KR20120108626A - Method and system for node diagnosis based on sensor network - Google Patents

Abstract

PURPOSE: A sensor network based node diagnosis method and system thereof are provided to rapidly and effectively control a system by determining malfunction in a sensor and facilities. CONSTITUTION: A node diagnosis server(120) receives sensing data from one or more sensors(110). The node diagnosis server analyzes packets by reconstructing the packets according to the set data. The node diagnosis server determines malfunction in the sensors or a control target apparatus. The node diagnosis server creates context information in target services. The node diagnosis server transmits alarm messages. The alarm message includes current state information for the sensor and control target apparatus. [Reference numerals] (AA) Wired and wireless communication network

Description

Method and system for node diagnosis based on sensor network

The present invention relates to a method and a system for diagnosing a node based on a sensor network, and more particularly, to a sensor or a driving device (hereinafter, mixed with a facility) present in each node in a sensor network based system including a USN (Ubiquitous Sensor Network). By quickly and accurately determining whether or not a malfunction is performed, the middleware to which the technology of the present invention is applied can be exhibited in a large system in which a plurality of sensors are installed.

The sensor network refers to a configuration of various sensors as a network, and includes a wireless sensor network (WSN) and a ubiquitous sensor network (USN).

The technology related to sensor network has the following features.

First, it is embedded wireless network technology that applies to all things including RFID and WSN.

Second, network technologies including wireless personal area networks (WPANs) and ad-hoc networks are being activated.

Third, software platforms include TinyOS, Nano Qplus, Contiki, LiteOS, and support various standards and protocols.

Fourth, it supports standards including IETF's 6LoWPAN, ROLL, CoRE and ZigBee, Wireless HART, and ISA 100.

Based on these features, the sensor network includes a sensor node, which is a small wireless transceiver equipped with a processor for processing the collected information, and a sink node that collects it and transmits it to the outside (remote location). It is developed and activated for various purposes in the fields of science, medicine, military and commerce with the basic purpose of automated remote information collection.

However, the development direction of the sensor network system up to now has been mostly related to data sharing, aggregation and processing methods among sensors processing heterogeneous data.

Therefore, when a sensor malfunctions and receives wrong sensing data, the sensor is detected by a malfunction detection module mounted separately for each sensor. However, such a separate malfunction detection module provides a total system construction cost of a sensor and a sensor network including the same. Increasing maintenance costs were burdensome for users who wanted to install and operate the system. This increase in cost is exacerbated as the number of sensors constituting each node increases.

In addition, in case that abnormal condition occurs temporarily according to the operation of other driving device under the condition that the sensor operates normally, the system judges the detected data as legitimate data (since the sensor operates normally), There was a problem that control is not achieved efficiently.

In order to solve the above problems, when the abnormal situation is detected from the sensor, the present invention analyzes the detection data of the sensor to determine whether the sensor and equipment malfunction, and accordingly the system quickly and efficiently An object of the present invention is to provide a method and system for diagnosing node based sensor network.

In addition, the present invention is a method of determining the malfunction of the sensor and the facility, by applying a separate malfunction detection module, by judging by the analysis of the detection data transmitted from the sensor, to minimize the installation cost and maintenance cost of the system An object of the present invention is to provide a sensor network-based node diagnosis method and system.

In particular, the indoor environment control method and system according to the present invention has an object to be easy to apply to the system already installed.

In order to achieve the above object, a sensor network-based node diagnosis method according to the present invention, a) receiving the sensed data from at least one sensor included in the sensor network and reconfiguring for each set data; b) analyzing the reconstructed data to determine whether there is a malfunction of at least one of the sensor and the device; And c) generating contextual information for each service according to the determination result and transmitting a notification message including current status information of at least one of the corresponding sensor and the device.

In an embodiment, the step a) may include a-1) receiving the sensed data; a-2) storing the received sensing data in a database; And a-3) reconfiguring the received sensed data based on the configured packet.

In an embodiment, the step c) may include: c-1) generating situation information including corresponding error information when at least one of the sensor and the device is malfunctioning as a result of the determination; c-2) checking a service to which the generated situation information is provided; And c-3) providing error information corresponding to the identified service. For example, step c) may further include deleting corresponding sensing data when at least one of the corresponding sensor and the device is malfunction.

