JP2015517130A - Early warning system for disaster situation of traditional wooden buildings - Google Patents

Abstract

In the case where a disaster situation occurs, the present invention collects data through a sensor for the environmental change in view of the fact that an environmental change occurs immediately before the occurrence of the disaster, and deletes the element of the disaster occurrence in advance. Thus, the present invention relates to an early warning system for the disaster situation of a traditional wooden building to prevent a disaster. As a result, the present invention collects information that may cause a disaster from data and collects it from a sensor, and uses the collected data to determine and prevent an element that may cause a disaster. There is an effect that can.

Description

  The present invention relates to an early warning system for disaster situations of wooden traditional buildings. More specifically, when a disaster situation occurs, environmental changes will occur immediately before the disaster occurs. Therefore, data related to the environmental changes is collected from the sensors, and the collected data is used. The present invention relates to an early warning system for the disaster situation of a traditional wooden building to prevent disaster by removing the cause of disaster.

  As a conventional technique, FIG. 1 is a configuration diagram of a conventional disaster management system. The disaster management system described above was composed of a fire-fighting equipment group (10), a video equipment group (20), and a control device (30) and executed disaster management.

  More specifically, the fire fighting equipment group (10) transmits data sensed using sensors such as a smoke sensor, a flame detection sensor, and a heat detection sensor to the control device (30), and the video equipment group. In (20), in order to monitor the intruder, the image is taken by a photographing device such as CCTV, and the photographed image is transmitted to the control device (30).

  Such a conventional disaster management system, when the management object is a traditional wooden building, is weak in the ability to recognize intelligent initial disaster information, and is delayed in dispatch to the site when various disasters such as fires occur Therefore, there was a great risk that most of the traditional wooden buildings (especially those like cultural properties) would disappear completely.

  In particular, because traditional buildings are not governed by fire-related laws and regulations, the frequency of ignition and the risk of fire are higher than ordinary buildings, but they are applied inside buildings. The response to fire is weak due to the lack of intelligent sensing devices.

  For example, when the conventional disaster management system is installed in a temple, it is mistaken for a fire due to various religious events and lifestyle habits held in the temple, and failure of sensing facilities frequently occurs. Is the actual situation.

  For example, if a smoke sensor is activated by dust generated by a fuel lamp event where a large number of people are mobilized in a temple, or if a human body sensor is activated by the entry or exit of an outsider, the detected information will be displayed at the fire department, Sent to a station continuously. This is because the fire information is transmitted despite the fact that it is not a disaster situation, so the disaster prevention manager becomes less nervous about the situation in the field and responds immediately when an actual disaster situation occurs There was a problem that could not be done.

  As a result, an analysis system that can actively handle disaster prevention according to the disaster situation using information that accurately analyzed whether there is a danger of disaster about the current situation of wooden traditional buildings There was no.

  In particular, in the case of a fire that occurs in a traditional wooden building, not only does it become very difficult to suppress the fire after about 5 minutes after the occurrence of a fire, but many parts of cultural assets have already disappeared. However, there is a problem in that it is impossible to analyze an element that may cause a fire type at an extremely early stage because only the technique of suppressing the fire after confirming the occurrence of the fire type is used.

  Therefore, the present invention has been devised in order to solve the above-described problems, and the object of the present invention is to collect data on elements that may cause a disaster and to generate a disaster. Its purpose is to predict certain elements and prevent disasters.

  According to one embodiment of the present invention for achieving the above object, an early warning system for a disaster situation of a traditional wooden building includes a sensor that generates a plurality of first data for each set first time period, Server. The server includes a receiving unit that receives the plurality of first data generated for each of the set first time periods, each of the plurality of received first data, and the immediately preceding first time. A setting unit configured to set a second difference value having the largest difference value as a set value among a plurality of first difference values obtained by comparing with second data measured in a cycle; and a user The second time period input by the input unit and the setting value set in the setting unit are received, and the second time period input by the input unit is transmitted to the sensor. Receiving a plurality of third data generated by the sensor every two time periods, comparing each of the received plurality of third data with the fourth data measured in the immediately preceding second time period Each of the obtained second difference values and the set value are compared. An analysis unit that generates analysis data indicating that a disaster factor has occurred with respect to the value of the second difference when higher than the set value, and the second time period input through the input unit to the sensor And a transmission unit that transmits the analysis data generated via the analysis unit to an administrator terminal.

