combinations of two sensor nodes 11 and the correlation coefficients as illustrated in FIG. 7 are obtained, the sensor node grouping means 123 performs two by two. When the correlation coefficient between the sensor nodes 11 of the combination is equal to or greater than a predetermined value, grouping is performed by determining that the corresponding two sensor nodes 11 are installed in the same room ( Step S306). The result of grouping in the sensor node grouping step of step S306 is stored in the grouping information storage unit 124 as grouping information.

  Here, for example, “0.8” is used as the constant value, and when the correlation coefficient between the sensor nodes 11 in two combinations is “0.8” or more, two corresponding values are used. The sensor nodes 11 are grouped as belonging to the same group (that is, installed in the same room).

  As a result, for example, “sensor node A and sensor node B”, “sensor node A and sensor node C”, “sensor node A and sensor node D”, “sensor node B and sensor node C”, “sensor node B and When the correlation coefficients as shown in FIG. 7 are obtained with respect to the six types of combinations of “sensor node D” and “sensor node C and sensor node D”, the correlation coefficient is “0.8”. It is determined that “sensor node A”, “sensor node B”, and “sensor node D”, which are “1”, belong to the same group (that is, are installed in the same room). Do. On the other hand, “sensor node C” whose correlation coefficient does not reach “0.8” in any combination with sensor node 11 is different from “sensor node A”, “sensor node B”, and “sensor node D”. The grouping is performed by determining that it belongs to a group (that is, installed in another room).

  The grouping information obtained as a result of the grouping is stored in the grouping information storage unit 124 as shown in FIG. As described above, the installation room ID T202 shown in FIG. 3 is an identifier for uniquely identifying the room in which the sensor node 11 is installed, and is automatically assigned so as to have a unique value for each group. The In the case of the example illustrated in FIG. 3, as the installation room ID T202, the “room A” is included in the “sensor node A”, “sensor node B”, and “sensor node D” of the same group, “Room B” is automatically assigned to “C”.

((Detailed operation example of unnecessary sensor node discriminating means 125))
Next, the detailed operation of the unnecessary sensor node determination step in step S4 in the flowchart of FIG. 5, that is, the details of the unnecessary sensor node determination means 125 for determining the unnecessary sensor node 11 among the installed sensor nodes 11. The operation will be described with reference to the flowchart of FIG. FIG. 8 is a flowchart showing an example of detailed operation of the unnecessary sensor node discriminating means 125 in the management server 12 shown in FIG.

  In the flowchart of FIG. 8, the unnecessary sensor node determination unit 125 first acquires a grouping information installation room ID list stored in the grouping information storage unit 124 (step S401). Here, for example, the grouping information shown in FIG. 3 is stored in the grouping information storage unit 124, and “room A” and “room B” are acquired as a list of installation room IDs.

  Next, the unnecessary sensor node discriminating means 125 executes the subsequent processing from step S403 to step S410 for each installation room ID acquired in the installation room ID list acquisition step of step S401 (step S402). Here, in the processing step for each installation room ID in step S402, the processing from step S403 to step S410 is executed in the order of “room A” and “room B”.

  The unnecessary sensor node discriminating means 125 accesses the grouping information storage unit 124 as shown in FIG. 3, and first acquires a sensor node ID list corresponding to the first installation room ID (step S403). Here, it is assumed that the grouping information in FIG. 3 is stored in the grouping information storage unit 124. In the sensor node ID list acquisition step in step S403, the sensor node ID T201 in the grouping information storage unit 124 in FIG. Three sensor node IDs of “sensor node A”, “sensor node B”, and “sensor node D” corresponding to “room A” of the first installation room ID are acquired.

  Next, the unnecessary sensor node discriminating means 125 executes the subsequent processing from step S405 to step S408 for each sensor node ID acquired in the sensor node ID list acquisition step of step S403 (step S404). Here, for example, in the case of “room A” of the first installation room ID, the processing steps for each sensor node ID in step S404 are “sensor node A”, “sensor node B”, “sensor” corresponding to “room A”. For each node D, the processing from step S405 to step S408 is executed in order.

  The unnecessary sensor node determination unit 125 first acquires an unnecessary sensor node determination rule list from the unnecessary sensor node determination rule storage unit 126 (step S405). Here, it is assumed that the unnecessary sensor node determination rule storage unit 126 stores two unnecessary sensor node determination rules as shown in FIG. 4, and the “if in the same room” of the first unnecessary sensor node determination rule is stored. Correlation coefficient of human feeling with any sensor node> 0.8 then 1 else 0, weight 0.5 ”and“ if average radio wave intensity <−80 dBm then 1 else ”of the second unnecessary sensor node discrimination rule 0, weight 0.5 ".

  Next, the unnecessary sensor node determination unit 125 executes the process of the next step S407 for each unnecessary sensor node determination rule acquired in the unnecessary sensor node determination rule list acquisition step of step S405 (step S406). Here, when two unnecessary sensor node determination rules as shown in FIG. 4 are stored, the processing step for each unnecessary sensor node determination rule in step S406 is “if” of the first unnecessary sensor node determination rule. Correlation coefficient of human feeling with any sensor node in the same room> 0.8 then 1 else 0, weight 0.5 ”and“ if average radio wave intensity <−80 dBm ”of the second unnecessary sensor node discrimination rule Then, the next step S407 is executed using “then 1 else 0, weight 0.5” in order.

  Next, the unnecessary sensor node discriminating means 125 performs the unnecessary sensor node specified in the processing step for each unnecessary sensor node discrimination rule in step S406 with respect to the sensor node IDs specified in the processing step for each sensor node ID in step S404. Evaluation is performed based on the discrimination rule (step S407).

  Here, in the unnecessary sensor node discriminating / evaluating step in step S407, for example, for “room A” initially specified in the processing step for each installation room ID in step S402, first in the processing step for each sensor node ID in step S404. For the designated “sensor node A”, first, using the correlation coefficient for each combination of two sensor nodes installed in the same room, the first unnecessary sensor node discrimination rule “if in the same room” is used. Evaluation based on correlation coefficient of human feeling with any sensor node> 0.8 then 1 else 0, weight 0.5 ”.

