JP2008059160A - Sensor node system, method, terminal and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a sensor node system, method, terminal and program for controlling the behavior of a sensor node in each area based on the correlation between a plurality of areas. <P>SOLUTION: In a sensor network composed of numerous sensor nodes, a terminal that investigates all the areas calculates context on the basis of sensing information available at the representative sensor node of a representative area. Next, in order to obtain more detailed information according to the context calculated, the terminal determines sensing methods for use in the representative area and in the areas related to the representative area. Next the terminal notifies the corresponding sensor nodes of the determined sensing methods. Each of the sensor nodes receives this notification and determines an operating method regarding whether or not it operates according to the notification received. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a sensor network technology, and more particularly to a sensing technology based on correlation between areas.

  Conventionally, a sensor node control method according to sensing information has been proposed as one method of sensor network technology (see, for example, Patent Document 1). In this method, each sensor node has a sensor with low power consumption and a sensor with high power consumption. Each sensor node always measures with a sensor with low power consumption, and only when the measured result exceeds a predetermined threshold, it is measured with a sensor with high power consumption.

  For example, in a sensor network for investigating the relationship between traffic volume and environmental pollution, a case where a sensor with low power consumption is a noise sensor and a sensor with high power consumption is a particulate sensor will be described. In this case, when the measured value by the noise sensor becomes equal to or higher than a predetermined value, that is, when the traffic volume is large, the particulate matter sensor measures the exhaust substances from the automobile such as NOx.

In Patent Document 1, there is an effect that the power consumption is reduced by not always operating a sensor with large power consumption by the control method as described above.
JP 2005-208719 A

However, the sensor node control method disclosed in Patent Document 1 has a problem in that the behavior of the sensor node in each area is not controlled based on the relationship between a plurality of areas.
Therefore, although the power consumption is small, a plurality of sensors with low power consumption always operate in a plurality of areas, so that there is a problem that the power consumption as a sum of the sensors increases.

  In addition, when the measurement result exceeds a threshold as a result of measurement in a certain area, it is possible to perform measurement with a sensor with high power consumption of the same sensor node associated in advance. Since sensors in a plurality of areas do not operate, there is a problem that measurement in a more detailed wide area is not possible.

  The present invention has been made in view of such circumstances, and an object of the present invention is to provide a sensor node system, method, terminal, and program for controlling the behavior of a sensor node in each area based on the relationship between a plurality of areas. Is to provide.

  The present invention has been made to solve the above-mentioned problems, and the invention according to claim 1 is a sensor node system in which a sensor node associated with a zone and a terminal are connected via a network, Sensing information including a zone, a zone information storage means in which a zone and a related zone that is a zone related to the zone are stored in association with each other, a zone, a sensor type, and a measurement result measured by the sensor type Sensing information receiving means for receiving from the sensor node, context calculation means for detecting semantic information by detecting whether a sensor type and a measurement result of the received sensing information satisfy a determination condition, and the context Sensing rule determination for extracting related areas from the area information storage means based on the semantic information detected by the calculation means A sensing rule transmitting means for transmitting a sensing rule including the extracted related area to the sensor node, the sensor node receiving the sensing rule from the terminal, and the received Sensing information processing means for measuring based on a sensing rule.

  The invention according to claim 2 is a sensor node system in which a sensor node and a terminal associated with a zone are connected via a network, and the terminal is a zone and a related zone that is a zone related to the zone. Area information storage means for storing association information indicating the positional relationship between the area and the related area in advance, and a value measured by the sensor node and a predetermined condition. Detailed information acquisition rule storage means in which semantic information detected by comparison and relevance information to be measured when the semantic information is detected are stored in association with each other, an area, a sensor type, and the sensor type Sensing information receiving means for receiving sensing information including a measurement result measured by the sensor node, a sensor type and a measurement result of the received sensing information Context detection means for detecting semantic information by detecting whether or not the determination condition is satisfied, and extracting the relevance information from the detailed information acquisition rule storage means based on the semantic information detected by the context calculation means, Sensing rule determining means for extracting a related area from the area information storage means based on the extracted relevance information and the area of the received sensing information; and transmitting a sensing rule including the extracted related area to the sensor node. Sensing rule transmitting means, wherein the sensor node has receiving means for receiving the sensing rule from the terminal, and sensing information processing means for measuring based on the received sensing rule. It is a sensor node system.

  According to a third aspect of the present invention, there is provided a sensor in which the terminal stores semantic information and an attribute value that is information for controlling the sensor when the semantic information is detected in association with each sensor in advance. Type information storage means, the context calculation means extracts attribute values for each sensor from the sensor type information storage means based on the detected semantic information, and the sensing rule transmission means is the extracted The attribute value included in the sensing rule is transmitted to the sensor node, and the sensing information processing means measures based on the attribute value of the received sensing rule. It is a sensor node system described in.

  According to a fourth aspect of the present invention, there is provided a determination condition for the terminal to detect the semantic information, which is predetermined based on the semantic information, the sensor type, and the measurement result measured by the sensor of the sensor type. Includes a context calculation rule storage unit that is stored in association with each other, and the context calculation unit determines the determination condition of the context calculation rule storage unit based on the sensor type and the measurement result of the received sensing information. The semantic information is detected by detecting whether or not the information is satisfied, and extracting semantic information associated with the detected determination condition from the context calculation rule storage unit. It is a sensor node system of description.

  According to a fifth aspect of the present invention, the terminal measures traffic of sensing information received from the sensor node, and limits the amount of communication transmitted by the sensor node based on the measured traffic. Sensing information transmission rule determining means for selecting the sensing information transmission rule, and the sensing rule transmission means includes the sensing information transmission rule in the sensing rule and transmits the sensing information to the sensor node. 5. The sensor node according to claim 1, further comprising: a sensing information transmitting unit configured to transmit the sensing information based on a sensing information transmission rule included in the received sensing rule. 6. System.

  According to a sixth aspect of the present invention, the terminal and the sensor node are connected via a base station, and the base station measures traffic of sensing information received from the sensor node; A sensing information transmission rule determination unit that selects a sensing information transmission rule for limiting the amount of communication transmitted by the sensor node based on the measured traffic, and the generated sensing information transmission rule is included in the sensing rule. 6. The sensor node system according to claim 1, further comprising a beacon signal transmission unit configured to transmit to the sensor node.

  The invention according to claim 7 is a method used in a sensor node system in which a sensor node associated with an area and a terminal are connected via a network, and the terminal uses the area information storage method, A process in which a related area, which is an area related to the area, is stored in association with each other in advance, and a sensing information receiving method receives sensing information including the area, a sensor type, and a measurement result measured by the sensor type as the sensor node. Sensing information receiving process received from the context, the context calculating method detects the semantic information by detecting whether the sensor type and the measurement result of the received sensing information satisfy the determination condition, and the sensing The rule determination method determines the related area based on the semantic information detected by the context calculation method. A sensing rule determination process extracted from the information storage method, and a sensing rule transmission method includes a sensing rule transmission process in which the sensing rule including the extracted related area is transmitted to the sensor node, and the sensor node receives A sensor node system method, characterized in that a method includes a reception process of receiving the sensing rule from the terminal, and a sensing information processing method of sensing based on the received sensing rule. is there.

  The invention according to claim 8 is a terminal connected via a network to a sensor node associated with an area, and the area and an associated area that is an area related to the area are stored in advance in association with each other. Area information storage means, sensing information receiving means for receiving sensing information including the area, sensor type, and measurement result measured by the sensor type from the sensor node; sensor type and measurement result of the received sensing information; Context calculation means for detecting semantic information by detecting whether or not the determination condition is satisfied, and sensing rule determination means for extracting a related area from the area information storage means based on the semantic information detected by the context calculation means And a sensing rule that transmits a sensing rule including the extracted related area to the sensor node. And Le transmitting unit, a terminal, characterized in that it comprises a.