In an embodiment, the step b) may include b-1) calculating a sensing value, a block average value, and a sector average value by analyzing the sensed data; B-2) the difference between the sector average value and the block average value is smaller than the first reference value, the difference between the previous sensing value and the current sensing value is greater than the second reference value, and the difference between the block average value and the previous sensing value is greater than the third reference value, If the difference between the current sensing value and the sector average value is smaller than the fourth reference value, the method may include determining that the sensor returns to normal after malfunctioning.

In another embodiment, the step b) may include b-1) calculating a sensing value, a block average value, and a sector average value by analyzing the sensed data; And b-2) the difference between the sector average value and the block average value is smaller than the first reference value, the difference between the previous sensing value and the current sensing value is smaller than the second reference value, and the difference between the current sensing value and the block average value is larger than the fifth reference value. In this case, the method may include determining that the sensor has malfunctioned. For example, step b-2) may further include determining that the corresponding sensor is normally operated when the difference between the current sensing value and the block average value is smaller than the fifth reference value.

In another embodiment, the step b) may include b-1) calculating a sensing value, a block average value, and a sector average value by analyzing the sensed data; And b-2) the difference between the sector average value and the block average value is smaller than the first reference value, the difference between the previous sensing value and the current sensing value is greater than the second reference value, and the difference between the block average value and the previous sensing value is smaller than the third reference value. This may include determining that the sensor has malfunctioned.

In another embodiment, the step b) may include b-1) calculating a sensing value, a block average value, and a sector average value by analyzing the sensed data; B-2) the difference between the sector average value and the block average value is smaller than the first reference value, the difference between the previous sensing value and the current sensing value is greater than the second reference value, and the difference between the block average value and the previous sensing value is greater than the third reference value, If the difference between the current sensing value and the sector average value is greater than the fourth reference value, the method may include determining that the corresponding sensor has malfunctioned.

In another embodiment, the step b) may include b-1) calculating a sensing value and a block average value by analyzing the sensed data; And b-2) when the difference between the sector average value and the block average value is greater than the first reference value, requesting control of the controlling device.

In another embodiment, the step b) may include b-1) calculating a sensing value and a block average value by analyzing the sensed data; And b-2) when the difference between the previous sensing value and the current sensing value is greater than the sixth reference value and the difference between the current sensing value and the block mean value is greater than the seventh reference value, determining that the corresponding sensor has malfunctioned. have.

In another embodiment, the step b) may include b-1) calculating a sensing value and a block average value by analyzing the sensed data; And b-2) when the difference between the previous sensing value and the current sensing value is smaller than the sixth reference value and the difference between the previous block average value and the current block average value is smaller than the eighth reference value, determining that the control target device is malfunctioning. It may include.

In another embodiment, the step b) may include b-1) calculating a sensing value, a block average value, and a sector average value by analyzing the sensed data; b-2) The difference between the previous sensing value and the current sensing value is greater than the sixth reference value, the difference between the current sensing value and the current block average value is smaller than the seventh reference value, and the difference between the block average value and the sector average value is greater than the ninth reference value. In this case, the method may include maintaining control of the control target device. For example, the step b-2 may further include stopping the control of the control target device when the difference between the block average value and the sector average value is smaller than a ninth reference value.

In addition, the sensor network-based node diagnostic system according to the present invention, at least one sector, at least one block included in the sector, at least one sensor and control target device included in the block; And receiving the sensed data from the at least one sensor and reconstructing and analyzing the packet for each set data and determining whether there is a malfunction of at least one of the corresponding sensor and the control target device to generate contextual information for each target service to be provided. And a node diagnosis server transmitting a notification message including current status information of at least one of the devices.

In an embodiment, the node diagnosis server may include: a data management module configured to process sensed data transmitted from the sensor and to reconfigure a packet by calling set data; An information storage module for storing sensed data processed by the data management module and setting and storing data to be used; A situation information providing module for converting the packet reconstructed by the data management module into situation information; A situation analysis module for determining a target service to be provided by analyzing the situation information converted by the situation information providing module; And a service provision module for executing the target service determined by the situation analysis module. For example, if it is determined that at least one of the sensor and the control target device malfunctions, the service providing module may request to delete the sensed data stored in the information storage module. As another example, when it is determined that the corresponding sensor and the control target device are normally operated, the service providing module may request to control the corresponding control target device based on the sensed data.

In one embodiment, the packet is the ID of the sensor, the ID of the block in which the sensor is installed, the ID of the sector including the block, the type of data collected by the sensor, the data currently sensed (sensing) by the sensor, Among the data previously sensed by the sensor, the average value of current sensing data of each sensor included in the same block, the average value of previous sensing data of each sensor included in the same block, and the average sensing value of the sensors included in the same block. It can be reconstructed including at least one.