  Here, sensor information (human sensor information) and communication environment information (radio wave intensity information) as shown in FIG. 2 are stored in the sensor information storage unit 122, and the phases for each two sensor node combinations are stored. Assuming that the correlation coefficient as shown in FIG. 7 is obtained as the number of relationships, in the case of “sensor node A”, a combination with “sensor node B” installed in the same room “room A”; In any of the combinations with “sensor node D”, the correlation coefficient is “1” and the first unnecessary sensor node determination rule as shown in the first and third rows of FIG. Since the value is larger than '0.8', which is the condition of the above, it is evaluated as '1', further weighted by the weight '0.5', and the evaluation result is evaluated as '0.5'. The

  Thereafter, in the unnecessary sensor node discriminating / evaluating step in step S407, “room A” first designated in the processing step for each installation room ID in step S402 is first designated in the processing for each sensor node ID in step S404. The second unnecessary sensor node discrimination is performed using the measured value T103 of the communication environment information (radio wave intensity information) of the communication environment sensor 112 stored in the sensor information storage unit 122 with respect to the obtained “sensor node A”. Evaluation is performed based on the rule “if average radio wave intensity <−80 dBm then 1 else 0, weight 0.5”.

  Here, assuming that sensor information and communication environment information as shown in FIG. 2 are stored in the sensor information storage unit 122, in the case of “sensor node A”, the third row (No. .3) The average radio field intensity for the measurement value T103 of each radio field intensity in the 15th line (No. 15) is “−30 dBm”, which is the condition of the second unnecessary sensor node discrimination rule “−80 dBm”. Since the value is not larger than “0”, it is evaluated as “0”, and is evaluated as “0” as an evaluation result after weighting with the weight “0.5”.

  Therefore, as an evaluation result based on the unnecessary sensor node determination rule in the unnecessary sensor node determination evaluation step in step S407, that is, as an evaluation result based on the unnecessary sensor node determination rule in the unnecessary sensor node determination unit 125, for example, the sensor node in step S404 With respect to “sensor node A” in “room A” specified first in the process for each ID, an evaluation result as shown in FIG. 9 is obtained.

  FIG. 9 is an explanatory diagram showing an example of an evaluation result based on an unnecessary sensor node determination rule for the sensor node 11 in the unnecessary sensor node determination unit 125 in the management server 12 shown in FIG. 1, and the sensor information storage shown in FIG. Based on the sensor information (human sensor information) and communication environment information (radio wave intensity information) of unit 122, evaluation for “sensor node A” in “room A” initially designated in the process for each sensor node ID in step S404 Results are shown.

  That is, as shown in the evaluation result T303 of FIG. 9, “if human sensor correlation coefficient with any sensor node in the same room> 0.8 then 1 else 0, As described above, the evaluation result regarding “weight 0.5” is “0.5”, and “if average radio wave intensity <−80 dBm then 1 else 0, weight 0.5 of the second unnecessary sensor node determination rule”. As described above, the evaluation result regarding “” is “0”.

  Thereafter, the unnecessary sensor node determination unit 125 determines whether the total of the evaluation results based on the unnecessary sensor node determination rule evaluated in the unnecessary sensor node determination evaluation step in step S407 is less than a predetermined evaluation threshold value. Thus, the necessity / unnecessity of the sensor node 11 is determined (step S408). That is, if the total value of the evaluation results is less than the evaluation threshold value, it is determined that the sensor node 11 is necessary. On the other hand, if it is equal to or greater than the evaluation threshold value, it is determined that the sensor node 11 is unnecessary.

  For example, in the case where the evaluation threshold is set to “0.8” in advance, an evaluation result as shown in an evaluation result T303 in FIG. 9 is obtained as an evaluation result of “sensor node A” installed in “room A”. In the case of being obtained, the total value of the evaluation results of “sensor node A” is “0.5” (= 0.5 + 0), and thus is a value less than “0.8” of the evaluation threshold value. “Sensor node A” is determined as the necessary sensor node 11.

  With the above operation, regarding “room A” initially specified in the processing step for each installation room ID in step S402, “sensor node A” first specified in the processing for each sensor node ID in step S404, that is, the first The evaluation regarding “sensor node A” installed in “room A”, which is an unnecessary sensor node discrimination process, is terminated. Thereafter, the unnecessary sensor node discriminating unit 125 selects the next sensor node 11 and executes the processing from step S405 to step S408 in the processing for each sensor node ID in step S404. It repeats until evaluation of all the sensor nodes 11 regarding "room A" designated first in the processing step for each room ID is completed.

  As a result, for example, sensor information (human sensor information) and communication environment information (radio wave intensity information) as shown in FIG. 2 are stored in the sensor information storage unit 122, and each two sensor node combinations. When the correlation coefficient as shown in FIG. 7 is obtained as the correlation coefficient, the following evaluation result is obtained.

  That is, “sensor node B” is “if human sensor correlation coefficient with any sensor node in the same room> 0.8 then 1 else 0, weight 0.5 of the first unnecessary sensor node discrimination rule. The evaluation result regarding “if” is “0.5”, and the evaluation result regarding “if average radio wave intensity <−80 dBm then 1 else 0, weight 0.5” of the second unnecessary sensor node determination rule is also “0.5”. Since the total value of the evaluation results of “sensor node B” is “1.0” (= 0.5 + 0.5), the evaluation threshold is “0.8” or more, and “sensor node “B” is determined as an unnecessary sensor node 11.

  Further, “sensor node D” is “if human sensor correlation coefficient with any sensor node in the same room> 0.8 then 1 else 0, weight 0.5 of the first unnecessary sensor node discrimination rule. Is “0.5”, and the second unnecessary sensor node discrimination rule “if average radio wave intensity <−80 dBm then 1 else 0, weight 0.5” is “0”. Since the total value of the evaluation results of “sensor node D” is “0.5” (= 0.5 + 0), the evaluation threshold value is less than “0.8”, and “sensor node D” is necessary. Is identified as a sensor node 11.