  The invention according to claim 9 is an area in which an area and a related area that is an area related to the area are stored in association with a computer connected to a sensor node associated with the area via a network. Information storage means, sensing information receiving means for receiving sensing information including the area, sensor type, and measurement result measured by the sensor type from the sensor node; sensor type and measurement result of the received sensing information; Context calculation means for detecting semantic information by detecting whether or not a determination condition is satisfied, and sensing rule determination means for extracting a related area from the area information storage means based on the semantic information detected by the context calculation means Sensing to transmit a sensing rule including the extracted related area to the sensor node A sensor node system program characterized thereby and rule sending means of the function.

  According to the present invention, it is possible to reduce the power consumption by controlling the behavior of the sensor node in each area based on the relationship between the plurality of areas.

  In addition, according to the present invention, by controlling the behavior of the sensor node in each area based on the relationship between a plurality of areas, other sensor nodes in the same area can be used together, and also occurred in the area. By setting an area that is easily affected by a disaster or the like as a measurement target, more detailed information can be obtained.

According to the present invention, in a sensor network composed of a large number of sensor nodes, a terminal that investigates the entire area calculates the context based on the sensing information at the representative sensor node in the representative area.
Next, the terminal determines a sensing method in the representative area and the area related to the representative area in order to obtain more detailed information according to the calculated context. Next, the terminal notifies the determined sensing method to each corresponding sensor node.
Each sensor node receives a notification and determines an operation method such as whether to operate according to the received notification.

  With this method, the power consumption of each sensor node can be reduced. The ability to reduce consumption is even more effective when there is concern about power consumption, such as when each sensor node is operated by a storage battery or the like.

  Note that when detailed sensing is performed based on the calculated context, traffic of sensing information transmitted from each sensor node may be enormous. In order to reduce the traffic, the traffic volume is measured, and based on the measured traffic volume, sensing information transmission rules such as aggregation and filtering of sensing information are determined in advance. Based on the rule, each sensor node transmits sensing information.

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a schematic block diagram showing a configuration of a sensor node system according to an embodiment of the present invention.
The sensor node system includes a terminal 1 that can simultaneously survey all areas, a base station 2 in each area, and a sensor node 3.
The terminal 1 and each base station 2 are connected via a network 4. The base station 2 and the sensor node 3 in the same area are connected via the network 5. The network 4 or the network 5 is a wired or wireless network.

Each of the terminal 1 and the base station 2 is uniquely identified in the network 4 by an identification number (for example, an IP address). In addition, the base station 2 and the sensor node 3 in each area are uniquely identified in the network 5 by an identification number such as an IP address.
Each sensor node 3 has one or a plurality of sensors.

  In FIG. 1, in area 1, sensing information from a plurality of sensor nodes 3 (1-1, 1-2, 1-M) is collected in the base station 2 (1), and sensing of the base station 2 (1) is performed. Information is collected in the terminal 1. Similarly, sensing information from the sensor node 3 for the area 2 to the area N is also collected in the terminal 1.

Here, the area and the sensor node 3 are respectively set in advance as representatives, and only the representative sensor node 3 in the representative area performs measurement using the sensor in the normal time, and the measurement result obtained by measurement. Is transmitted to the terminal 1 via the base station 2. The sensor nodes other than the representative sensor node in the representative area and the sensor node 3 in the non-representative area do not perform operations such as measurement using a sensor or transmission of a measurement result in a normal time.
In FIG. 1, area 1 is a representative area, and sensor node 3 (1-1) is a representative sensor node. In addition, the area 2 to the area M are non-representative areas, and the sensor nodes 3 (1-2, 1-M, 2-1 to 2-M, N-1 to NM) are non-representative sensor nodes.

In the embodiment, at the normal time, only the representative sensor node 3 in the representative area is monitoring. Therefore, since the sensor node 3 in the other area is not operating, the power consumption as a whole is small.
Here, when the terminal 1 detects, for example, a fire or the like by measurement of the representative sensor node 3 (1-1), not only the sensor node 3 (1-1) that is a representative sensor in the representative area but also a representative. The non-representative sensor node 3 in the area or the sensor node 3 in the non-representative area associated with the representative area also performs monitoring.
Thereby, in the case of a disaster such as a fire, more detailed information can be acquired by a plurality of sensor nodes 3 in a plurality of areas.
In the embodiment, the representative area and the representative sensor node are assumed to be determined in advance.

For example, as a description of the embodiment, a case will be described in which the sensor node system according to the present invention is used for a disaster situation survey that easily spreads to an adjacent area such as a fire.
For example, as the representative area, an area having a cooking room where a fire is likely to occur is set in advance as the representative area. In order to detect a fire, a temperature sensor is set in advance as a sensor of the representative sensor node.
The sensor node system monitors an area of a cooking chamber, which is a representative area, by a temperature sensor, which is a representative sensor node. During normal times when no fire is occurring, only the temperature sensor in the cooking chamber area performs monitoring, so the power consumption is small.

When terminal 1 detects the occurrence of a fire by monitoring this representative sensor node, terminal 1 should also use other sensor nodes in the same area, and also subject areas that are susceptible to fire. To obtain more detailed information.
For example, in a sensor node system, when a fire breaks out, the flame spreads over the area where the fire broke out and in the area in the horizontal direction. To investigate the.
In the following, the sensor node system will be described by taking as an example the case of using for fire investigation.

  Next, the configuration of the terminal 1, the base station 2, and the sensor node 3 of the sensor node system will be described with reference to FIG. Further, data registered in each storage unit in FIG. 2 will be specifically described with reference to FIGS. 3 to 5 which are data as an example.

First, the configuration of the terminal 1 will be described.
The context calculation rule registration unit 101 has a function of registering a context calculation rule that is data registered in advance for context calculation in the context calculation rule storage unit DB1. The context calculation rule is a rule that represents a correspondence between a context and a determination condition that the context has occurred.

The context calculation rule storage unit DB1 of FIG. 2 stores in advance a context calculation rule that is data for context calculation.
Specifically, in the context calculation rule storage unit DB1, determination conditions and semantic information are associated with each other and stored as a context calculation rule table T1. An example of the context calculation rule table T1 is shown in FIG.
In the context calculation rule table T1 of FIG. 3 (1), the fact that the search condition is 60 ° C. or higher with the temperature sensor and the semantic information in that case is fire is stored in association with each other.
Note that the determination conditions are conditions relating to sensor types and measurement results of sensing information, which will be described later, corresponding to each semantic information. In this case, the sensor type is a temperature sensor, and the condition regarding the measurement result is 60 ° C. or higher.

  That is, the semantic information is information indicating the situation by comparing a measured value obtained by a certain sensor with a predetermined condition. On the contrary, based on the information of the situation to be made meaning, the determination condition between the sensor and the measured value is determined in advance and stored in the context calculation rule storage unit DB1.

One sensor may be associated with a plurality of semantic information. A plurality of sensors may be associated with one piece of semantic information.
For example, the measurement result by the temperature sensor may be related to the semantic information of fire and the semantic information of comfort level.
Further, there is semantic information such as comfort level, and this semantic information may be determined based on the measurement results of the temperature sensor and the humidity sensor.
Note that the context calculation unit 132 described later may simultaneously detect two pieces of semantic information based on the information registered in the context calculation rule storage unit DB1.