In one embodiment, the status information is packet information, status determination, whether the error has occurred, whether the sensor occurs, whether or not in the facility, whether the equipment is running, the ID of the equipment, the name of the equipment, the sector of the It may include at least one of a management field, management standard information and related data in the corresponding field.

In an embodiment, the schema of the database managed by the node diagnosis server may include at least one of a current sensing information table, a management reference information table, a device table, a data type table, and a control table.

By the above solution means, even if there is no malfunction detection module inside the sensor and the facility, it is possible to quickly and accurately determine whether the sensor and / or the facility malfunction by analyzing the detection data transmitted from the sensor.

Therefore, even in the case of using a relatively low-cost sensor, it is not only effective to achieve sufficient control of environmental factors in the room efficiently, but also to minimize the system construction cost and maintenance cost.

In particular, the sensor network-based node diagnosis method and system according to the present invention has an advantage that it is easy to apply to a system that is already installed. In other words, the effect of the present invention can be sufficiently obtained by updating a program of an existing system.

In addition, by preventing unnecessary control is performed by a temporary abnormal situation, it is possible to efficiently manage resources as well as to prevent unnecessary waste of energy in advance.

In addition, the present invention can be easily applied to various network systems as well as the embodiments described in the present invention. For example, it can be applied to indoor air conditioning systems such as offices, greenhouses and factories, and can be applied to various fields such as remote security systems, remote control systems, and intelligent transportation systems.

Therefore, there is an effect of improving the competitiveness in the field of various remote monitoring system, including the sensor network-based system field.

1 is a flowchart illustrating an embodiment of a method for diagnosing a node based on a sensor network according to the present invention.
2 is a flowchart for explaining a specific embodiment of FIG. 1.
FIG. 3 is a flowchart for explaining an exemplary embodiment of step S120 of FIG. 1.
FIG. 4 is a flowchart for explaining another exemplary embodiment of step S120 of FIG. 1.
5 is a configuration diagram illustrating an embodiment of a sensor network based node diagnosis system according to the present invention.
FIG. 6 is a hierarchical diagram illustrating an embodiment of the node diagnosis server of FIG. 5.
FIG. 7 is a flowchart illustrating an operation of a configuration included in the “FDCM Layer” of FIG. 6.
FIG. 8 is a diagram illustrating an embodiment of a packet data configuration used in a sensor network-based node diagnosis method and system according to the present invention.
9 is a view for explaining an embodiment of the configuration of the context information used in the sensor network-based node diagnosis method and system according to the present invention.
FIG. 10 is a diagram illustrating an embodiment of a database schema used in a sensor network-based node diagnosis method and system according to the present invention.
FIG. 11 is a diagram illustrating an embodiment of a class diagram used in a method and a system for diagnosing a node based on a sensor network according to the present invention.

Examples of a method and a system for diagnosing a node based on a sensor network according to the present invention can be variously applied.

1 is a flowchart illustrating an embodiment of a method for diagnosing a node based on a sensor network according to the present invention. Hereinafter, the sensor network-based node diagnosis method according to the present invention may be performed by the node diagnosis server 200 shown in FIG. 5.

Referring to FIG. 1, in the sensor network-based node diagnosis method according to the present invention, sensing data is received from at least one sensor included in the sensor network and reconfigured for each set data (step S110). For example, the sensed data may be reconstructed corresponding to FIGS. 8 to 11.

The reconstructed data is analyzed to determine whether there is a malfunction of at least one of the corresponding sensor and the device (step S120). In one embodiment, determining whether a malfunction of the sensor and the device can be performed by comparing with the management standard information set based on the field to which the system is applied. For example, the management standard information may include a management target item (temperature, humidity, air component, etc.) and a management range (steady state determination range).

According to the determination result, the service-specific situation information is generated and a notification message including the current state information of at least one of the corresponding sensor and the device is transmitted (step S130). For example, the notification message may include normal operation information of the sensor and the device. As another example, the notification message may include error information of the corresponding sensor and the device.

2 is a flowchart for explaining a specific embodiment of FIG. 1.