  Next, when the evaluation of all sensor nodes 11 regarding the same installation room ID, for example, the installation room ID indicating the first “room A” is completed, the unnecessary sensor node determination unit 125 performs the sensor node necessity / unnecessity determination step in step S408. It is determined whether all sensor nodes 11 related to the same installation room ID, for example, the installation room ID indicating the first “room A” have been evaluated as unnecessary sensor nodes 11 (step S409). When all sensor nodes 11 related to the same installation room ID, for example, the installation room ID indicating the first “room A” are evaluated as unnecessary sensor nodes 11 in the same installation room ID all sensor node unnecessary determination step in step S409. (Yes in step S409), the process proceeds to step S410.

  When the total value of the evaluation results of all sensor nodes 11 related to the same installation room ID, for example, the installation room ID indicating the first “room A” is equal to or greater than the evaluation threshold value, the process proceeds to step S410. The unnecessary sensor node discriminating means 125 evaluates the sensor node necessity / unnecessity judgment step in step S408 in order to eliminate the situation where all the sensor nodes 11 are removed from the same installation room ID, for example, the first “room A”. The sensor node 11 having the lowest total value is determined again as the necessary sensor node 11 in the installation room ID (step S410). In the sensor node non-installation room elimination step of step S410, all the sensor nodes 11 in the same installation room have all the evaluation results equal to or higher than the evaluation threshold value, and all the sensor nodes 11 in the same installation room This is a process for preventing the sensor node from being removed, and is a process for eliminating the sensor node non-installation room.

  On the other hand, in the step of determining that all sensor nodes in the same installation room ID are unnecessary in step S409, if there is a sensor node 11 evaluated as a necessary sensor node 11 among the sensor nodes 11 related to the same installation room ID (step S409). In step S409, the unnecessary sensor node determination unit 125 returns to step S402 and selects the next “room B” in the processing step for each installation room ID in step S402. All the sensor nodes 11 related to the installation room ID of “room B” are evaluated as to whether they are unnecessary sensor nodes.

  As a result, for example, sensor information and communication environment information as shown in FIG. 2 are stored in the sensor information storage unit 122. As shown in FIG. In the case where only one of “C” is set, “sensor node C” is “if the first unnecessary sensor node discrimination rule is“ if correlation coefficient of human feeling with any sensor node in the same room ”> The evaluation result relating to “0.8 then 1 else 0, weight 0.5” is “0”, and “if average radio wave intensity <−80 dBm then 1 else 0, weight 0 of the second unnecessary sensor node determination rule” .5 ”is also“ 0 ”, and the total value of the evaluation results of“ sensor node C ”is“ 0 ”(= 0 + 0). Therefore, the evaluation threshold value is less than“ 0.8 ”. Yes, “sensor node C” is determined as the necessary sensor node 11.

  As described in detail above, the sensor node installation method according to the first embodiment installs a plurality of sensor nodes 11 in each room in a residence where a resident to be watched lives as shown in FIG. The sensor node installation step of step S1, the sensor information storage step of step S2 for storing sensor information and communication environment information transmitted from the sensor node 11 to the management server 12, and the sensor information stored in the sensor information storage step Based on the above, in the sensor node grouping step of step S3 for grouping the installed sensor nodes 11 for each installed room, the sensor information and communication environment information accumulated in the sensor information accumulation step, and the sensor node grouping step Grouped sensor nodes 11 and Based on the unnecessary sensor node determination step in step S5 for determining the unnecessary sensor node 11 from the installed sensor nodes 11, and displaying the unnecessary sensor node determined in the unnecessary sensor node determination step, It includes at least an unnecessary sensor node display step of step S5 for notifying a resident or a related person to be watched over.

  Further, as shown in FIG. 6, the sensor node grouping step in the first embodiment includes a sensor node ID list attached to the sensor information and communication environment information accumulated in the sensor information accumulation step. Sensor node ID acquisition step of step S301 for acquiring so as not to overlap, and sensor node combination of step S302 for acquiring all combinations of two sensor node IDs from the sensor node ID acquired in the sensor node ID list acquisition step For each combination acquired in the list acquisition step, the sensor node combination list acquisition step, the following step S304 and step S305 are executed for each sensor node combination processing step; Sensor node combination sensor information (human sensor measurement value) acquisition step of step S304 for acquiring sensor information (human sensor information) of each sensor node 11 for each combination acquired in the command combination list acquisition step, and the sensor node combination A human measurement value correlation coefficient calculating step of step S305 for calculating a correlation coefficient between the sensor information (human sensor information) of each sensor node 11 acquired in the sensor information (human measurement value) acquisition step; In the case of sensor node combinations in which the correlation coefficient calculated in the sensation measurement value correlation coefficient calculation step is equal to or greater than a predetermined value, it is determined that they are installed in the same room, and is grouped for each installation room ID. The result is recorded in the grouping information storage unit 124 as grouping information. A sensor node grouping step in step S306, the and at least a.

  Further, as shown in FIG. 8, the unnecessary sensor node determination step in the first embodiment includes an installation room ID list acquisition step of step S401 for acquiring an installation room ID list from the grouping information storage unit 124, and the installation For each installation room ID acquired in the room ID list acquisition step, the following step S403 to step S410 are executed for each installation room ID processing step in step S402, and sensor node ID list acquisition in step S403 for acquiring the sensor node ID list. Steps, processing steps for each sensor node ID in Step S404 for executing the following Steps S405 to 08 for each sensor node ID acquired in the sensor node ID list acquisition step, and an unnecessary sensor node discrimination rule storage unit 126 An unnecessary sensor node discrimination rule is evaluated for each unnecessary sensor node discrimination rule acquired in the unnecessary sensor node discrimination rule list acquisition step in step S405 of acquiring the node discrimination rule list and in the unnecessary sensor node discrimination rule list acquisition step. The unnecessary sensor node discrimination rule evaluation step of step S406 is executed for each unnecessary sensor node discrimination rule processing step of step S406 and the sensor node ID acquired in the sensor node ID list acquisition step. The same installation room as the sensor node necessity / unnecessity determination step of step S408 for determining the necessity / unnecessity of installation of the sensor node 11 based on whether or not the total value of the evaluation results is less than a predetermined evaluation threshold value All sensor nodes 11 of the same installation room ID in the same installation room ID all sensor node unnecessary determination step in step S409 and whether or not all the sensor nodes 11 of the same installation room ID are required in step S409 are confirmed. When the sensor node 11 becomes unnecessary, the sensor node 11 in which the total value of the evaluation results is the lowest value is re-determined as the sensor node 11 that needs to be installed. Have.