  In the context calculation rule table T1, corresponding semantic information is extracted using a search condition as a search key. Therefore, “(search key)” is clearly indicated in the attribute column of FIG. 3 for explanation. Similarly, in each table of FIGS. 3 to 5, “(search key)” is shown in the attribute column used for search, but this is also for explanation. Specific search will be described later.

  The detailed information acquisition rule registration unit 102 of FIG. 2 has a function of registering a detailed information acquisition rule, which is data registered in advance for sensing rule calculation, in the detailed information acquisition rule storage unit DB2. The detailed information acquisition rule is a rule representing a correspondence between a context and a sensing method necessary for acquiring more detailed information corresponding to the context.

  The detailed information acquisition rule storage unit DB2 in FIG. 2 stores in advance a detailed information acquisition rule that is data for sensing rule calculation.

Specifically, the detailed information acquisition rule storage unit DB2 stores the semantic information, the association type and value, which are related area information, and the sensing target in association with each other as the detailed information acquisition rule table T2. An example of the detailed information acquisition rule table T2 is shown in FIG.
In the detailed information acquisition rule table T2 in FIG. 3 (2), the semantic information, the relation type of the related area, the value, and the sensing target are respectively the same as the fire and the position and the fire, the fire and the position and the adjacent (same floor). ) And fire, and fire, position, adjoining (higher floor), and fire.

For example, in the case of a fire, this means that the area where the fire occurred is the same area where the fire has occurred, the area that is adjacent to the same floor at the position, the area that is adjacent to the higher floor at the position , Is to monitor the fire.
Thus, based on the semantic information that is the context, for example, in the case of a fire, the flame spreads to the upper and lateral areas. Therefore, based on the context, information related to the related area is set in advance in the detailed information acquisition rule table T2.

The area information registration unit 103 in FIG. 2 has a function of registering area information, which is data registered in advance for sensing rule calculation, in the area information storage unit DB3. The area information is information indicating correspondence between a plurality of areas.
The correspondence between the areas is, for example, in the case of a fire, there is adjacency between the areas. In addition, there are similarities between areas such as environmental characteristics and human behavior characteristics.

In the area information storage unit DB3 of FIG. 2, area information that is data for sensing rule calculation is stored in advance.
Specifically, in the area information storage unit DB3, the area name, the related area name, the related type, and the value, which are related area information, are associated and stored in advance as an area information table T3. An example of the area information table T3 is shown in FIG.
In the area information table T3 of FIG. 4 (1), the area name, the area name information of the related area, the association type, and the value are the same as the position of the Makuhari Building 15th Floor Kitchen and the Makuhari Building 15th Floor Kitchen, respectively. Building 15th floor kitchen and Makuhari Building 15th floor cafeteria and location (same floor), Makuhari Building 15th floor kitchen and Makuhari Building 16th floor room and position (high floor), Makuhari Building 15th floor kitchen and Makuhari Building 14th floor It is stored in association with the room, position, and low (lower floor).

  The sensor type information registration unit 104 in FIG. 2 has a function of registering sensor type information, which is data registered in advance for sensing rule calculation, in the sensor type information storage unit DB4. Sensing information is information indicating a sensing target (what event is sensed) that can be investigated by each sensor type, and an attribute value of a sensing method of each sensor type according to each sensing target. The attribute value of the sensing method is, for example, a sensing sampling period.

  The sensor type information storage unit DB4 in FIG. 2 stores in advance sensor type information that is data for calculating sensing rules.

Specifically, the sensor type, sensing object, and attribute value are associated with each other and stored as a sensor type information table T4. A plurality of sensing targets and attribute values may be associated with each other and stored for one sensor type information. The attribute value is information on a sensor type unit and a sensing target unit, and is information on a sensing method. An example of the sensor type information table T4 is shown in FIG.
In the sensor type information table T4 in FIG. 4 (2), the sensor type, the sensing target, and the attribute value are the temperature sensor, the comfort level, and the sampling cycle of 1 / second, and the temperature sensor, the fire, and the sampling cycle of 10 times / second, respectively. , And a super-sensitive flame sensor, fire, and a sampling period of 5 times / second, are stored in association with each other.

  Thus, even if the sensor type is the same sensor type as the temperature sensor, the sensor type information table T4 can be set so that the sampling period as the attribute value is different depending on the difference in sensing target. Moreover, even if the same sensing object is fire, it can be set to perform measurement with a temperature sensor and measurement with an ultra-sensitive flame sensor.

  The sensor node information registration unit 105 in FIG. 2 has a function of registering sensor node information, which is data registered in advance for sensing rule calculation, in the sensor node information storage unit DB5. The sensor node information is information representing the sensor nodes existing in each area and the sensor type of the sensor node.

In the sensor node information storage unit DB5 of FIG. 2, sensor node information that is data for sensing rule calculation is stored in advance.
Specifically, in the sensor node information storage unit DB5, an area name, a sensor node, and a sensor type are associated and stored as a sensor node information table T5. A plurality of sensor nodes and sensor types may be stored in association with one area name. An example of the sensor node information table T5 is shown in FIG.
In the sensor node information table T5 of FIG. 4 (3), the area name, sensor node, and sensor type are stored in association with the 15th floor kitchen, the sensor node A, and the human sensor, respectively. A description of other information in FIG.

The sensing information receiving unit 131 in FIG. 2 has a function of receiving the sensing information acquired by each sensor node 3 from the base station 2. As an example, sensing information includes an area name, a sensor type, and a measurement result.
That is, the sensing information receiving unit 131 receives sensing information including a zone, a sensor type, and a measurement result measured by the sensor type from the sensor node 3.
In addition, the sensing information receiving unit 131 has a function of registering the received sensing information in the sensing information table T10 of the sensing information storage unit DB10. An example of the sensing information table T10 is shown in FIG.
In the sensing information table T10 in FIG. 5A, the area name, sensor type, and measurement result are registered in association with the 15th floor kitchen, the temperature sensor, and 70 ° C. in the Makuhari Building.

The context calculation unit 132 of FIG. 2 is based on the determination conditions and semantic information stored in advance in the context calculation rule storage unit DB1, and the area name, sensor type, and measurement result registered in the sensing information table T10. It has a function to calculate a context. Here, the context is information having information on area names and semantic information.
That is, the context calculation unit 132 detects the semantic information by detecting whether or not the sensor type and the measurement result of the received sensing information satisfy a predetermined condition.
In addition, the context calculation unit 132 has a function of registering the calculated context in the context table T11 of the context storage unit DB11.

Specifically, the context calculation unit 132 acquires the area name, sensor type, and measurement result registered in the sensing information table T10, and the context calculation rule storage unit DB1 based on the acquired sensor type and measurement result. Get semantic information from
For example, the context calculation unit 132 is a temperature sensor in which the sensor type acquired from the sensing information table T10 in FIG. 5A, the temperature sensor that is the measurement result, and 70 ° C. are the determination conditions of the context calculation rule storage unit DB1. By satisfying 60 ° C. or higher, the fire that is the semantic information is acquired from the context calculation rule storage unit DB1.

  Next, the context calculation unit 132 calculates a context by combining the acquired semantic information and the area name acquired from the sensing information table T10, and registers the calculated context in the context table T11 of the context storage unit DB11. .

  The context calculation executed by the context calculation unit 132 may be executed in response to the sensing information receiving unit 131 of the terminal 1 receiving the sensing information, or the sensing information receiving unit 131 of the terminal 1 may execute the calculation of the context. Instead of receiving sensing information, it may be executed at predetermined time intervals.