Referring to FIG. 2, when the node diagnosis server 200 receives sensing data from a sensor (step S210), the node diagnosis server 200 may store the received sensing data in a database (step S220), and set packet and / or data format. Based on Format, the received sensed data may be reconstructed (step S230). In an embodiment, data may be transmitted and received between sensors located in each node of the sensor network, and a specific sensor may collect data of the sensors in the role of a sink node and transmit sensing data. For example, the sink node may include a sensor that is connected to and communicates with the node diagnosis server 200 for the first time. In one embodiment, the packet and / or data format may be set by dividing data collected from heterogeneous sensors by item. For example, the item may include a sensor ID, a sensor name, an ID and a sensing value of a block and a sector in which the sensor is located.

The node diagnosis server 200 may analyze the reconstructed packet (step S240) and diagnose whether the sensor and the facility included in the sensor network are malfunctioning (step S250). For example, the facility may include a manual control device having a unidirectional communication function as well as a device (control target device) capable of remote control by bidirectional communication.

If at least one of the sensor and the device is malfunctioning, the node diagnosis server 200 may generate situation information including the corresponding error information (step S260), and identify a service to which the generated situation information is provided (step S260). S270). For example, the service to which the situation information is to be provided may include an abnormal situation notification service of a sensor and a facility, a malfunction notification service, and an excess notification service of an allowable reference range.

If the service to be provided is confirmed, error information corresponding to the service may be provided (step S280). For example, the error information may be output in the form of blinking warning lights, text data, and / or image data.

As such, when it is determined that the sensor and the facility malfunction, the detection data may be deleted (discarded) from the database (step S290). In other words, by deleting the data due to malfunction can prevent the error of the system due to unnecessary data analysis.

FIG. 3 is a flowchart for explaining an exemplary embodiment of step S120 of FIG. 1.

Referring to FIG. 3, when sensing data is received from a sensor (step S301), the node diagnosis server 200 may calculate a sensing value, a block average value, and a sector average value by analyzing the received sensing data (step S301). S302). In one embodiment, the entire target area may be partitioned into at least two sectors, one sector may be partitioned into at least two blocks, and one block may include at least two sensors.

In one embodiment, the difference between the calculated sector average values SA and SectorAve and the block average values BA and BlockAve is smaller than the first reference value (for example, 3) (step S302), and the previous sensing value (BD, BeforeData). And the difference between the current sensing value (CD, CurrentData) is greater than the second reference value (eg, 3) (step S303), and the difference between the block average value and the previous sensing value is greater than the third reference value (eg, 3). (Step S304) If the difference between the current sensing value and the sector average value is smaller than the fourth reference value (eg, 3) (step S305), it may be determined that the sensor has returned to normal after a malfunction. For example, when the sensor has returned to normal, if the sensor error count (SEC, SensorErrCount) is greater than '0' (step S306), the sensor error count can be reduced (e.g., 1) (step S307). ), The result can be output (displayed) (step S308).

In another embodiment, the difference between the sector average value and the block average value is smaller than the first reference value (step S302), the difference between the previous sensing value and the current sensing value is smaller than the second reference value (step S303), and the current sensing value and the block mean value. When the difference in the average value is larger than the fifth reference value (for example, 3) (step S309), it may be determined that the corresponding sensor has malfunctioned. For example, the sensor error count may be increased (for example, 1) after step S309 and if the increased sensor error count is greater than or equal to the first threshold (LSEC, LimitSensorErrCount) (step S311). ), It may be determined that the sensor has malfunctioned (step S312).

In another embodiment, when the difference between the current sensing value and the block average value is smaller than the fifth reference value (step S309), it may be determined that the corresponding sensor is in normal operation, and the sensor error count (SEC, SensorErrCount) is 0. If greater than n (step S306), the corresponding sensor error count can be reduced (step S307).

In another embodiment, the difference between the sector average value and the block average value is smaller than the first reference value (step S302), the difference between the previous sensing value and the current sensing value is greater than the second reference value (step S303), and the block average value and the previous sensing value. If the difference in value is smaller than the third reference value (step S304), it may be determined that the sensor is malfunctioning, and the sensor error count may be increased (for example, 1) (step S310), and the increased sensor error If the count is greater than or equal to the first threshold value (step S311), it may be determined that the corresponding sensor has malfunctioned (step S312).

In another embodiment, the difference between the sector average value and the block average value is smaller than the first reference value (step S302), the difference between the previous sensing value and the current sensing value is greater than the second reference value (step S303), and the block average value and the previous sensing value. If the difference between the values is greater than the third reference value (step S304) and the difference between the current sensing value and the sector average value is greater than the fourth reference value (step S305), it may be determined that the sensor is malfunctioning and the sensor error count is increased. (For example, 1), and if the increased sensor error count is greater than or equal to the first threshold value (step S311), it may be determined that the corresponding sensor has malfunctioned (step S312).