<Second Embodiment>
Next, a sensor node installation system and a sensor node installation method according to the second embodiment of the present invention will be described in detail with reference to FIGS. 10 to 13.

(Configuration example of the second embodiment)
First, a system configuration example of a sensor node installation system according to the second embodiment of the present invention will be described with reference to FIG. FIG. 10 is a system configuration diagram showing an example of the entire configuration of the sensor node installation system according to the second exemplary embodiment of the present invention. The sensor node installation system 1A in FIG. 10 appropriately installs a plurality of sensor nodes 11 constituting the watching system, and then, based on sensor information and communication environment information measured at each sensor node 11, It has a mechanism similar to that of the first embodiment that makes it possible to automatically determine unnecessary sensor nodes by determining installation effects, correlations, and the like, and further, in FIG. 1 of the first embodiment. Unlike the case, a mechanism for automatically determining and displaying the room type in which the sensor node 11 is installed is provided.

  As shown in FIG. 10, the sensor node installation system 1A according to the second embodiment is similar to the sensor node installation system 1 shown in FIG. A server 12A and an unnecessary sensor node display device 13 are provided, and a room type display device 14 is newly added to FIG. Here, as in the case of FIG. 1 of the first embodiment, a plurality of sensor nodes 11 are installed at a plurality of locations where installation is assumed to be appropriate according to the environmental conditions to be monitored by the monitoring system. is set up.

  That is, the sensor node installation system 1A shown in FIG. 10 as the second embodiment is configured by adding each hatched component to the sensor node installation system 1 shown in FIG. In the management server 12A, a room type determination unit 127 and a room type determination rule storage unit 128 are added, and the room type display device 14 is connected to the management server 12A as described above. It has been added. The other components are configured by the same components as the sensor node installation system 1 shown in FIG. 1, and are denoted by the same reference numerals as those in FIG.

  In the following description, the duplicate description regarding the same component as the sensor node installation system 1 shown in FIG. 1 as the first embodiment is omitted, and the sensor node installation system 1A according to the second embodiment is newly added. The added component will be described.

  First, the room type determination unit 127 in the management server 12A is stored in the sensor information stored in the sensor information storage unit 122, the grouping information stored in the grouping information storage unit 124, and the room type determination rule storage unit 128. Based on the room type determination rule, the room type of the room where the sensor node 11 is installed is determined and notified to the room type display device 14.

  Further, the room type determination rule storage unit 128 in the management server 12A is a storage medium that predetermines and stores a room type determination rule for determining the room type, and is configured by a hard disk or the like. Here, the room type determination rule storage unit 128 stores the room type determination rule in a format as shown in FIG.

  FIG. 11 is an explanatory diagram showing an example of a room type determination rule stored in the room type determination rule storage unit 128 in the management server 12A shown in FIG. As illustrated in FIG. 11, the room type determination rule storage unit 128 sets an evaluation formula T401 indicating an evaluation formula for determining the room type, and a room type determined by each evaluation formula set in the evaluation formula T401. And room type T402.

  In the example of the room type determination rule shown in FIG. 11, as shown in the evaluation formula T401, the following four evaluation formulas are used as the evaluation formula for discriminating the room type. That is, as the first evaluation formula, the number of times the arbitrary sensor 111 (human sensor) has reacted between 0 o'clock and 9 o'clock is 0, and the arbitrary sensor between 17 o'clock and 22 o'clock This is a case where the number of times 111 (human sensor) has reacted more than five times. In such a case, as shown in the room type T402, it is evaluated that the room type is “bathroom”.

  The second evaluation formula is a case where the number of times the arbitrary sensor 111 (human sensor) has reacted more than 50 times from 21:00 to 8:00 the next morning, and from 10:00 to 18 This is a case where the number of times that the arbitrary sensor 111 (human sensor) has reacted by less than 10 times, and in such a case, as shown in the room type T402, the room type is “bedroom”. evaluate.

  Further, as a third evaluation formula, the number of times that the arbitrary sensor 111 (human sensor) has reacted less than 5 from 21:00 to 8:00 the next morning, and from 10:00 to 18:00 In this case, the number of times the arbitrary sensor 111 (human sensor) has reacted is more than 100. In this case, the room type is evaluated as “living room” as shown in the room type T402. To do. Further, the fourth evaluation formula is a case that does not correspond to any of the above-described first to third evaluation formulas. In this case, the room type is “unknown” as shown in the room type T402. And evaluate.

  Further, the room type display device 14 of the sensor node installation system 1A shown in FIG. 10 observes the discrimination result of the room type determined by the room type determination unit 127 of the management server 12A, and the situation of the system manager and the residents to be watched over. For example, a liquid crystal display or the like.

(Description of operation example of second embodiment)
Next, the operation of the sensor node installation system 1A shown in FIG. 10 as the second embodiment of the present invention will be described with reference to FIG. 12 and FIG.

((Example of main operation of sensor node installation system 1A))
First, the main operation of the sensor node installation system 1A will be described with reference to the flowchart of FIG. FIG. 12 is a flowchart showing an example of the operation of the sensor node installation system 1A shown in FIG. In the flowchart of FIG. 12, the two steps S6 and S7 that are hatched are newly added to the flowchart shown in FIG. 5 as the first embodiment. Also, each step from step S1 to step S5 in the flowchart of FIG. 12 is exactly the same as the flowchart shown in FIG. 5, and the same reference numerals are given, and redundant explanations are omitted here.

  In the flowchart of FIG. 12, the processing from step S1 to step S5 is finished, and information regarding the unnecessary sensor node 11 determined by the unnecessary sensor node determination unit 125 is displayed on the unnecessary sensor node display device 13. When notified to the administrator of the watching system, etc., the room type determination means 127 of the management server 12A is then executed.

  The room type determination unit 127 then stores the sensor information stored in the sensor information storage unit 122, the grouping information stored in the grouping information storage unit 124, and the room type determination stored in the room type determination rule storage unit 128 in advance. Based on the rule, the room type of the room in which each sensor node 11 is installed is determined and notified to the room type display device 14 as a room type determination result (step S6). The detailed operation of the room type determination step in step S6 will be described later.