  The sensing rule determination unit 133 in FIG. 2 includes a context registered in the context storage unit DB11, a detailed information acquisition rule storage unit DB2, a zone information storage unit DB3, a sensor type information storage unit DB4, and a sensor node information storage unit DB5. It has a function of generating a sensing rule that is information indicating what kind of sensing is performed in which sensor node in which area based on information stored in advance.

Sensing rules are used to obtain detailed information on contexts and to reduce the power consumption of base stations and sensor nodes in each area, and what type of sensor in which sensor node in which area. This is a rule for controlling a sensor node including information on whether to measure with an attribute value such as a period.
Moreover, the sensing rule determination unit 133 has a function of registering the generated sensing rule in the sensing rule table T12 of the sensing rule storage unit DB12.

  The sensing rule determination unit 133 stores the detailed information acquisition rule so as to generate the optimum sensing rule for the purpose of acquiring detailed information of the context and reducing the power consumption of the base stations and sensor nodes in each area. Information is registered in advance in the part DB2, the area information storage part DB3, the sensor type information storage part DB4, and the sensor node information storage part DB5.

  An example sensing rule registered in the sensing rule table T12 is shown in FIG. In the sensing rule table T12 of FIG. 5 (3), the area name, sensor node, sensor type, attribute value, Makuhari Building 15th floor kitchen, sensor node B, temperature sensor, sampling cycle 10 times / second, etc. are recorded. Is done.

Note that the sensing rule shown in FIG. 5 (3) is based on the sensing information shown in FIG. 5 (1) and the context calculation unit 132 uses the area name as shown in FIG. It is a sensing rule generated by the sensing rule determining unit 133 based on the calculated context, which is a 15th floor kitchen in the Makuhari Building and whose semantic information is fire.
Here, since the context is a fire in the 15th floor kitchen of the Makuhari Building, as a sensing rule, the Makuhari Building 15th Floor Kitchen and the Makuhari Building 15th Floor Cafeteria where the area is adjacent to or next to the Makuhari Building 15th Floor Kitchen And the 15th floor room in Makuhari Building are selected, and the sensor type and its attribute value are selected to detect fire.
Detailed description of how the sensing rule determination unit 133 generates the sensing rule will be described later.

  Note that the sensing rule determination performed by the sensing rule determination unit 133 may be performed in response to the context calculation unit 132 of the terminal 1 calculating the context, or the context calculation unit 132 of the terminal 1 may execute the context. It may be executed at predetermined time intervals without depending on the calculation.

  The sensing rule transmission unit 134 of FIG. 2 has a function of transmitting the sensing rules generated by the sensing rule determination unit 133 and registered in the sensing rule storage unit DB 12 to the base station 2 every time the sensing rules are updated. Have.

  In the description of the embodiment, the sensing rule transmission unit 134 is described as transmitting the sensing rule to all sensor nodes 3 via the base station 2. For example, the terminal 1 in FIG. 1 transmits a sensing rule to all sensor nodes 3 in the area via the base stations 1, 2 and N in the areas 1, 2 and N.

Next, returning to the description of FIG. 2, the configuration of the base station 2 will be described.
The sensing rule receiving unit 201 has a function of receiving a sensing rule from the terminal 1 via the network 4 and transmitting the received sensing rule to a beacon signal transmitting unit 205 described later.
The sensing information relay unit 202 has a function of receiving sensing information from the sensor node 3 via the network 5 and transmitting the received sensing information to the terminal 1 via the network 4.
The traffic measurement unit 203 has a function of measuring traffic of sensing information received by the sensing information relay unit 202 from the sensor node 3.

The sensing information transmission rule determination unit 204 has a function of determining a sensing information transmission rule for an area where the base station 2 exists in accordance with the traffic measurement result measured by the traffic measurement unit 203. The sensing information transmission rule determination unit 204 has a function of transmitting the determined sensing information transmission rule to the beacon signal transmission unit 205.
The sensing information transmission rule is information for aggregation and filtering of sensing information acquired by the sensing information transmission unit 304 described later from the sensing information processing unit 303.

Here, the sensing information transmission rule is a rule for aggregation and filtering of sensing information for the purpose of reducing traffic of sensing information. An example of the information transmission rule will be described next.
The sensing information transmission rule determination unit 204 determines a sensing information transmission rule by selecting an information transmission rule from predetermined information transmission rules as described below.

Sensing information is aggregated as the first information transmission rule. Aggregation of sensing information is to collectively transmit a plurality of sensing information representing the same result as one sensing information.
For example, when the trend of sensing results between neighboring sensor nodes is the same, only sensing information from one specific sensor node among these sensor nodes is adopted, and a predetermined specific range within a specific range is adopted. Information including an instruction to be transmitted is transmitted to the sensor, and information including an instruction not to be transmitted is transmitted to the other sensors. The sensor node that has received this information receives information including an instruction to transmit or not, and transmits sensing information when detecting that information including an instruction to transmit has been received. By doing so, only a specific sensor node is transmitted in a specific range. This is a location aggregation.

In addition, for example, when similar sensing information is continuously generated in time, only the first acquired sensing information is adopted or only when there is a change in the measured value of the measured sensing information. Send information to send information. The sensor node that has received this information detects a change in the measured value, and transmits sensing information only when there is a change. By doing so, only the sensor whose measured value has changed is transmitted. This is a time aggregation.
For example, the above-described location aggregation or time aggregation information is adopted as sensing information.

As a second information transmission rule, there is filtering of sensing information. Sensing information filtering refers to sensing information to be transmitted only when a specific condition is satisfied.
For example, the sensing information is used only when the sensing information exceeds a predetermined threshold. Further, for example, only when the logical operation results of a plurality of sensing information satisfy a specific condition, the sensing information is used.
For example, information to be transmitted is transmitted only when a predetermined value is reached, and the sensor node that has received this information transmits the measured value only when the measured value is greater than or equal to the received value. .

The sensing information editing method at the sensor node 3 targets the following sensing information. The relay sensor node targets sensing information acquired by the sensor node itself and sensing information received from another sensor node.
A non-relay sensor node uses sensing information acquired by the sensor node itself as a sensing target.

  The beacon signal transmission unit 205 has a function of periodically delivering a beacon signal to all sensor nodes 3 in the area where each base station exists via the network 5. The beacon signal transmission unit 205 distributes the beacon signal including the sensing rule received from the sensing rule reception unit 201 and the sensing information transmission rule received from the sensing information transmission rule determination unit 204.

Next, the configuration of the sensor node 3 will be described.
The beacon signal receiving unit 301 has a function of receiving a beacon signal from the base station 2. Further, the beacon signal receiving unit 301 has a function of transmitting the received beacon signal to the sensing setting unit 302.

The sensing setting unit 302 has a function of receiving a beacon signal from the beacon signal receiving unit 301 and extracting a sensing rule and a sensing information transmission rule from the received beacon signal.
In addition, the sensing setting unit 302 sets and registers the sensing signal processing method of the sensing information processing unit 303 based on the extracted sensing rule, and the sensing information of the sensing information transmission unit 304 based on the extracted sensing information transmission rule. Set and register the editing method.

  In addition, the sensing setting unit 302 detects whether there is information specifying the sensor node 3 in the extracted sensing rule, and detects that there is information specifying the sensor node 3 , The operation of a sensing information processing unit 303 and a sensing information transmitting unit 304 described later is executed, and when it is not detected that there is information specifying the sensor node 3 of itself, the sensing information processing unit 303 and the sensing information described later are detected. It has a function of stopping the operation of the information transmission unit 304.