According to another embodiment, when the difference between the sector average value and the block average value is larger than the first reference value (step S302), it may be determined that the abnormal situation by the equipment existing in the block, and request the control of the control target device. (Step S313). For example, when the temperature of the block is lower than the average value of the sector, a device capable of raising the temperature of the block (for example, a heater or a heater) may be operated.

One embodiment described above with reference to FIG. 3 may correspond to a case in which the facility is not running, and another embodiment of FIG. 4 to be described below may correspond to a case in which the facility is in operation.

FIG. 4 is a flowchart for explaining another exemplary embodiment of step S120 of FIG. 1.

Referring to FIG. 4, the node diagnosis server 200 may calculate a sensing value, a block average value, and a sector average value by analyzing the received sensing data (step S401). In one embodiment, the entire target area may be partitioned into at least two sectors, one sector may be partitioned into at least two blocks, and one block may include at least two sensors.

When the difference between the previous sensing value and the current sensing value is greater than the sixth reference value (for example, 3) (step S402), and the difference between the current sensing value and the block average value is greater than the seventh reference value (for example, 3) ( In step S403, the sensor error count may be increased (for example, 0.5) (step S404).

If the sensor error count is greater than or equal to the second threshold value (step S405), it may be determined that the sensor has malfunctioned (step S406), and the result may be displayed on the screen (step S407).

If the difference between the previous sensing value and the current sensing value is smaller than the sixth reference value (step S402), and the difference between the previous block average value and the current block average value is smaller than the eighth reference value (for example, 3) (step S408), the device error. The count can be increased (for example, 1) (step S409).

If the device error count is greater than or equal to the third threshold value (step S410), it may be determined that the corresponding control target device has malfunctioned (step S411), and the result may be displayed on the screen (step S407).

The difference between the previous sensing value and the current sensing value is larger than the sixth reference value (step S402), and the difference between the current sensing value and the current block average value is smaller than the seventh reference value (step S403), and the difference between the block average value and the sector average value is zero. If greater than 9 reference values (e.g., 3) (step S412), the device error count can be checked.

As a result of the check, when the device error count is larger than " 0 " (step S413), the device error count can be reduced (e.g., reduced by 1) (step S414) and the control of the controlling device can be maintained (step S414). S415).

The difference between the previous sensing value and the current sensing value is larger than the sixth reference value (step S402), and the difference between the current sensing value and the current block average value is smaller than the seventh reference value (step S403), and the difference between the block average value and the sector average value is zero. If it is smaller than 9 reference values (step S412), control of the control target device can be stopped.

5 is a configuration diagram illustrating an embodiment of a sensor network based node diagnosis system according to the present invention.

Referring to FIG. 5, the sensor network-based node diagnosis method and system 100 includes a sensor 110, a node diagnosis server 120, a user terminal 130, and a control target device 140.

The sensor 110 may be installed in the sensing target region and provided to correspond to the sensing target element. For example, if crops are cultivated in the area to be detected and the elements to be detected include photosynthesis, light quantity, soil information, atmospheric humidity, and crop conditions, the sensors may be oxygen / carbon dioxide sensors, light intensity sensors, soil sensors, humidity sensors, leaf temperatures. / Lobe temperature sensor may be included. In an embodiment, the sensor 110 may include a plurality of sensors 110 configured as a sensor network to transmit data in an ad-hoc manner.

The node diagnosis server 120 checks the sensing data transmitted through the at least one sensor 110, and when detecting an abnormal situation from the sensor 110, analyzes the sensing data and at least one sensor 110. ) And whether the at least one of the control target device 140 operates normally to determine the validity of the corresponding sensing data. In other words, the node diagnosis server 120 may collect and analyze the sensing data of the sensor for the entire sensing target area, and perform the operation control of the control target device 140 accordingly.

In one embodiment, the node diagnostic server 120 receives the sensing data from at least one sensor, reconstructs and analyzes the packet for each set data, and determines whether there is a malfunction of at least one of the sensor and the control target device. It may generate context information for each target service and transmit a notification message including current status information of at least one of the corresponding sensor and the device.