  When the room type display device 14 receives the information about the room type of the room in which each sensor node 11 determined in the room type determination step of step S6 is received as the room type determination result, the room type display device 14 receives the information. The room type discrimination result is displayed on the screen and notified to the monitoring system administrator or the like (step S7). An administrator of the estimation system can provide an effective monitoring service using the monitoring system to the user based on the room type determination result displayed on the room type display device 14 on the screen.

((Detailed operation example of the room type discrimination means 127))
Next, the detailed operation of the room type determination step in step S6 of the flowchart of FIG. 12, that is, the detailed operation of the room type determination unit 127 that determines the room type of the room where each sensor node 11 is installed. This will be described with reference to the flowchart of FIG. FIG. 13 is a flowchart showing an example of detailed operation of the room type determination unit 127 in the management server 12A shown in FIG.

  In the flowchart of FIG. 13, the room type determination unit 127 first acquires a list of installation room IDs from the grouping information storage unit 124 (step S601). For example, when the grouping information as shown in FIG. 3 is stored in the grouping information storage unit 124, the installation room IDs related to “room A” and “room B” are acquired as the installation room ID list. .

  Next, the room type determination unit 127 sequentially performs the processing from step S603 to step S608 for each installation room ID acquired in the installation room ID list acquisition step of step S601 (step S602). Here, when the grouping information as shown in FIG. 3 is stored, the processing steps for each installation room ID in step S602 are, for example, in the order of “room A” and “room B” from step S603. The processing up to S608 is executed.

  The room type determination unit 127 acquires a list of room type determination rules from the room type determination rule storage unit 128 (step S603). Here, in the case where the room type determination rule storage unit 128 stores the correspondence between the evaluation formula T401 and the room type T402 as shown in FIG. The four evaluation formulas shown in the evaluation formula T401 and the room type T402 in FIG. 11 and the corresponding room type are acquired as a list of room type discrimination rules.

  Next, the room type determination unit 127 sequentially executes the processes from step S605 to step S608 for each room type determination rule acquired in the room type determination rule list acquisition step of step S603 (step S604). Here, in the processing step for each room type determination rule in step S604, for example, the number of human reaction from 0 to 9 o'clock in the first evaluation formula = 0 and the number of human reaction from 17:00 to 22:00> 5 Times, bathroom ”, second evaluation formula“ Number of human reaction from 21:00 to 8 o'clock> 50 times and number of human reaction from 10:00 to 18:00 <10 times, bedroom ”,“ The number of human reaction from 21:00 to 8 o'clock <5 times and the number of human reaction from 10 o'clock to 18:00> 100 times, “living”, the fourth evaluation formula “other than the above-mentioned first to third evaluation formulas, The processing from step S605 to S608 is executed in the order of “unknown”.

  Next, the room type determination means 127 acquires a sensor node ID list corresponding to the installation room ID corresponding to the order in the processing step for each installation room ID in step S602 from the grouping information storage unit 124 (step S605). Here, for example, it is assumed that the grouping information in FIG. 3 is stored in the grouping information storage unit 124. If the order in the processing step for each installation room ID in step S602 is “room A”, FIG. As illustrated, “sensor node A”, “sensor node B”, and “sensor node D” corresponding to “room A” are acquired.

  Thereafter, the room type determination unit 127 obtains sensor information (human sensor information) in each sensor node 11 in the sensor node ID list corresponding to the installation room ID acquired in the installation room ID corresponding sensor node acquisition step in step S605. The information is acquired from the sensor information storage unit 122 (step S606). Here, for example, when the sensor information (human sensor information) shown in FIG. 2 is stored in the sensor information storage unit 122 and the installation room ID is “room A”, The sensor information (human sensor information) in each sensor node 11 corresponding to the sensor node ID “sensor node A”, “sensor node B”, and “sensor node D” is acquired.

  Then, the room type determination unit 127 calculates the room in step S604 with respect to the total number of reactions in the sensor information (human sensor information) of each sensor node 11 acquired in the sensor node corresponding sensor information acquisition step in step S606. Each type discrimination rule is evaluated by applying the room type discrimination rule corresponding to the order in the processing step (step S607).

  Here, in the room type determination rule evaluation step in step S607, for example, the number of human reaction from 0 o'clock to 9 o'clock in the first evaluation formula first selected in the processing step for each room type determination rule in step S604 = Applying the room type discrimination rule of “0 and 17:00 to 22:00> 5 times, bathroom” and the order of the installed rooms in the processing step for each installed room ID in step S602 is “room A” Evaluates the total number of human reaction responses of the arbitrary sensor 111 (human sensor) in each of the sensor nodes 11 of “sensor node A”, “sensor node B”, and “sensor node D” of “room A”. .

  Next, the room type determination unit 127 uses the sensor information (human sensor information) of each sensor node 11 acquired in the sensor node corresponding sensor information acquisition step of step S606 as the evaluation result in the room type determination rule evaluation step of step S607. It is determined whether or not the total value of the number of reactions in (1) matches the conditions of the evaluation formula of the applied room type determination rule (step S608).

  If it is determined in the room type determination rule conformity determination step of step S608 that the condition of the evaluation formula of the applied room type determination rule is satisfied (Yes in step S608), processing for each installation room ID in step S602 is performed. The room of the installation room ID specified in the step is determined to be the room type corresponding to the evaluation formula of the applied room type determination rule.

  Here, for example, the total number of human reaction times of “sensor node A”, “sensor node B”, and “sensor node D” in “room A” is “0” from 0 to 9 o'clock. When the interval from 17:00 to 22:00 is “6 times”, the condition of the first evaluation formula is satisfied, so as shown in the room type T402 in FIG. It is determined that “room A” is a “bathroom” corresponding to the first evaluation formula. Thereafter, the process returns to step S602, the installation room ID in the next order is designated, and the processes from step S603 to S608 are executed.

  On the other hand, if the room type determination unit 127 determines in the room type determination rule conformity determination step in step S608 that the condition does not meet the conditions of the evaluation formula of the applied room type determination rule (No in step S608), step Returning to S604, the evaluation formulas of the next-order room type determination rule are applied, and the processing from S605 to S608 is executed. When the fourth evaluation formula of the last room type determination rule is reached, as shown in the room type T402 in FIG. 11, the installation room ID specified in the processing step for each installation room ID in step S602 is displayed. The room is determined to have the room type “unknown”.