The sensing information processing unit 303 has a function of sensing the sensor based on the sensing signal processing method set and registered by the sensing setting unit 302.
In addition, the sensing information processing unit 303 has a function of transmitting sensing information that is a result of sensing to the sensing information transmitting unit 304.

  The sensing information transmission unit 304 receives the sensing information from the sensing information processing unit 303, edits the received sensing information based on the sensing information editing method set and registered by the sensing setting unit 302, and sets the edited sensing information as a base. It has a function of transmitting to the station 2 via the network 5.

  Note that the functions of the traffic measurement unit 203 and the sensing information transmission rule determination unit 204 of the base station 2 can be the functions of the terminal 1 instead of the functions of the base station 2. When these functions are the functions of the terminal 1, the sensing information transmission rule is transmitted from the terminal 1 to each sensor node 3 via the base station 2 in each area in the same manner as the terminal 1 transmits the sensing rule. Send.

  In addition, the sensor node 3 is intended for the sensor nodes 3 in all areas including the representative area. A representative sensor node 3 and a non-representative sensor node 3 exist in the representative area, and only a non-representative sensor node 3 exists in the non-representative area.

  Note that transmission / reception between the base station 2 and each sensor node 3 under the base station 2 has the following two cases depending on the positional relationship. The first case is a case of direct transmission / reception with a base station, and the second case is a case of transmission / reception via another sensor node by multi-hop communication between sensor nodes. In the second case, a sensor node that relays sensing information acquired by another sensor node is referred to as a “relay sensor node”, and a terminal sensor node that is not relayed is referred to as a “non-relay sensor node”.

  Next, a method for generating a sensing rule by the terminal 1 will be described in detail with reference to FIGS. 6 and 7. First, the operation in which the terminal 1 generates a sensing rule will be described in detail with reference to FIG.

First, the sensing information receiving unit 131 of the terminal 1 receives the sensing information of the representative area from the base station 2 of the representative area (step S710).
Next, the context calculation unit 132 calculates the context generated in the representative area based on the sensing information of the representative area received in step S710 and the context calculation rule registered in advance in the context calculation rule storage unit DB1. (Step S720).

  Next, the sensing rule determination unit 133 first determines the context calculated in step 720 and the detailed information acquisition rule and the area information stored in advance in the detailed information acquisition rule storage unit DB2 and the area information storage unit DB3. Based on the above, it is the information for deciding the sensing target of what kind of event is sensed that is necessary for obtaining more detailed information on the context. (Referred to as zone information) ”and“ sensing target information acquired in the representative zone and its related zone (referred to as sensing target information) ”are calculated (step S730).

  Next, the sensing rule determination unit 133 includes the related area information and sensing target information calculated in step S730, and the sensor type information and sensor stored in advance in the sensor type information storage unit DB4 and the sensor node information storage unit DB5. Based on the node information, the sensor node used in each area, the sensor type used in each sensor node, and the attribute value related to sensing are calculated. The calculation result is a sensing rule.

Next, referring to FIG. 7, the context calculation unit 132 and the sensing rule determination unit 133 of the terminal 1 generate sensing rules from the sensing information registered in the record of the sensing information table, and the generated sensing rules are used as the sensing rules. A method of registering in the table will be described in detail.
Here, in the description of FIG. 7, the case of fire detection will be specifically described using the information in the tables of FIGS. FIG. 7 is a diagram showing the relationship between the table name of each table in FIGS. 3 to 5 and the attribute (data item) of each table. In FIG. 7, in each table, the table name is written on the square frame, and the attributes of the table are written in the square frame.

  First, the context calculation unit 132 searches and acquires semantic information in which the sensor type attribute and the measurement result attribute of the sensing information table T10 satisfy the determination condition attribute of the context calculation rule table T1 from the context calculation rule table T1 (Step S1). S801).

Next, the context calculation unit 132 creates a record of the context table T11 by combining the area name attribute of the sensing information table T10 and the semantic information retrieved in step S801, and stores the area name and Semantic information is registered (steps S802 and S803).
For example, as shown in FIG. 5B, the context calculation unit 132 registers a context whose attribute name attribute is Makuhari Building 15th floor kitchen and whose semantic information attribute is fire in the context table T11.

Next, in step S802 and step S803, the context calculation unit 132 uses the previous sensing information table record in which the zone name and the sensor type are equal to the zone name and the sensor type of the current sensing information table T10. Delete all records registered in.
Note that the semantic information that is the search result in step S801 corresponds to the semantic information attribute of the context table T11.

Next, the sensing rule determination unit 133 searches the area information table T3 for an area name attribute that matches the area name attribute of the context table T11, so that the related area name, the related type, and the value of the related area are matched. Information that is a set is retrieved from the area information table T3 (step S811).
For example, since the area name attribute of the context table T11 is Makuhari Building 15th Floor Kitchen, the area name information of the related area, the related type, and the value are the same as the position of the Makuhari Building 15th Floor Kitchen and the Makuhari Building 15 respectively. The floor cafeteria, position and adjoining (same floor), Makuhari Building 16 floor room and position and high (high floor), and Makuhari Building 14 floor room, position and low (low floor) are searched from the area information table T3 (step) S811).

Next, the sensing rule determination unit 133 searches the detailed information acquisition rule table T2 for semantic information that matches the semantic information attribute of the context table T11, so that the relation type, value, and sensing target of the relevant related area are detected. Information that is a set is retrieved and acquired from the detailed information acquisition rule table T2 (step S812).
For example, since the semantic information attribute of the context table T11 is “fire”, the relationship type, value, and sensing target are the same as the position and the fire, and the position and the adjacent (same floor) from the detailed information acquisition rule table T2, respectively. And fire, and the position, adjacent (higher floor), and fire are acquired as search results (step S812).

  Next, from the information that is a combination of the related area name, the related type, and the value of the related area that the sensing rule determining unit 133 searches and acquires from the area information table T3 in step S811, the detailed information acquisition rule table in step S812. The name of the related area in which the related type and value match is extracted from the information that is a combination of the related type, value, and sensing target of the related area that is obtained by searching from T2 (step S813).

  For example, the area name information of the related area acquired by searching from the area information table T3 in step S811, the related type, and the value are the same as the position of the 15th floor kitchen and the position of the Makuhari Building 15th floor respectively. Related types retrieved from the detailed information acquisition rule table T2 in step S812 from the adjacent (same floor), Makuhari Building 16th floor room and position and high (high floor), and Makuhari Building 14th floor room and position and low (low floor). , Value, and sensing target are the same area and fire, the position and adjacent (same floor) and fire, and the position and adjacent (higher floor) and fire are related areas where the relationship type and value match As names, Makuhari Building 15th Floor Kitchen, Makuhari Building 15th Floor Cafeteria and Makuhari Building 16th Floor Living Room are extracted (step S813).

  On the other hand, the sensing rule determination unit 133 searches the sensor type information table T4 for sensor type attributes and attribute values that match the sensing target information of the related area acquired by searching from the detailed information acquisition rule table T2 in step S812. (Step S821).

  For example, since the sensing target information of the related area obtained by searching from the detailed information acquisition rule table T2 in step S812 is fire, as the sensor type attribute and attribute value matching the fire from the sensor type information table T4, The temperature sensor and the sampling cycle of 10 times / second, and the ultra-sensitive flame sensor and the sampling cycle of 5 times / second are retrieved and acquired (step S821).