The node diagnosis server 120 may be connected to the sensor 110 and the control target device 140 through a local area wired communication network, and may be connected to the user terminal 130 through a wired or wireless communication network. Since the specific internal configuration of the node diagnosis server 120 may be variously modified and applied according to each component to be connected and the needs of those skilled in the art, it is natural that the present invention is not limited thereto.

The user terminal 130 may check the sensed data of the sensor 110 in conjunction with the node diagnosis server 120 and control the control target device 140 as necessary. For example, the user terminal 130 may include a personal computer 131, a cellular phone 132, a PDA 133, and a smartphone 134.

The user terminal 130 may output an image transmitted from the photographing apparatus of the control target device 140. In one embodiment, the user can check the image of the desired area by controlling the movement and movement of the photographing device through the user terminal 130.

The control target device 140 may be operated to perform a solution corresponding to the abnormal situation. For example, the control target device 140 may include a window opening and closing device, a light source control device, a mobile image acquisition device (photographing device), a cold / hot air fan, a fan, a carbon dioxide supply device, and a watering device. In one embodiment, if the solution is ventilation, the window may be opened and the ventilator operated to ventilate the indoor air. In another embodiment, if the solution is to increase the amount of light can be turned on the lighting installed in the room.

FIG. 6 is a hierarchical diagram illustrating an embodiment of the node diagnosis server of FIG. 5.

Referring to FIG. 6, the node diagnosis server 120 may include a physical layer, a failure-diagnostic context-awareness middleware layer, and an application layer.

The physical layer may be connected to the sensor 110 and the control target device 140 of FIG. 5, and may receive the sensing data of the sensor 110 and transmit a signal for controlling the control target device 140. .

The FDCM layer may perform the node diagnosis method according to the present invention, and may include a data management module, a data storage module, a context provider module, and a context interpreter. Module) and a service provider module.

The data management module may process the sensed data transmitted from the sensor and call the set data to reconstruct the packet. In one embodiment, the data management module may include "Data Parser", "Packet Creator", and "Packet Data" as inner classes.

The information storage module may store the sensed data processed by the data management module and set and store the data to be used. In one embodiment, the information storage module may include "DataBase" and "Data Storage Manager" as inner classes.

The contextual information providing module may convert the packet reconstructed by the data management module into contextual information. In one embodiment, the context information providing module may include "Context Creator", "Context Diagnosis", and "Context Data" as inner classes.

The context analysis module may determine the target service to be provided by analyzing the context information converted in the context information providing module. In one embodiment, the context analysis module may include the "Context Interpreter" as an inner class.

The service provision module may execute the target service determined by the situation analysis module. In one embodiment, the service provision module may include the "Service Provider" as an inner class.

The application layer may support an interface with the user terminal 130, check the sensed data of the sensor 110, and control the control target device 140 at the request of a user (manager).

FIG. 7 is a flowchart illustrating an operation of a configuration included in the “FDCM Layer” of FIG. 6.

Referring to FIG. 7, the data management module may transmit sensed data transmitted from the sensor 110 to the information storage module (InsertEnvironment), and may receive a packet format (format) from the information storage module (SetPacketData).

The data management module may regenerate the packet based on the received packet type and transmit the packet to the context information providing module for analysis (DataAnalysis).

The context information providing module may obtain device information (GetDeviceCode), data type (GetDataType), and operation state (GetActivate) from the information storage module to generate context information based on the regenerated packet.

The context information providing module may generate context information based on the called information and transmit the context information to the context analysis module (ContextAnalysis).

The context analysis module may generate a notification message in response to the set (or selected) service and transmit the generated notification message to the service providing module (ErrAlarmService). In one embodiment, the context analysis module may generate the notification message by the method described in FIG. 3 or 4.

The service providing module may request to delete the sensed data stored in the information storage module when it is determined (confirmed) that at least one of the corresponding sensor and the control target device is malfunctioning (DeleteErrData). In one embodiment, if the service providing module determines that the corresponding sensor and the control target device are normally operated, the service providing module may request to control the corresponding control target device based on the sensed data (ControlDevice).

FIG. 8 is a diagram illustrating an embodiment of a packet data configuration used in a sensor network-based node diagnosis method and system according to the present invention.