  According to another embodiment of the present invention, an early warning system for a disaster situation of a traditional wooden building includes a first sensor that generates first data every set first time period, and the set first sensor. It has the 2nd sensor which generates the 2nd data for every 1 hour period, and a server. The server includes a receiving unit that receives the generated first and second data in the same first time period to form a plurality of pairs, and each of the paired first and second data. For the first difference value, a setting unit for setting the largest difference value as a setting value, an input unit for inputting a second time period by the user, and the setting value set in the setting unit The second time period received and input by the input unit is transmitted to the first and second sensors, whereby a plurality of third data generated by the first sensor in the second time period and the second data period A plurality of fourth data generated by the second sensor are grouped together in the same second time period, a second difference value is obtained for each of the third and fourth data, and each second difference is determined. When the value is higher than the set value An analysis unit that generates analysis data indicating that a disaster factor has occurred with respect to the second difference value, and the analysis unit that transmits the second time period input via the input unit to the sensor And a transmitting unit that transmits the analysis data generated by the method to an administrator terminal.

  As described above, according to the present invention, information that may cause a disaster is converted into data and collected from a sensor, and an element that causes the disaster is determined in advance using the collected data to avoid the disaster. There is an effect that can.

It is a block diagram of the conventional disaster management system. It is a block diagram of the early warning system of the disaster situation of a wooden traditional building by one Example of this invention. It is a block diagram of the server by one Example of this invention. 6 is an exemplary graph for setting value measurement according to an embodiment of the present invention; FIG. 3 is an exemplary diagram of a sensor arrangement according to one embodiment of the present invention. 4 is an exemplary graph for determining disaster according to an embodiment of the present invention. It is an illustration of an early warning system for disaster situation of a traditional wooden building according to another embodiment of the present invention.

  DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, the configuration and operation of an optimum embodiment of the present invention will be described with reference to the accompanying drawings.

  FIG. 2 is a block diagram of an early warning system for disaster situations of traditional wooden buildings according to the present invention. The early warning system for the disaster situation of the wooden traditional building consists of a sensor (100) and a server (200).

  More specifically, the sensor (100) generates first data for each set first time period.

  For example, assume that the sensor (100) is a temperature sensor. The temperature sensor senses the temperature in real time, but if it is a set time period, for example, a 1-minute period, the temperature value measured in the 1-minute period is converted into data, and the value is changed every 1-minute period. 1 data is generated, and the generated first data is transmitted to the server (200).

  At this time, when the time period is 1 minute, when the time period of 1 minute is input to the server (200), the sensor (100) generates the first data every minute. The sensor (100) corresponds to 60 minutes per hour, so 60 first data is generated and sent to the server (200). It is generated and transmitted to the server (200).

  On the other hand, the sensor (100) is preferably a sensor that can detect disasters, and typically a temperature sensor, a smoke sensor, or a humidity sensor is desirable. Of course, it is desirable that the human body sensor for detecting an intruder is a temperature sensor, the human body sensor is a smoke sensor, and the human body sensor is a humidity sensor. It is also preferable that the human body sensor is configured together after the humidity sensor is configured to include a plurality of sensors.

  This is because the intruder enters the wooden traditional building and copes with acts such as arson.

  The sensor 100 performs data communication with the server 200.

  As shown in FIG. 3, the server (200) includes a receiving unit (210), a setting unit (220), an input unit (230), an analysis unit (240), and a transmission unit (250).

  More specifically, the receiving unit (210) of the server (200) receives a plurality of first data generated for each of the set first time periods.

  In addition, the receiving unit (210) receives the third data generated by the second time period, and the third data generated by the second time period will be described in detail below in the analysis unit (240). .

  The setting unit (220) of the server (200) includes a plurality of first data obtained by comparing each of the received plurality of first data with the second data measured in the immediately preceding first time period. Among the 1 difference values, the second difference value having the largest difference value is set as the set value.

  For example, this will be described with reference to the graph of FIG. 4 in order to help understanding of the present invention. Assuming that the first data is A ′ data, B ′ data, C ′ data, D ′ data, E ′ data, the A ′ data, B ′ data, C ′ data, D ′ data, The E ′ data has time information and a measured value (temperature value).