  Next, the sensing rule determining unit 133 matches the area name of the sensor node information table T5 with the related area name extracted based on the detailed information acquisition rule table T2 and the area information table T3 in step S813, and the sensor The area name, the sensor node, and the sensor type that match the sensor type attribute obtained by searching from the sensor type information table T4 in step 821 in the node information table T5 are searched and acquired from the sensor node information table T5 ( Step S823).

  For example, the related area names extracted based on the detailed information acquisition rule table T2 and the area information table T3 in step S813 are Makuhari Building 15th Floor Kitchen, Makuhari Building 15th Floor Cafeteria, and Makuhari Building 16th Floor Room. The sensor type attributes retrieved from the sensor type information table T4 in 821 are the temperature sensor and the ultra-sensitive flame sensor, and the zone name, sensor node, and sensor type in which both the zone name and the sensor type match. Makuhari Building 15th Floor Kitchen and Sensor Node B and Temperature Sensor, Makuhari Building 15th Floor Kitchen and Sensor Node C and Ultra Sensitive Flame Sensor, Makuhari Building 15th Floor Cafeteria and Sensor Node B and Temperature Sensor, Makuhari Building 15th Floor Cafeteria, sensor node C, ultra-sensitive flame sensor, Makuhari Building 16th floor, sensor node B, temperature sensor, Makuhari Building 16th floor, Nsanodo C and highly sensitive flame sensors, searching from the sensor node information table T5 is obtained (step S823).

  Next, the sensing rule determination unit 133 searches the sensor name of the area name, sensor node, and sensor type retrieved from the sensor node information table T5 in step S823, and the sensor retrieved from the sensor type information table T4 in step S821. Based on the type attribute and attribute value sensor type, the area name, sensor node, sensor type, and attribute value are generated, and the generated area name, sensor node, sensor type, and attribute value are registered in the sensing rule table T12. (Step S824).

  The result of step S824 is, for example, a sensing rule table T12 shown in FIG.

Next, the operation of the sensor node system will be described with reference to FIG. In the figure, parts corresponding to those in FIG. 2 are denoted by the same reference numerals, and description thereof is omitted.
Here, the operation of the sensor node system immediately after the fire has occurred will be described.

First, the sensing information transmitting unit 304 of the representative sensor node 3 in a predetermined specific area transmits sensing information to the base station 2 (step S601).
For example, the sensor node 3 (1-1) in the area 1 that is the representative sensor node in the representative area in FIG. 1 transmits the sensing information. For example, the sensor node B in the Makuhari Building 15th Floor Kitchen transmits information that the area name, sensor type, and measurement result are the Makuhari Building 15th Floor Kitchen, Temperature Sensor, and 70 ° C. as sensing information.
At this stage, since the sensor node system has not detected a fire, the other sensor nodes in area 1 and the sensor nodes in other areas will be described as not transmitting sensing information.

  Returning to FIG. 8, the sensing information relay unit 202 of the base station 2 transmits the sensing information received from the sensor node 3 to the terminal 1 (step S602).

Next, the sensing information receiving unit 131 of the terminal 1 receives the sensing information from the base station 2, and transmits the received sensing information to the context calculation unit 132 via the sensing information storage unit DB10 (step S610).
Next, the context calculation unit 132 of the terminal 1 calculates the context based on the sensing information received from the sensing information reception unit 131 and the information stored in advance in the context calculation rule storage unit DB1, and the calculated context Is transmitted to the sensing rule determination unit 133 via the context storage unit DB11 (step S611).

  For example, in the sensor node system, when the context calculation unit 132 of the terminal 1 calculates the context, the sensor node 3 (1-1) in the area 1 that is the representative sensor node in the representative area in FIG. The sensor node B in the floor kitchen detects that a fire has occurred.

  Next, the sensing rule determination unit 133 of the terminal 1 receives the context received from the context calculation unit 132, the detailed information acquisition rule storage unit DB2, the zone information storage unit DB3, the sensor type information storage unit DB4, and the sensor node information storage unit DB5. Based on the information stored in advance, the sensing rule is determined, and the determined sensing rule is transmitted to the sensing rule transmission unit 134 via the sensing rule storage unit DB12 (step S612).

Next, the sensing rule transmission unit 134 of the terminal 1 transmits the sensing rule received from the sensing rule determination unit 133 to the base station 2 (step S613).
Here, the sensing rule transmitted to the base station 2 by the sensing rule transmission unit 134 of the terminal 1 is, for example, as shown in FIG. 5 (3), a plurality of area names and sensor nodes, a sampling period of the sensor nodes, and the like. Contains attribute values. In addition, the sensing rule is information that causes sensor nodes to operate in areas other than the representative sensor node in the representative area, such as sensor node 3 (2-2) in area 2 in FIG.

  Returning to FIG. 8, the sensing rule receiving unit 201 of the base station 2 that has received the sensing rule from the terminal 1 transmits the received sensing rule to the beacon signal transmitting unit 205 (steps S625 and S626).

On the other hand, based on the sensing information that the sensing information relay unit 202 of the base station 2 receives from the sensor node 3 in step S602, the traffic measurement unit 203 measures the traffic, and the measured traffic is sent to the sensing information transmission rule determination unit 204. Transmit (step S621, step S622).
The sensing information transmission rule determination unit 204 that has received traffic from the traffic measurement unit 203 determines a sensing information transmission rule based on the received traffic, and transmits the determined sensing information transmission rule to the beacon signal transmission unit 205 (step S623). , S624).

  The beacon signal transmission unit 205 of the base station 2 that has received the sensing rule transmitted from the sensing rule reception unit 201 and the sensing information transmission rule transmitted from the traffic measurement unit 203 receives the sensing rule and the sensing information transmission rule. Are transmitted to the sensor node 3 (step S631).

The beacon signal receiving unit 301 of the sensor node 3 that has received the beacon signal from the base station 2 transmits the received beacon signal to the sensing setting unit 302 (step S641).
The sensing setting unit 302 that has received the beacon signal from the beacon signal receiving unit 301 extracts a sensing rule and a sensing information transmission rule from the received beacon signal, and sets the extracted sensing rule in the sensing information processing unit 303 (step S651). In addition, the extracted sensing information transmission rule is set in the sensing information transmission unit 304 (step S652).

Thereafter, the sensing information processing unit 303 performs measurement by the sensor based on the set sensing rules, and transmits the measured information to the sensing information transmission unit 304 (step S661).
The sensing information transmission unit 304 that has received the information measured from the sensing information processing unit 303 transmits the information measured based on the set sensing information transmission rule to the base station 2 as sensing information (step S601).

For example, each sensor node 3 receives a sensing rule including attribute values such as a plurality of area names and sensor nodes, and a sampling period of the sensor node as shown in FIG. If there is an area name and a sensor node, the measurement is performed by the sensor, and the measurement result is transmitted to the terminal 1 via the base station 2.
For example, not only the representative area in FIG. 1 but also the sensor node 3 (2-2) in the area 2 is measured by the sensor, and the measurement result is transmitted as sensing information.

Thereafter, the terminal 1, the base station 2, and the sensor node 3 of the sensor node system repeat Step 601 to Step 661.
However, thereafter, for example, not only the representative sensor node of the representative area but also the sensor node specified by the area name and sensor node of the sensing rule transmits the sensing information to the terminal 1 via the base station 2.

  Thereafter, when it is detected that the fire is extinguished and all of the sensing information received by the terminal 1 does not satisfy the determination condition that the semantic information becomes a fire, the sensing rule that the terminal 1 measures only with the representative sensor in the representative area , To the sensor node 3 via the base station 2. Thereby, after that, only the representative sensor in the representative area is measured by the sensor, and the measured information is transmitted to the terminal 1 as sensing information. That is, it becomes the same state as before the occurrence of the fire.