  By executing the above operation for all installation room IDs and all room type determination rules, the room type of each room in which the sensor node 11 is installed can be automatically determined. When it is desired to grasp the occurrence of a fall accident in the bathroom of the target inhabitant, it is also possible to perform an operation such as management by paying attention to the sensor information of the sensor node 11 installed in the bathroom.

<Third Embodiment>
Next, a sensor node installation system and a sensor node installation method according to the third embodiment of the present invention will be described in detail with reference to FIGS. 14 and 15. The configuration of the sensor node installation system in the third embodiment is the same as that of the sensor node installation system 1 shown in FIG. 1 as the first embodiment, but the sensor node installation system in the third embodiment. The operation 1 is described in the case where the operation in the unnecessary sensor node determination unit 125 in the management server 12 performs an operation different from the flowchart shown in FIG. 8 of the first embodiment.

(Explanation of operation example of third embodiment)
((Detailed operation example of unnecessary sensor node discrimination means in the third embodiment))
FIG. 14 is a flowchart showing an example of the detailed operation of the unnecessary sensor node discriminating means 125 in the management server 12 shown in FIG. 1 different from FIG. 8, and is a flowchart of FIG. 5 (the main of the sensor node installation system 1). An operation example different from FIG. 8 of the detailed operation of the unnecessary sensor node determination step of step S4 in the flowchart showing the operation) is shown. Here, in the unnecessary sensor node discriminating means 125 in the third embodiment, the number of sensor nodes that need to be installed is reduced to a smaller number than in the case shown in FIG. 8 as the first embodiment. An example of an operation that makes it possible is shown.

  In the flowchart of FIG. 14, the unnecessary sensor node determination unit 125 first obtains a list of grouping information installation room IDs stored in the grouping information storage unit 124 as in step S401 of the flowchart of FIG. (Step S411). Here, it is assumed that the grouping information shown in FIG. 3 is stored in the grouping information storage unit 124, and “room A” and “room B” are acquired as a list of installation room IDs.

  Next, as in the case of step S402 in the flowchart of FIG. 8, the unnecessary sensor node determination unit 125 performs the following steps S413 to S420 for each installation room ID acquired in the installation room ID list acquisition step of step S411. Processing is executed (step S412). Here, in the processing step for each installation room ID in step S412, the processing from step S413 to step S420 is executed in the order of "room A" and "room B".

  The unnecessary sensor node discriminating unit 125 accesses the grouping information storage unit 124 as shown in FIG. 3, and first acquires a sensor node ID list corresponding to the first installation room ID (step S413). 3 is stored in the grouping information storage unit 124. In the sensor node ID list acquisition step in step S413, for example, the sensor node ID T201 of the grouping information storage unit 124 in FIG. The three sensor node IDs “sensor node A”, “sensor node B”, and “sensor node D” corresponding to “room A” of the first installation room ID are acquired.

  The subsequent operation in FIG. 14 performs an operation different from the operation after step S404 in the flowchart of FIG. 8 to determine an unnecessary sensor node. First, the unnecessary sensor node determination unit 125 acquires all combinations of the two sensor nodes 11 as a sensor node combination list from the sensor node list corresponding to the installation room ID acquired in the sensor node list acquisition step of step S413. (Step S414).

  Here, for example, as a sensor node list corresponding to “room A” of the first installation room ID, 3 of “sensor node A”, “sensor node B”, and “sensor node D” in the sensor node ID list acquisition step of step S413. When the sensor node IDs have been acquired, three types of sensor node combinations of “sensor node A and sensor node B”, “sensor node A and sensor node D”, and “sensor node B and sensor node D” As a sensor node combination list.

  Next, the unnecessary sensor node discriminating means 125 performs the processing of the next step S416 and step S417 for each sensor node combination in the sensor node combination list corresponding to the installation room ID acquired in the sensor node combination list acquisition step of step S414. The processes are executed in order (step S415). Here, in the processing step for each sensor node combination in step S415, for example, “sensor node A and sensor node B”, “sensor node A and sensor node D”, “sensor node B and sensor node D” Steps S416 and S417 are executed.

  The unnecessary sensor node discriminating means 125 calculates the measured value of the arbitrary sensor 111 (human sensor) of each of the two sensor nodes 11 corresponding to the sensor node combination specified in order in the processing step for each sensor node combination in step S415. Obtained from the sensor information storage unit 122 (step S416).

  Here, for example, the sensor node combination designated in the sensor node ID list acquisition step of step S413 is “sensor node A and sensor node B”, and the sensor information shown in FIG. If it is, the measured value of the arbitrary sensor 111 (human sensor) of “sensor node A” is “sensor node A, human sensor, 0, 2017/2/1 17:01”, “sensor node A, Human impression, 1, 2017/2/1 17:02 ”is acquired. The measured values of the arbitrary sensor 111 (human sensor) of “sensor node B” include “sensor node B, human sensor, 0, 2017/2/1 17:01”, “sensor node B, human sensor, 1, 2017/2/1 17:02 ”is acquired.

  Next, the unnecessary sensor node discriminating means 125 is based on the measured values of the arbitrary sensors 111 (human sensors) of the two sensor nodes 11 acquired in the combined sensor node human acquisition step of step S416. A correlation coefficient between the sensor nodes 11 is calculated (step S417). The correlation coefficient may be calculated using the Pearson product moment correlation coefficient, as described above.

  Here, for example, in the combined sensor node human body acquisition step of step S416, for each of “sensor node A” and “sensor node B” in the case of the sensor node combination of “sensor node A and sensor node B”, as described above. When the measured value of the arbitrary sensor 111 (human sensor) has been acquired, the correlation coefficient between “sensor node A” and “sensor node B” is calculated as “1”.

  Thereafter, the unnecessary sensor node discriminating means 125 returns to step S415, and repeats the processing of step S416 and step S417 for calculating the correlation coefficient regarding the next combination of sensor nodes 11 in order. As a result, when the calculation of the correlation coefficient regarding all the sensor node combinations indicated in the sensor node combination list corresponding to the installation room ID acquired in the sensor node combination list acquisition step of step S414 is completed, for example, the installation room ID is “room” In the case of “A”, a calculation result as shown in FIG. 15 is obtained.