  That is, A 'data has information of 10 ° C and 30 minutes, B' data has information of 12 ° C and 31 minutes, C 'data has information of 16 ° C and 32 minutes, The D 'data has information of 14 ° C and 33 minutes, and the E' data has information of 12 ° C and 34 minutes.

  At this time, for each data of A ', B', C ', D', E ', it is like A', B ', C', D ', E' data by a time period of 1 minute on the time axis. Assuming that the arbitrary first data is B ′ for generating the first difference between the first data and the second data, the second data collected in the immediately preceding first time period is A ′. However, since the temperature value measured at B ′ is 12 ° C. and the temperature value measured at A ′ is 10 ° C., the value of the first difference is 2 ° C.

  When this process is repeated, the difference between C 'and B' is 4 ° C, the difference between D 'and C' is 2 ° C, and the difference between E 'and D' is 2 ° C. . From such a large number of first difference values, the second difference value having the largest difference value, that is, 4 ° C. of C ′ and B ′ is set as the set value.

  The reason for setting the above set values is that in the event of a disaster, such as a fire, if a fire type occurs, the wooden traditional building will be damaged unbearably after about 5 minutes. This is to determine whether there is an element in advance about 5 minutes before the occurrence of fire.

  According to the result of measuring the Susan Shoin in Andong, Gyeongsangbuk-do, South Korea using the present invention and temperature sensor to generate the above set value, the time period may have increased by up to 1.6 ° C per minute, It was found that the average was about 1.0 ° C.

  When the maximum temperature rises by 1.6 ° C per minute, it was analyzed that factors that increased the temperature such as heating and cooking facilities were activated due to special events at Toyama Shoin. After all, the present invention is intended to cope with the situation immediately even if the smallest element that may cause a fire appears, so the set value is the largest difference among the first difference values. Is set to the value of the second difference having the value of

  The server (200) having the setting unit (220) obtains a set value for each sensor from the setting unit (220) when a large number of sensors (100) are set, and each sensor is transmitted via the transmission unit (250). It is also desirable to transmit the set value every time.

  For example, as shown in Fig. 5, A sensor installed at the entrance, B sensor installed on the ceiling, C sensor installed on the floor is explained in an arbitrary space of a wooden traditional building To do. In the case of the A sensor, since it is at the entrance and exit, it is frequently opened and closed by entering and exiting, so it becomes very sensitive to the influence of the external environment, and the value measured by the A sensor changes frequently. However, B sensor and C sensor have constant measurement values than A sensor, so if a set value is given equal to the same value as the average value of A sensor, B sensor, C sensor, it is installed at the entrance / exit. The A sensor detects false positives that disasters frequently occur. For this reason, it may be desirable to have different set values for each sensor.

  Since it is difficult for the setting unit (220) to apply a uniform set value depending on environmental conditions such as location, position, season, etc., the set value is automatically applied according to the set cycle after a set cycle.

  Further, since it is difficult for the setting unit (220) to apply a uniform set value depending on environmental conditions such as location, position, and season, the set value is applied by a user's numerical calculation.

  In other words, in the case of a temperature sensor, the difference value is greatly affected by the season of spring, summer, autumn, and winter, so the set value is set with a set cycle for applying this difference value according to the season. Set the set value to the server (200) automatically or manually.

  The second time period is input to the input unit (230) of the server (200) in order to determine whether a disaster cause occurs by the user.

  That is, when the second time period is input, the input second time period is transmitted to the sensor (100) through the transmission unit (260), and the third data is generated by the second time period. It will be.

  The analysis unit (240) of the server (200) receives the set value set by the setting unit (220), and the second time period input by the input unit (230) is input to the sensor (100). A plurality of third data generated by the sensor (100) is received every second time period by being transmitted. The analysis unit (240) compares each of the received third data with the fourth data measured in the immediately preceding second time period, and determines the plurality of second difference values obtained and the above settings. Compared with the value, the analysis data that the disaster factor has occurred is generated for the value of the second difference when the value is higher than the set value.