  Thus, in the normal case, only the representative sensor node in the representative area of FIG. 1 operates, and when the sensor node system generates a fire due to the measurement of the representative sensor node in the representative area, it is related to the representative sensor node in the representative area. By operating the sensor nodes in the representative area or other areas as well, more detailed fire information can be detected.

As described above, according to the context calculated from the sensing information of the representative sensor node in the representative area, the following matters can be performed for all areas.
Since unnecessary sensing information acquisition and transmission / reception can be omitted, it is possible to reduce power consumption of base stations and sensor nodes in each area and unnecessary traffic of sensing information.
In addition, according to the context generated in the representative area, determine the area related to the representative area, the sensing area to be acquired in the representative area and the related area, and perform sensing according to this decision, More detailed information about the context can be obtained.

In the above description, the sensor node system according to the present invention has been described for the case of fire detection. However, the sensor node system according to the present invention is not limited to fire detection, and can be used in other ways.
Next, an application example of the sensor node system according to the present invention will be described.
In the description of the application examples, the parentheses at the end of the first line of the application examples indicate the types of correlation between the application examples and the corresponding areas.

(Application 1) Survey of disasters (eg fires) that can easily spread over a wide area (adjacent areas)
Areas where disasters are likely to occur are designated as representative areas (such as places where fires are likely to occur). Sensing is performed at the representative sensor node in the representative area. When the context of the occurrence of a disaster is calculated based on this sensing result, more detailed information can be obtained by using other sensor nodes in the same area together, and also making areas subject to disasters subject to investigation. . (This is the example described above.)

(Application 2) Investigation of each area when people travel around multiple areas (adjacency between areas)
The area where people first stay is designated as the representative area. When the presence sensor is detected by the human sensor in the representative area, an area that is likely to stay in the future due to movement from the representative area is calculated. Detailed information is obtained in the representative area and related areas. This method is effective for the following investigation, for example.
Survey of environmental information (temperature, humidity, noise, etc.) for each area for the purpose of improving the comfort of visitors. An investigation to track intruders for the purpose of improving security and crime prevention in banks and the like.

(Application 3) Investigation of damage occurrence prediction in each area due to natural disaster (similarity of environmental characteristics between areas)
If a disaster (for example, a landslide) occurs in A district due to bad weather, a similar disaster will occur in B district and C district. This is an assumption based on the similarity of environmental characteristics between areas (for example, the weak ground in the mountains and the flow of rivers), and areas A, B, and C are geographically adjacent. It is not necessary.
In this case, District A is the representative zone. Sensing is performed at the representative sensor node in the representative area. When the context of the occurrence of a disaster is calculated based on the sensing result, more detailed information is acquired by using other sensor nodes in the same area or by making the B and C areas to be investigated.

(Application 4) Investigation of traffic concentration (similarity in human behavior characteristics between areas)
If traffic concentration occurs in the A district, it is assumed that the traffic concentration also occurs in the B district and C district. This is an assumption based on human behavioral characteristics between areas (for example, city center, business district, etc.), and areas A, B, and C may not be geographically adjacent.
In this case, District A is the representative zone. Sensing is performed at the representative sensor node in the representative area. When the traffic concentration context is calculated based on the sensing result, more detailed information is acquired by setting the B and C areas as the survey targets.

As described above, in the area information storage unit DB3, the area, the related area that is the area related to the area, and the relevance information that indicates the positional relationship between the area and the related area are stored in advance. It is stored in association.
In the detailed information acquisition rule storage unit DB2, semantic information detected by comparing a value measured by the sensor node 3 with a predetermined condition, and relevance information measured when the semantic information is detected Are stored in advance in association with each other.

The sensing information receiving unit 131 receives sensing information including a zone, a sensor type, and a measurement result measured by a sensor of the sensor type from the sensor node 3.
The context calculation unit 132 detects semantic information in which the sensor type and the measurement result of the received sensing information satisfy the determination condition.

The sensing rule determination unit 133 extracts relevance information from the detailed information acquisition rule storage unit DB2 based on the semantic information detected by the context calculation unit 132, and the extracted relevance information and the area of the received sensing information Based on the above, the related area is extracted from the area information storage unit DB3.
The sensing rule transmission unit 134 transmits a sensing rule including the extracted related area to the sensor node 3.

In the sensor type information storage unit DB4, semantic information and attribute values that are information for controlling the sensor when the semantic information is detected are stored in association with each sensor in advance.
In addition, the sensing rule determination unit 133 extracts an attribute value for each sensor from the sensor type information storage unit DB4 based on the detected semantic information.
In addition, the sensing rule transmission unit 134 includes the extracted attribute value in the sensing rule and transmits it to the sensor node.

In the context calculation rule storage unit DB1, semantic information, a determination condition for detecting the semantic information predetermined based on the sensor type and the measurement result measured by the sensor of the sensor type are associated in advance. Is remembered.
The context calculation unit 132 detects semantic information by extracting from the context calculation rule storage unit DB1 semantic information in which the sensor type and the measurement result of the received sensing information satisfy the determination condition of the context calculation rule storage unit DB1. .

The traffic measurement unit 203 measures the traffic of sensing information received from the sensor node 3.
The sensing information transmission rule determination unit 204 selects a sensing information transmission rule for limiting the amount of communication transmitted by the sensor node 3 based on the measured traffic.
Moreover, the sensing information transmission means 304 transmits sensing information based on the sensing information transmission rule included in the received sensing rule.
The traffic measurement unit 203 and the sensing information transmission rule determination unit 204 may be included in the base station 2 or the terminal 1.

As described above, the present invention provides a representative network for acquiring more detailed information based on the context calculated from the sensing information at the representative sensor node in the representative area in a sensor network including a large number of sensor nodes. This is a method for controlling the behavior of a sensor node by determining an area where the sensor node exists and a sensing method in an area related to the area. With this method, the power consumption of each sensor node can be reduced.
The present invention is effective for, for example, investigating the situation of disasters (such as fires) that easily spread over a wide area. First, sensing is performed by a representative sensor node in an area where a disaster is likely to occur as a representative area.
If the context of the occurrence of a disaster is calculated based on this sensing result, other sensor nodes in the same area will be used in combination, and areas that are susceptible to disasters occurring in the area will also be subject to sensing. Detailed information can be acquired.

  The context calculation rule storage unit DB1, the detailed information acquisition rule storage unit DB2, the area information storage unit DB3, the sensor type information storage unit DB4, the sensor node information storage unit DB5, the sensing information storage unit DB10, the context storage unit DB11, and the sensing rule Each storage unit of the storage unit DB12 is a non-volatile memory such as a hard disk device, a magneto-optical disk device, or a flash memory, a storage medium that can only be read such as a CR-ROM, or a RAM (Random Access Memory). A volatile memory or a combination of these is assumed.

Note that the terminal 1, the base station 2, or the sensor node 3 in FIG. 1 may be realized by dedicated hardware, or may be realized by a memory and a microprocessor.
The terminal 1, the base station 2 or the sensor node 3 may be realized by dedicated hardware, and the terminal 1 and the base station 2 are configured by a memory and a CPU (central processing unit). Alternatively, the function may be realized by loading a program for realizing the function of the terminal 1, the base station 2 or the sensor node 3 into a memory and executing the program.

  The embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to this embodiment, and includes design and the like within a scope not departing from the gist of the present invention.

  The present invention is suitable for use in a sensor node system.

