Space monitoring system and space monitoring method using acoustic signals

Abstract

The present invention relates to a space monitoring system and a space monitoring method using an acoustic signal, and discloses a technology for easily, quickly, and accurately determining the status of a monitored space by comparing frequency response spectra for each measurement period for a monitored space in individual frequency units or frequency interval units and analyzing the degree and pattern of change in the difference values.

Description

[Technical Field]

[0001] The present invention relates to a space monitoring system and a space monitoring method using an acoustic signal, and provides a technology for easily, quickly, and accurately determining the physical state of a monitored space by comparing frequency response spectra for each measurement period for the monitored space in individual frequency units or frequency interval units and analyzing the degree and pattern of change in the difference values. [Background technology]

[0002] A spatial situation monitoring sensor technology has been presented that uses acoustic signals to detect various situations such as an intrusion of an outsider into an indoor space, an outbreak of a fire, or a gas leak.

[0003] In the conventional technology, sound of multiple frequencies is emitted into a sensing target space for each measurement period, the sound is received, and a sound pressure spectrum of the received sound is obtained. The measured sound pressure spectrum is compared with a specific reference sound pressure spectrum, and the situation of the target space is judged based on the degree and pattern of change in the spectrum.

[0004] If the measured sound pressure spectrum fluctuates by more than a reference value, it can be determined that some event has occurred in the monitored space. However, to determine the type of event that has occurred in the monitored space, for example, whether it is the movement of an object or a change in temperature, it is necessary to observe the fluctuation pattern of the sound pressure spectrum.

[0005] To explain what is needed to accurately observe the fluctuation pattern of the sound pressure spectrum, let us take an infrared sensor as an example. For example, an infrared sensor installed in an automatic door only needs to measure whether there is a warm object in front of the door. Here, the infrared sensor only needs to measure the amount or change of infrared rays entering the sensor. In other words, one pixel of the infrared sensor is sufficient to determine whether an event has occurred.

[0006] However, if an infrared sensor has only one pixel, it can detect the occurrence of an event, but it cannot distinguish the type of event. For example, it cannot distinguish whether a warm object in front of a gate is a human or an animal. However, a military infrared camera needs to distinguish whether a warm object that appears at night is a human or an animal. This requires two factors. First, the number of pixels must be large enough. Second, the resolution must be high enough. To achieve this, the area of ​​the monitored object detected by one pixel must be small. For example, if one pixel detects an area of ​​1m x 1m, it will be impossible to distinguish between humans and animals, but if one pixel detects an area of ​​1cm x 1cm, it will be possible to distinguish between humans and animals.

[0007] The same is true for acoustic sensors. For an acoustic sensor to determine whether an event has occurred, it only needs to determine the "presence" or "degree" of fluctuation in the sound pressure spectrum. Therefore, measuring the sound pressure spectrum two or three times may be sufficient. However, to determine whether the event is movement or a temperature change, the "pattern" of spectrum fluctuation over time must be observed. However, two factors are necessarily required to clearly observe this "pattern." First, the spectrum must be measured a sufficiently large number of times, and second, the interval between spectrum measurements must be sufficiently short.

[0008] For example, if conventional technology is applied to measure the sound pressure spectrum in a monitored space once at a measurement interval of 5 seconds, if 20 to 30 measurement points are required to observe the spectrum fluctuation pattern, the time required for this will be 100 to 150 seconds, which will slow down the measurement speed accordingly.

[0009] On the other hand, if the spectrum were measured once every five seconds, the time interval between measurement points would be too long to accurately determine the type of event. In other words, the resolution would be too low to adequately represent the spectrum variation pattern over time. For example, if an intruder moves at a speed of 2 meters per second and the spectrum variation must be represented every time the intruder's position changes by 10 cm, conventional technology would require measuring the spectrum 20 times per second. However, measuring the spectrum once every 0.05 seconds is not practical.

[0010] In summary, conventional spatial situation monitoring sensors can detect the occurrence of an event, but it takes a long time to distinguish whether the event is an object movement or a temperature change, and the resolution is low, so the accuracy of distinguishing the event type cannot be guaranteed. Summary of the Invention [Problem to be solved by the invention]

[0011] Conventional acoustic space monitoring sensors can detect the occurrence of an event, but they have problems in that it is difficult to distinguish the type of event and it takes a long time.

[0012] The present invention has been devised to solve the problems of the prior art as described above, and provides a technology that can distinguish the type of event occurring in a monitored space more quickly, accurately, and easily by observing the change pattern of the spectrum.

[0013] The objects of the present invention are not limited to those described above, and other objects and advantages of the present invention that have not been mentioned can be understood from the following description. [Means for solving the problem]

[0014] One embodiment of the space monitoring method using an acoustic signal according to the present invention may include a frequency response measurement step of emitting an acoustic signal into a monitored space for each measurement period, receiving the acoustic signal, and acquiring a frequency response spectrum for each measurement period; a difference value calculation step of comparing the frequency response spectrum of a specific period with a comparison target frequency response spectrum in individual frequency units or frequency interval units, and calculating a difference value for each individual frequency unit or frequency interval unit; a difference value storage step of matching the difference value with one or more of the frequency or the measurement time and storing the difference value in a database; and a space situation determination step of determining the situation of the monitored space based on the degree or pattern of variation in the difference value depending on the frequency or the measurement time.