  FIG. 15 shows the measurement value of the arbitrary sensor 111 (human sensor) in the combination of two sensor nodes 11 installed in the same installation room in the unnecessary sensor node determination means 125 in the management server 12 shown in FIG. It is explanatory drawing which shows the result of having calculated the correlation coefficient. In FIG. 15, when the sensor information shown in FIG. 2 is stored in the sensor information storage unit 122, 3 of “sensor node A”, “sensor node B”, and “sensor node D” installed in “room A”. The example of the calculation result of the correlation coefficient between two sensor nodes 11 is shown for each sensor node 11. That is, as shown in the correlation coefficient column of FIG. 15, three types of sensor node combinations of “sensor node A and sensor node B”, “sensor node A and sensor node D”, and “sensor node B and sensor node D” In either case, the correlation coefficient is calculated as “1”.

  Next, the unnecessary sensor node discriminating means 125 determines that the correlation coefficient of all combinations of two sensor nodes 11 installed in the same installation room is greater than or equal to a predetermined regrouping threshold, for example, “0.9” or greater. Check if it is. If the correlation coefficients of all sensor node combinations are equal to or greater than the re-grouping threshold, the sensor nodes 11 installed in the same installation room are grouped again as belonging to the same sensor node group. Correct (step S418).

  Here, for example, when the correlation coefficient as shown in FIG. 15 is obtained for the installation room “room A”, the calculated correlation coefficient is “1” for all combinations of sensor nodes. Since the re-grouping threshold value is, for example, “0.9” or more, the group is re-grouped as the same group to create the “sensor node A, sensor node B, and sensor node D” group.

  Note that the grouping in the sensor node regrouping step in step S418 is performed when further grouping is performed on the sensor nodes 11 that have already been grouped in the sensor node grouping step in step S3 in the flowchart of FIG. 5 which is the main process. An example is shown.

  That is, in the sensor node regrouping step in step S418, the correlation coefficient between the sensor information (human sensor information) related to each sensor node 11 grouped for each installed room is calculated again, and a predetermined regrouping is performed. Based on the result of comparison with the threshold value, the sensor node group is grouped again, and there is a possibility that grouping is further performed even in the same room.

  Next, the unnecessary sensor node discriminating means 125 executes the next process of S420 for each sensor node grouped again in the sensor node regrouping step of step S418 (step S419). Here, in the processing step for each sensor node group in step S419 for the sensor nodes grouped again, for example, “sensor node A, sensor node B, and sensor node D” of the first sensor node group, second The process of the next step S420 is executed in the order of “sensor node C” of the sensor node group.

  The unnecessary sensor node discriminating means 125 has the maximum average radio field intensity related to the radio field intensity information as an example of the communication environment information from among the sensor nodes 11 included in the sensor node group designated in the process step for each sensor node group in step S419. Only one sensor node 11 is selected as a sensor node 11 that needs to be installed, and the remaining other sensor nodes 11 are determined as sensor nodes 11 that do not need to be installed (step S420).

  For example, when the communication environment information (radio wave intensity information) of FIG. 2 is stored in the sensor information storage unit 122, among the three sensor nodes 11 constituting the first sensor node group, “sensor The average radio wave intensity of “Node A” is −30 dBm, the average radio wave intensity of “Sensor Node B” is −85 dBm, and the average radio wave intensity of “Sensor Node D” is −35 dBm. Therefore, for the first sensor node group, “sensor node A” having the maximum average radio wave intensity is selected as the sensor node 11 that needs to be installed, and the other “sensor node B” and “sensor node D” are unnecessary. Judged as a sensor node. Further, there is only one “sensor node C” in the second sensor node group, and it is selected as the sensor node 11 that needs to be installed.

  As described above, in the third embodiment, the sensor nodes 11 in the same installation room are further regrouped in step S418, and the sensor nodes are grouped again for each sensor node group. Among the communication environment information measured in each, one sensor node 11 that is the best communication environment is set as a sensor node that needs to be installed, and the remaining sensor nodes 11 that are not in the best communication environment are set as unnecessary sensor nodes. Judging.

  In other words, among the sensor nodes 11 that belong to the same sensor node group and measure similar sensor information, only one sensor node 11 having the maximum average radio wave intensity as the communication environment is set as the sensor node 11 that needs to be installed. The remaining sensor nodes 11 are determined to be removed as unnecessary sensor nodes 11. Therefore, it is possible to operate the watching system using a smaller number of sensor nodes 11 than in the case of the first embodiment shown in the flowchart of FIG.

  The configuration of the preferred embodiment of the present invention has been described above. However, it should be noted that such embodiments are merely examples of the present invention and do not limit the present invention in any way. Those skilled in the art will readily understand that various modifications and changes can be made according to a specific application without departing from the gist of the present invention.

DESCRIPTION OF SYMBOLS 1 Sensor node installation system 1A Sensor node installation system 11 Sensor node 12 Management server 12A Management server 13 Unnecessary sensor node display device 14 Room classification display device 111 Arbitrary sensor 112 Communication environment sensor 113 Transmission means 121 Reception means 122 Sensor information storage part 123 Sensor Node grouping unit 124 Grouping information storage unit 125 Unnecessary sensor node determination unit 126 Unnecessary sensor node determination rule storage unit 127 Room type determination unit 128 Room type determination rule storage unit S1 Sensor node installation step S2 Sensor information accumulation step S3 Sensor node grouping step S4 Unnecessary sensor node determination step S5 Unnecessary sensor node display step S6 Room type determination step S7 Room type determination result notification step S301 Sensor node I List acquisition step S302 Sensor node combination list acquisition step S303 Processing step S304 for each sensor node combination Sensor node combination human measurement measurement value acquisition step S305 Human measurement measurement value correlation coefficient calculation step S306 Sensor node grouping step S401 Installation room ID list acquisition step S402 Processing step S403 for each installation room ID node acquisition step S404 for each sensor node ID Processing step S405 for each sensor node ID Acquisition step list for unnecessary sensor node discrimination rule Step S406 Processing step for each unnecessary sensor node discrimination rule Step S407 Unnecessary sensor node discrimination evaluation step S408 Unnecessary determination step S409 Unnecessary determination step S410 in the same installation room ID all sensor nodes Resolution step S411 Installation room ID list acquisition step S412 Installation room ID processing step S413 Sensor node ID list acquisition step S414 Sensor node combination list acquisition step S415 Sensor node combination processing step S416 Combination sensor node human presence acquisition step S417 Correlation coefficient calculation Step S418 Sensor node regrouping step S419 Processing for each sensor node group Step S420 Non-necessity determination step other than maximum average radio wave intensity sensor node Step S601 Installation room ID list acquisition step S602 Processing for each installation room ID Step S603 Room type determination rule list acquisition step S604 Room type Processing step S605 for each discrimination rule Installation room ID corresponding sensor node acquisition step S606 Sensor node Corresponding sensor information acquisition step S607 Room type determination rule evaluation step S608 Room type determination rule conformity determination step T101 Sensor node ID
T102 Type T103 Measurement value T104 Measurement date and time T201 Sensor node ID
T202 Installation room ID
T301 Evaluation formula T302 Weight T303 Evaluation result T401 Evaluation formula T402 Room type