It is a block diagram which shows the structure of the sensor node system by one Embodiment of this invention. It is a block diagram explaining the detailed structure of a sensor node system. It is a 1st table figure which shows the information registered into the database as an example. It is a 2nd table figure which shows the information registered into the database as an example. It is a 3rd table figure which shows the information registered into the database as an example. It is explanatory drawing for demonstrating the operation | movement for producing | generating a sensing rule. It is explanatory drawing for demonstrating using the procedure which produces | generates a sensing rule. It is an operation | movement diagram for demonstrating operation | movement of the sensor node system by one Embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Terminal 2 Base station 3 Sensor node 4 Network 5 Network 101 Context calculation rule registration part 102 Detailed information acquisition rule registration part 103 Area information registration part 104 Sensor type information registration part 105 Sensor node information registration part 131 Sensing information reception part 132 Context calculation Unit 133 sensing rule determination unit 134 sensing rule transmission unit DB1 context calculation rule storage unit DB2 detailed information acquisition rule storage unit DB3 area information storage unit DB4 sensor type information storage unit DB5 sensor node information storage unit DB10 sensing information storage unit DB11 context storage unit DB12 Sensing rule storage unit T1 Context calculation rule table T2 Detailed information acquisition rule table T3 Area information table T4 Sensor type information table T5 Sensor node Reporting table T10 Sensing information table T11 Context table T12 Sensing rule table 201 Sensing rule receiving unit 202 Sensing information relay unit 203 Traffic measuring unit 204 Sensing information transmission rule determining unit 205 Beacon signal transmitting unit 301 Beacon signal receiving unit 302 Sensing setting unit 303 Sensing Information processing unit 304 Sensing information transmission unit

Claims (9)

A sensor node system in which a sensor node associated with an area and a terminal are connected via a network,
The terminal is
An area information storage means in which an area and a related area, which is an area related to the area, are stored in association with each other;
Sensing information receiving means for receiving sensing information from the sensor node including an area, a sensor type, and a measurement result measured by a sensor of the sensor type;
Context calculation means for detecting semantic information in which the sensor type and measurement result of the received sensing information satisfy a determination condition;
Sensing rule determining means for extracting a related area from the area information storage means based on the semantic information detected by the context calculating means;
Sensing rule transmitting means for transmitting a sensing rule including the extracted related area to the sensor node;
Have
The sensor node is
Receiving means for receiving the sensing rule from the terminal;
Sensing information processing means for measuring based on the received sensing rules;
A sensor node system comprising: A sensor node system in which a sensor node associated with an area and a terminal are connected via a network,
The terminal is
An area information storage means in which an area, an associated area that is an area related to the area, and association information indicating a positional relationship between the area and the associated area are stored in association with each other;
Details in which semantic information detected by comparing a value measured by the sensor node with a predetermined condition and relevance information measured when the semantic information is detected are stored in association with each other in advance Information acquisition rule storage means;
Sensing information receiving means for receiving sensing information from the sensor node including an area, a sensor type, and a measurement result measured by a sensor of the sensor type;
Context calculation means for detecting semantic information in which the sensor type and measurement result of the received sensing information satisfy a determination condition;
Relevance information is extracted from the detailed information acquisition rule storage means based on the semantic information detected by the context calculation means, and the related area is determined based on the extracted relevance information and the area of the received sensing information. Sensing rule determining means to extract from the information storage means;
Sensing rule transmitting means for transmitting a sensing rule including the extracted related area to the sensor node;
Have
The sensor node is
Receiving means for receiving the sensing rule from the terminal;
Sensing information processing means for measuring based on the received sensing rules;
A sensor node system comprising: The terminal is
Sensor type information storage means in which semantic information and attribute values that are information for controlling the sensor when the semantic information is detected are stored in association with each sensor type in advance.
Have
The context calculation means extracts an attribute value for each sensor type from the sensor type information storage means based on the detected semantic information,
The sensing rule transmitting means includes the extracted attribute value for each sensor type in the sensing rule and transmits the sensor value to the sensor node,
The sensing information processing means measures based on the attribute value of the received sensing rule,
The sensor node system according to claim 1 or 2, characterized by the above. The terminal is
A context calculation rule storage in which semantic information, determination conditions for detecting the semantic information determined in advance based on the sensor type and the measurement result measured by the sensor of the sensor type are stored in association with each other. means,
Have
The context calculation means detects semantic information by extracting from the context calculation rule storage means semantic information that the sensor type and measurement result of the received sensing information satisfy the determination condition of the context calculation rule storage means,
The sensor node system according to claim 1, wherein: The terminal is
Traffic measuring means for measuring traffic of sensing information received from the sensor node;
Sensing information transmission rule determining means for selecting a sensing information transmission rule for limiting the amount of communication transmitted by the sensor node based on the measured traffic;
Have
The sensing rule transmission means includes the sensing information transmission rule in the sensing rule and transmits it to the sensor node,
The sensor node is
Sensing information transmission means for transmitting the sensing information based on a sensing information transmission rule included in the received sensing rule,
Having
The sensor node system according to claim 1, wherein the sensor node system is configured as described above. The terminal and the sensor node are connected via a base station,
The base station is
Traffic measuring means for measuring traffic of sensing information received from the sensor node;
A sensing information transmission rule determination unit that selects a sensing information transmission rule for limiting the amount of communication transmitted by the sensor node based on the measured traffic;
Beacon signal transmitting means for including the generated sensing information transmission rule in the sensing rule and transmitting it to the sensor node;
The sensor node system according to claim 1, wherein the sensor node system includes: A method used in a sensor node system in which a sensor node associated with an area and a terminal are connected via a network,
The terminal is
A method in which an area information storage method stores an area and an associated area that is an area related to the area in advance;
Sensing information receiving method, the sensing information receiving process of receiving sensing information including the area, the sensor type and the measurement result measured by the sensor of the sensor type from the sensor node;

A context calculation process for detecting semantic information in which a sensor type and a measurement result of the received sensing information satisfy a determination condition;
Sensing rule determination method, a sensing rule determination process for extracting a related area from the area information storage method based on semantic information detected by the context calculation method;
A sensing rule transmission method, wherein the sensing rule transmission method transmits a sensing rule including the extracted related area to the sensor node;
Have
The sensor node is
A receiving method includes receiving a sensing rule from the terminal;
A sensing information processing method in which a sensing information processing method measures based on the received sensing rule; and
A sensor node system method comprising: A terminal connected via a network to a sensor node associated with a zone,
An area information storage means in which an area and a related area, which is an area related to the area, are stored in association with each other;
Sensing information receiving means for receiving sensing information from the sensor node including an area, a sensor type, and a measurement result measured by a sensor of the sensor type;
Context calculation means for detecting semantic information in which the sensor type and measurement result of the received sensing information satisfy a determination condition;
Sensing rule determining means for extracting a related area from the area information storage means based on the semantic information detected by the context calculating means;
Sensing rule transmitting means for transmitting a sensing rule including the extracted related area to the sensor node;
A terminal characterized by comprising: To a computer connected via a network with the sensor node associated with the area,
An area information storage means in which an area and a related area, which is an area related to the area, are stored in association with each other;
Sensing information receiving means for receiving sensing information from the sensor node including an area, a sensor type, and a measurement result measured by a sensor of the sensor type;
Context calculation means for detecting semantic information in which the sensor type and measurement result of the received sensing information satisfy a determination condition;
Sensing rule determining means for extracting a related area from the area information storage means based on the semantic information detected by the context calculating means;
Sensing rule transmitting means for transmitting a sensing rule including the extracted related area to the sensor node;
A sensor node system program characterized by causing

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