Referring to FIG. 8, packet data includes an ID (id) of a corresponding sensor, an ID (block_id) of a block in which the corresponding sensor is installed, an ID (sector_id) of a sector including the corresponding block, and a type of data collected by the corresponding sensor (data_CODE). ), Data currently sensed by the sensor (current Data), data previously sensed by the sensor (beforeData), average value (blockAve) of the current sensing data of each sensor included in the same block, and included in the same block It may include at least one of the average value (beforeBlockAve) of the previous sensing data of each of the sensor and the average sensing value (sectorAve) of the sensors included in the same block. In one embodiment, the average value of the current sensing data (blockAve) of each sensor included in the same block and the average sensing value (sectorAve) of the sensors included in the same block may be applied to a value other than the sensor that transmitted the current sensing data. have.

9 is a view for explaining an embodiment of the configuration of the context information used in the sensor network-based node diagnosis method and system according to the present invention.

Referring to FIG. 9, the status information includes packet information, status determination (isDecision), error occurrence (isErr), sensor occurrence (isSensor), facility occurrence (isDevice), operation of facility. At least one of whether or not (isActivation), the ID of the equipment (DEVICE_CODE), the name of the equipment (deviceName), the management field of the sector (optimalName), the management standard information (optimalData) and the type of related data (DataType) in the field. It may include one.

FIG. 10 is a diagram illustrating an embodiment of a database schema used in a sensor network-based node diagnosis method and system according to the present invention.

Referring to FIG. 10, a schema of a database managed by a node diagnosis server may include at least one of a current sensing information table, a management reference information table, a device table, a data type table, and a control table.

FIG. 11 is a diagram illustrating an embodiment of a class diagram used in a method and a system for diagnosing a node based on a sensor network according to the present invention.

Here, the variables, functions, and connection relationships for each configuration shown in FIGS. 8 to 11 are not limited to specific ones because various modifications are possible depending on the system to which the present invention is applied and the needs of those skilled in the art.

The sensor network-based node diagnosis method and system according to the present invention have been described above. It will be understood by those skilled in the art that the technical features of the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.

Therefore, the above-described embodiments are to be understood in all respects as illustrative and not restrictive, and the scope of the present invention is indicated by the appended claims rather than the foregoing description, and therefore the meaning of the claims. And all changes or modifications derived from the scope and equivalent concept thereof should be construed as being included in the scope of the present invention.

100: node diagnostic system
110: sensor 120: node diagnostic server
130: user terminal 140: control target device

Claims (21)