  For example, the analysis unit (240) will be described with reference to FIG. First, if the set value is set to 3 ° C, the temperature value of the time period A 'data is 10 ° C and the temperature value of B' data is 12 ° C, so A 'data and B' data The difference value is 2 ° C. Since the temperature value of B ′ data is 12 ° C. and the temperature value of C ′ data is 16 ° C., the difference value between B ′ data and C ′ data is 4 ° C. Since the temperature value of C ′ data is 16 ° C. and the temperature value of D ′ data is 14 ° C., the difference value between C ′ data and D ′ data is 2 ° C. Since the temperature value of D ′ data is 14 ° C. and the temperature value of E ′ data is 12 ° C., the difference value is 2 ° C.

  At this time, since the time period exceeding the set value of 3 ° C is the time period between B 'data and C' data, it is judged that there is an element of disaster, and the server (200) analyzes Generate data.

  In other words, the analysis data does not send the fact that a disaster has occurred, but rather tells us that there is a minimum element that can cause a disaster, so that the cause of the disaster can be removed in advance. It is data, and it is intended to deal immediately with the occurrence of disaster about 5 minutes before using such analysis data.

  The analysis unit (240) receives the fifth data exceeding the set value in an arbitrary second time period, and then receives the fifth data that is less than the set value in the second time period following the optional second time period. When the sixth data is received, analysis is made that no disaster cause has occurred and analysis data generation is blocked.

  For example, when the sensor (100) is a non-contact temperature sensor among temperature sensors, the temperature at a certain distance is measured instead of measuring the surrounding temperature. Therefore, when a person passes in front of the temperature sensor, the temperature rises rapidly and then immediately changes to the normal temperature. In such a case, it is not analyzed that a disaster factor such as a fire has occurred.

  Further details will be described with reference to FIG. The F ′ data is in a state where there is no disaster element below the set value, the G ′ data is in a state where a disaster factor above the set value has occurred, and the H ′ data is in a state where there is no disaster element below the set value. In this case, as indicated by time period 1 in which F ′ data and G ′ data are measured, the sudden rise in temperature corresponds to measurement of the temperature of a person in front of the temperature sensor. As illustrated in the time period 2, the temperature suddenly decreased because the person who was in front of the temperature sensor measured after passing, and thus maintained a state where no disaster element exists.

  In this way, if the value measured within the time period of at least 3 to 5 times returns from the state where the disaster element has occurred to the state where the disaster element does not exist again, the situation where disaster can not occur Judge that.

  Next, the analysis unit (240) receives fifth data exceeding a set value in an arbitrary second time period, and then receives fifth data in a second time period after the optional second time period. When the seventh data that is the same as or increased is received, it is analyzed that a disaster factor has occurred, and analysis data is generated.

  For example, if the set value is assumed to be 4 ° C, the temperature value that rises by 6 ° C in the second time period is measured and the set value has been exceeded. If the temperature continues to be the same or rises, such as 6 ° C in the second time period and then 7 ° C in the second time period, analysis data is generated because it has continuity of disaster factors .

  Even if data having continuity as described above is received by the external environment, analysis data is generated in a preventive sense.

  Particularly, when the third data generated at an arbitrary second time period is greater than or equal to a set value, the analysis unit (240) is in units of one second until 1 minute elapses from the time when the third data is generated. All the 8th data received by comparing the 8th data sequentially received from the sensor with the 4th data for obtaining the value of the second difference generated in the arbitrary second time period. If is greater than the set value, it is analyzed that a disaster factor has occurred. Moreover, if any 8th data is less than a preset value among all the 8th data received within 1 minute, it will analyze that the disaster cause has not occurred.

  For example, when data is received from a temperature sensor, the third data generated in an arbitrary second time period is set to 30 ° C., and the second difference value generated in the arbitrary second time period is obtained. If the 4th data is 25 ° C and the set value is 4 ° C, the difference between the 3rd data 30 ° C and the 4th data 25 ° C is higher than the set value 4 ° C. Then, the 8th data is received every second for 1 minute.

  At this time, if all of the 8th data has a value of 4 ° C or more until 1 minute has passed, this indicates that a disaster factor has occurred, and any of the 4th data in the 4th data. 4 If the data is displayed below the set value, it is not considered that a disaster cause has occurred.

  On the other hand, the reason for receiving the eighth data every second per minute is that, in the case of a wooden traditional building, not only fire suppression becomes difficult after about 5 minutes, but many parts of the wooden traditional building have already disappeared. Therefore, after analyzing the disaster factors within 1 minute and grasping the disaster factors for the remaining 4 minutes, it is necessary to respond quickly.