Claims (10)

A sensor node installation system for determining whether or not it is necessary to install a plurality of sensor nodes to be installed in a residence where the inhabited residents live.
A sensor node that transmits sensor information that measures information for watching and communication environment information that measures the status of the communication environment; and
Based on the sensor information and the communication environment information transmitted from each of the plurality of sensor nodes installed in the residence, it is unnecessary to determine a sensor node that does not need to be installed from the plurality of sensor nodes. A management server that outputs as a sensor node;
A sensor node installation system comprising: an unnecessary sensor node display device that displays the unnecessary sensor node output from the management server. The management server
Based on the result of evaluating the correlation coefficient between the sensor information measured at each of the plurality of installed sensor nodes and the communication environment information using an evaluation formula that is predetermined as an unnecessary sensor node discrimination rule, The sensor node installation system according to claim 1, further comprising: an unnecessary sensor node determination unit configured to determine the unnecessary sensor node that does not need to be installed from the plurality of installed sensor nodes. The management server
Sensor node grouping means for grouping the plurality of sensor nodes installed based on the correlation coefficient between the sensor information measured in each of the plurality of installed sensor nodes as a sensor node group for each installed room; ,
For each sensor node group grouped by the sensor node grouping means, a correlation coefficient between the sensor information measured at each sensor node and the communication environment information are determined in advance as unnecessary sensor node determination rules. The sensor node installation system according to claim 1, further comprising: an unnecessary sensor node determination unit that determines the unnecessary sensor node based on a result of evaluation using an expression. The management server
Between the sensor information of each of the sensor nodes grouped for each room in which the plurality of sensor nodes installed based on the correlation coefficient between the sensor information measured at each of the plurality of sensor nodes installed Sensor node grouping means for regrouping as a sensor node group based on the result of comparing the correlation coefficient of
For each of the sensor node groups grouped by the sensor node grouping means, among the communication environment information measured in each sensor node, the sensor node that is the best communication environment is the sensor node that needs to be installed, and the best 2. The sensor node installation system according to claim 1, further comprising: an unnecessary sensor node determination unit configured to determine the remaining sensor node that is not in the communication environment as the unnecessary sensor node. The management server
Based on the sensor information measured in each of the sensor nodes grouped for each room by the sensor node grouping means, using a predetermined evaluation formula as a room type determination rule and a room type corresponding to the evaluation formula The sensor node installation system according to claim 3, further comprising room type determination means for determining a room type in which each of the sensor nodes is installed. A sensor node installation method for determining whether or not it is necessary to install a plurality of sensor nodes to be installed in a residence where the inhabited residents live.
Sensor node transmission step for transmitting sensor information for monitoring information and communication environment information for measuring the status of the communication environment from each of the plurality of installed sensor nodes;
A sensor information storage step for storing the sensor information and the communication environment information transmitted from each of the plurality of sensor nodes in the sensor node transmission step;
An unnecessary sensor node determining step of determining, as an unnecessary sensor node, a sensor node that does not need to be installed from among the plurality of sensor nodes based on the sensor information and the communication environment information stored in the sensor information storage step. A sensor node installation method comprising: The unnecessary sensor node determining step includes:
Based on the result of evaluating the correlation coefficient between the sensor information accumulated in the sensor information accumulation step and the communication environment information using an evaluation formula determined in advance as an unnecessary sensor node discrimination rule, a plurality of installed The sensor node installation method according to claim 6, wherein among the sensor nodes, a sensor node that does not need to be installed is determined as an unnecessary sensor node. A sensor node grouping step of grouping a plurality of installed sensor nodes as sensor node groups for each installed room based on the correlation coefficient between the sensor information stored in the sensor information storage step. ,
The unnecessary sensor node determining step includes:
For each of the sensor node groups grouped in the sensor node grouping step, a correlation coefficient between the sensor information and the communication environment information in each of the sensor nodes accumulated in the sensor information accumulation step are determined as unnecessary sensor nodes. The sensor node installation method according to claim 6, wherein the unnecessary sensor node is determined based on a result of evaluation using a predetermined evaluation formula as a determination rule. Correlation between the sensor information related to each of the sensor nodes grouped for each room in which the plurality of sensor nodes installed based on the correlation coefficient between the sensor information stored in the sensor information storage step is grouped A sensor node grouping step for regrouping the number as a sensor node group based on the result of comparing the number with a predetermined regrouping threshold;
The unnecessary sensor node determining step includes:
For each of the sensor node groups grouped in the sensor node grouping step, the sensor node that is the best communication environment is installed among the communication environment information in each of the sensor nodes accumulated in the sensor information accumulation step. The sensor node installation method according to claim 6, wherein the sensor node is determined as a necessary sensor node, and the remaining sensor nodes that are not in the best communication environment are determined as the unnecessary sensor nodes. Based on the sensor nodes grouped for each room in the sensor node grouping step and the sensor information accumulated in the sensor information accumulation step, an evaluation formula predetermined as a room type determination rule and the evaluation formula The sensor node installation method according to claim 8, further comprising a room type determination step of determining a room type in which each of the sensor nodes is installed using a room type.

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