a) receiving sensing data from at least one sensor included in the sensor network and reconfiguring the data for each set data;
b) analyzing the reconstructed data to determine whether there is a malfunction of at least one of the sensor and the device; And
and c) generating contextual information for each service according to the determination result and transmitting a notification message including the current status information of at least one of the corresponding sensor and the device. The method of claim 1,
Step a)
a-1) receiving the sensed data;
a-2) storing the received sensing data in a database; And
a-3) a method for diagnosing a node based on a sensor network, comprising reconstructing the received sensed data based on a configured packet. The method of claim 1,
The step c)
c-1) generating situation information including corresponding error information when at least one of the sensor and the device is malfunctioning as a result of the determination;
c-2) checking a service to which the generated situation information is provided; And
c-3) a method for diagnosing a node based on a sensor network, comprising providing error information corresponding to the identified service. The method of claim 1,
The step c)
And detecting the detected data when at least one of the corresponding sensor and the device is malfunctioning as a result of the determination. The method according to any one of claims 1 to 4,
Step b)
b-1) calculating a sensing value, a block average value, and a sector average value by analyzing the sensed data; And
b-2) The difference between the sector average value and the block average value is smaller than the first reference value, the difference between the previous sensing value and the current sensing value is greater than the second reference value, and the difference between the block average value and the previous sensing value is greater than the third reference value, and And if the difference between the sensing value and the sector average value is smaller than the fourth reference value, determining that the sensor has returned to normal after a malfunction of the sensor network. The method according to any one of claims 1 to 4,
Step b)
b-1) calculating a sensing value, a block average value, and a sector average value by analyzing the sensed data; And
b-2) The difference between the sector average value and the block average value is smaller than the first reference value, the difference between the previous sensing value and the current sensing value is smaller than the second reference value, and the difference between the current sensing value and the block average value is larger than the fifth reference value. And a process of determining that the corresponding sensor is malfunctioning. The method according to claim 6,
Step b-2)
And determining that the corresponding sensor is in normal operation when the difference between the current sensing value and the block average value is smaller than a fifth reference value. The method according to any one of claims 1 to 4,
Step b)
b-1) calculating a sensing value, a block average value, and a sector average value by analyzing the sensed data; And
b-2) when the difference between the sector average value and the block average value is smaller than the first reference value, the difference between the previous sensing value and the current sensing value is greater than the second reference value, and the difference between the block average value and the previous sensing value is smaller than the third reference value, Sensor network-based node diagnostic method comprising the step of determining that the sensor is malfunctioning. The method according to any one of claims 1 to 4,
Step b)
b-1) calculating a sensing value, a block average value, and a sector average value by analyzing the sensed data; And
b-2) The difference between the sector average value and the block average value is smaller than the first reference value, the difference between the previous sensing value and the current sensing value is greater than the second reference value, and the difference between the block average value and the previous sensing value is greater than the third reference value, and And determining that the corresponding sensor has malfunctioned when the difference between the sensing value and the sector mean value is larger than the fourth reference value. The method according to any one of claims 1 to 4,
Step b)
b-1) calculating a sensing value and a block average value by analyzing the sensed data; And
b-2) when the difference between the sector average value and the block average value is greater than the first reference value, requesting control of the control target device. The method according to any one of claims 1 to 4,
Step b)
b-1) calculating a sensing value and a block average value by analyzing the sensed data; And
b-2) if the difference between the previous sensing value and the current sensing value is greater than the sixth reference value, and the difference between the current sensing value and the block mean value is greater than the seventh reference value, determining that the corresponding sensor has malfunctioned. Sensor network based node diagnosis method. The method according to any one of claims 1 to 4,
Step b)
b-1) calculating a sensing value and a block average value by analyzing the sensed data; And
b-2) if the difference between the previous sensing value and the current sensing value is smaller than the sixth reference value, and the difference between the previous block average value and the current block average value is smaller than the eighth reference value, determining that the control target device is malfunctioning. Sensor network based node diagnostic method, characterized in that the. The method according to any one of claims 1 to 4,
Step b)
b-1) calculating a sensing value, a block average value, and a sector average value by analyzing the sensed data;
b-2) The difference between the previous sensing value and the current sensing value is greater than the sixth reference value, the difference between the current sensing value and the current block average value is smaller than the seventh reference value, and the difference between the block average value and the sector average value is greater than the ninth reference value. In the case, the node network-based node diagnostic method comprising the step of maintaining control of the control target device. The method of claim 13,
Step b-2)
And stopping the control of the control target device when the difference between the block mean value and the sector mean value is smaller than a ninth reference value. At least one sector, at least one block included in the sector, at least one sensor and a control target device included in the block; And
Receives the sensed data from the at least one sensor and reconstructs and analyzes the packet for each set data and determines whether there is a malfunction of at least one of the corresponding sensor and the control target device, thereby generating context information for each target service to be provided, and Sensor network-based node diagnostic system including a node diagnostic server for transmitting a notification message including the current status information of at least one of the devices. The method of claim 15, wherein the node diagnostic server
A data management module processing the sensed data transmitted from the sensor and reconstructing a packet by calling set data;
An information storage module for storing sensed data processed by the data management module and setting and storing data to be used;
A situation information providing module for converting the packet reconstructed by the data management module into situation information;
A situation analysis module for determining a target service to be provided by analyzing the situation information converted by the situation information providing module; And
Sensor network-based node diagnosis system comprising a service providing module for executing the target service determined in the situation analysis module. The method of claim 16, wherein the service providing module
And if it is determined that at least one of the sensor and the control target device malfunctions, requesting to delete the sensed data stored in the information storage module. The method of claim 16, wherein the service providing module
And if it is determined that the sensor and the control target device operate normally, requesting to control the control target device based on the sensed data. 19. The method of any one of claims 15 to 18, wherein the packet is
ID of the sensor, ID of the block in which the sensor is installed, ID of the sector that contains the block, type of data collected by the sensor, data currently sensed by the sensor, data previously sensed by the sensor And reconstructing at least one of an average value of current sensing data of each sensor included in the same block, an average value of previous sensing data of each sensor included in the same block, and an average sensing value of sensors included in the same block. Sensor network based node diagnosis system. 19. The method according to any one of claims 15 to 18, wherein the situation information is
Packet information, status determination, error occurrence, sensor occurrence, equipment occurrence, equipment operation, ID of the equipment, name of the equipment, management field of the sector, management standard in the field Sensor network-based node diagnosis system comprising at least one of the type of information and related data. 19. The method according to any one of claims 15 to 18,
Schema of the database managed by the node diagnostic server,
A sensor network-based node diagnosis system comprising at least one of a current sensing information table, a management reference information table, a device table, a data type table, and a control table.

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