  Also, if any 8th data is displayed below the set value among many 8th data, the reason for not seeing it as a disaster element is that the temperature will continue to rise when a fire occurs and it develops into a fire If there is a discontinuity in the above continuity compared to having continuity of whether or not to maintain, this means that it has not developed from a fire type to a fire, so no disaster element has occurred And analyze.

  For example, if a security guard visiting a traditional wooden building, typically a cultural property building, patrols and turns on an arbitrary space in a special situation, and then leaves the arbitrary space, a disaster factor occurs, but it continues Because there is no nature, it does not develop into a disaster, so we do not analyze the occurrence of a disaster.

  After all, in the present invention, the server (200) analyzes that there is continuity when a disaster occurs. In other words, when a fire occurs from a fire type in the event of a disaster such as a fire, the elements (temperature) of the fire have continuity, so analyze this to prevent the fire 5 minutes before the fire occurs It is.

  The transmission unit (250) of the server (200) transmits the second time period input via the input unit (230) to the sensor (100), and also generates the second time period via the analysis unit (240). The analyzed data is transmitted to the administrator terminal.

  At this time, the analysis data is displayed on the administrator terminal so that the administrator can deal with it immediately.

  An early warning system for a disaster situation of a traditional wooden building according to another embodiment of the present invention includes a first sensor (100-1), a second sensor (100-2), and a server (200-1).

  More specifically, the early warning system of the present invention includes a first sensor (100-1) that generates first data for each set first time period; and second data for each set first time period. A second sensor (100-2) that generates: a receiving unit that receives the first and second data generated in the same first time period together to form a plurality of pairs, and the pair A setting unit that obtains a first difference value for each of the first and second data, sets the maximum difference value as a set value, an input unit that inputs a second time period by the user, and the setting unit And the second time period input by the input unit is transmitted to the first and second sensors (100-1, 100-2), so that the first time period is the first time period. Multiple third data generated by the sensor (100-1) and multiple third data generated by the second sensor (100-2) 4 data are grouped together in the same second time period, the second difference value is obtained for each of the third and fourth data, and the respective second difference value is compared with the set value. The analysis unit that generates analysis data indicating that a disaster factor has occurred for an arbitrary second difference value that is higher than the set value, and the second time period input through the input unit to the sensor And a server (200-1) composed of a transmission unit that transmits and transmits the analysis data generated through the analysis unit to the management terminal.

  More specifically, another embodiment of the present invention analyzes whether a disaster factor has occurred using the environmental conditions between both sensors, and will be described with reference to FIG. Certain environmental conditions are established in any space inside the object.

  For example, the first sensor (100-1) is disposed on an upper part of a traditional wooden building, and the second sensor (100-2) is disposed on a lower part of the traditional wooden building. In this case, the value between the first data generated by measuring from the first sensor (100-1) and the second data generated by measuring from the second sensor does not have any disaster factors Always has a stable range.

  Therefore, in order to set the above stable range, the value of the first difference between the first and second data generated by the first and second sensors (100-1 and 100-2) at the same first time period is used. It is obtained and the largest value among them is set as a set value (stable range).

  If fire is generated from the first sensor (100-1), the value of the first difference between the first sensor (100-1) and the second sensor (100-2) where the fire is generated is , Higher than the set value, which in the end implies that a fire has occurred.

  In addition, the present invention using both sensors (100-1 and 100-2) may occur in combination with the invention composed of one sensor described with reference to FIGS. The description of is omitted.

  In the drawings and detailed description, preferred embodiments are disclosed, and the specific terms used above are merely used for the purpose of describing the present invention and are described in the meaning limitation and in the claims. It has not been used to limit the scope of the invention.

  Accordingly, those skilled in the art can make various modifications and other equivalent embodiments from this, and the true technical protection scope of the present invention is defined by the scope of the claims. Should be determined by specific ideas.

10: Fire fighting equipment group 20: Video equipment group
30: Control device 100: Sensor
100-1: First sensor 100-2: Second sensor
200, 200-1: Server 210: Receiver
220: Setting section 230: Input section
240: Analysis unit 250: Transmission unit

Claims (10)

A sensor that generates a plurality of first data for each set first time period;
A server, and
The server
A receiving unit for receiving the plurality of first data generated for each of the set first time periods;
Among the plurality of first difference values obtained by comparing each of the plurality of received first data and the second data measured in the immediately preceding first time period, the largest difference A setting unit for setting the value of the second difference having a value as a set value;
An input unit for inputting a second time period by the user;
The setting value set in the setting unit is received, and the second time period input by the input unit is transmitted to the sensor to thereby generate a plurality of second values generated by the sensor for each second time period. 3 data is received, and each of the plurality of received third data and the fourth data measured in the immediately preceding second time period are compared with a plurality of second difference values and the setting Each of the values, an analysis unit that generates analysis data that a disaster factor has occurred for the value of the second difference when higher than the set value,
A transmission unit configured to transmit the second time period input via the input unit to the sensor and transmit the analysis data generated via the analysis unit to an administrator terminal. An early warning system for disaster situations of traditional wooden buildings. In Claim 1, the analysis unit,
When fifth data exceeding the set value is received in an arbitrary second time period and then sixth data less than the set value is received in the second time period following the arbitrary second time period Is an early warning system of a disaster situation of a traditional wooden building, characterized in that generation of the analysis data is blocked by analyzing that the disaster factor has not occurred. In Claim 1 or Claim 2, the analysis unit,
After the fifth data that exceeds the set value in any second time period is received, the seventh data that is the same as or increased to the fifth data in the second time period after the arbitrary second time period is An early warning system for a disaster situation of a traditional wooden building, wherein if received, the disaster factor is analyzed and the analysis data is generated. In Claim 1, the analysis unit,
When the third data generated at an arbitrary second time period is equal to or greater than the set value, it is sequentially received from the sensor in units of seconds until 1 minute ± 15 seconds elapses from the time when the third data is generated. Compared to the fourth data for obtaining the value of the second difference generated in the arbitrary second time period, and all the received eighth data is equal to or greater than the set value. If there is an analysis that the disaster factor has occurred, and if any of the eighth data received within one minute is less than or equal to the set value, the disaster factor is An early warning system for the disaster situation of traditional wooden buildings, characterized by analyzing that it has not occurred. In Claim 1, the setting unit,
Since it is difficult to apply a uniform set value depending on environmental conditions such as location, position, season, etc., the wooden set building is characterized in that the set value is automatically applied according to the set cycle after a set cycle. Early warning system for disaster situations. In Claim 1 or Claim 5, the setting unit,
Since it is difficult to apply uniform set values depending on environmental conditions such as location, position, season, etc., the above set values are applied by numerical calculation by the user. system. In Claim 1, the sensor is
An early warning system for disaster situations in traditional wooden buildings, characterized by being one of a temperature sensor, smoke sensor, or humidity sensor. 8. The sensor according to claim 7, wherein the sensor
An early stage of a disaster of a traditional wooden building characterized by comprising a human body sensor after being configured to include at least one of the temperature sensor, the smoke sensor, and the humidity sensor Alarm system. In Claim 1, the server is
When a large number of sensors are configured, the setting unit obtains the setting value for each of the large number of sensors, and transmits the setting value for each sensor through the transmission unit. Early warning system for the disaster situation of goods. A first sensor that generates first data for each set first time period;
A second sensor that generates second data for each set first time period;
A server and
The server
A receiving unit that receives the generated first and second data by grouping together the same first time periods to form a plurality of pairs;
A setting unit that obtains a first difference value for each of the paired first and second data, and sets a maximum difference value as a set value;
An input unit for inputting a second time period by the user;
The first sensor is received in the second time period by receiving the set value set in the setting unit and transmitting the second time period input by the input unit to the first and second sensors. A plurality of third data generated by the second sensor and a plurality of fourth data generated by the second sensor are grouped together in the same second time period, and the third and fourth data are 2) Find the difference value, compare the respective second difference value with the set value, and analyze that the disaster factor has occurred for any second difference value that is higher than the set value An analysis unit for generating data;
A transmission unit configured to transmit the second time period input via the input unit to the first and second sensors and transmit the analysis data generated via the analysis unit to a management terminal. An early warning system for disaster situations in traditional wooden buildings.

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