[0015] Preferably, the difference value calculation step compares the frequency response spectrum of a specific period with the frequency response spectrum of at least one other measurement period, and the difference value storage step can store the difference value by matching it with the frequency or the measurement time, the measurement time interval of the frequency response spectrum of the specific period, and the measurement time interval of the frequency response spectrum of the other measurement period.

[0016] As an example, the frequency response measuring step may emit a single-tone acoustic signal into the monitored space whose frequency changes continuously or gradually over time, and the spatial situation determining step may determine that there is a change in the physical shape of the monitored space in a second frequency interval or a second time interval if the degree of scattering of the difference value in a first frequency interval or a first time interval is maintained below a first criterion and then exceeds a second criterion in the second frequency interval or the second time interval.

[0017] As an example, the spatial situation determination step may determine that there is a change in the physical shape of the monitored space in a third frequency interval or a third time interval if the degree of dispersion of the difference values ​​in the third frequency interval or the third time interval exceeds a third criterion.

[0018] As an example, the spatial situation determination step may determine that there is a temperature change in the monitored space in the fourth frequency interval or the fourth time interval if the degree of dispersion of the difference values ​​in the fourth frequency interval or the fourth time interval exceeds a fourth criterion and the degree of dispersion of the difference values ​​in the fifth frequency interval or the fifth time interval included in the fourth frequency interval or the fourth time interval is less than a fifth criterion.

[0019] Furthermore, one embodiment of the space monitoring system using acoustic signals according to the present invention may include a frequency response measurement means for measuring a response spectrum, comparing a frequency response spectrum of a specific period with a comparison target frequency response spectrum by corresponding the frequency response spectrum in individual frequency units or frequency interval units, and calculating a difference value for each individual frequency unit or frequency interval unit, a database construction means for matching the difference value with one or more of the frequency or the measurement time and storing the matched difference value in a database, and a space situation determination means for determining the situation of the monitored space based on the degree or pattern of variation of the difference value depending on the frequency or the measurement time.

[0020] Preferably, the frequency response measurement means compares the frequency response spectrum of a specific period with the frequency response spectrum of at least one other measurement period, and the database construction means can store the difference value by matching it with the frequency or the measurement time, the measurement time interval of the frequency response spectrum of the specific period, and the measurement time interval of the frequency response spectrum of the other measurement periods.

[0021] As an example, the frequency response measurement means emits a single-tone acoustic signal into the monitored space, the frequency of which changes continuously or stepwise over time, and the spatial situation determination means can determine that there is a change in the physical shape of the monitored space in the second frequency interval or the second time interval when the degree of dispersion of the difference value between a first frequency interval or a first time interval is maintained below a first criterion and then the degree of dispersion of the difference value in the second frequency interval or the second time interval exceeds a second criterion.

[0022] As an example, if the dispersion of the difference values ​​in a third frequency interval or a third time interval exceeds a third criterion, the spatial situation judgment means can judge that there is a change in the physical shape of the monitored space in the third frequency interval or the third time interval.

[0023] As an example, the spatial situation judgment means can determine that there is a temperature change in the monitored space in the fourth frequency interval or the fourth time interval if the degree of dispersion of the difference values ​​in the fourth frequency interval or the fourth time interval exceeds a fourth criterion and the degree of dispersion of the difference values ​​in the fifth frequency interval or the fifth time interval included in the fourth frequency interval or the fourth time interval is less than a fifth criterion. [Effects of the Invention]

[0024] According to the present invention, the frequency response spectrum for each measurement period of the monitored space is subdivided and compared in individual frequency units or frequency intervals, and the degree and pattern of change in the difference values ​​are analyzed. Since the time interval or frequency interval of the calculated difference values ​​is sufficiently narrow, the present invention can quickly and accurately distinguish the type of event occurring in the monitored space, such as movement or temperature change.

[0025] The effects of the present invention are not limited to those mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art to which the present invention pertains from the following description. [Brief explanation of the drawings]

[0026] [Figure 1] 1 is a configuration diagram of an embodiment of a space monitoring system according to the present invention; [Figure 2] 1 is a block diagram of an embodiment of a frequency response measuring means of a space monitoring system according to the present invention; [Figure 3] 1 is a block diagram of an embodiment of a database construction means of a space monitoring system according to the present invention; [Figure 4] 1 is a block diagram of an embodiment of a space situation determination means of a space monitoring system according to the present invention; [Figure 5]1 is a flowchart of an embodiment of a space monitoring method according to the present invention. [Figure 6] FIG. 2 is a diagram illustrating an example of obtaining a frequency response spectrum according to the present invention. [Figure 7] 1 is a diagram showing an example of extracting measurement values ​​for individual frequencies or frequency intervals according to the present invention; [Figure 8] 10 is a diagram illustrating an example of extracting a difference value by comparing frequency response spectra by frequency according to the present invention; FIG. [Figure 9] FIG. 10 is a diagram showing an example of a multi-dimensional data table for difference values ​​according to the present invention. [Figure 10] 10A and 10B are diagrams illustrating an example of the degree and pattern of fluctuation of differential values ​​for different event types according to the present invention; [Figure 11] FIG. 2 is a diagram illustrating an example of determining a motion event of an object in a monitored space according to the present invention. [Figure 12] FIG. 2 is a diagram illustrating an example of determining a motion event of an object in a monitored space according to the present invention. [Figure 13] FIG. 2 is a diagram illustrating an example of determining a motion event of an object in a monitored space according to the present invention. [Figure 14] FIG. 2 is a diagram illustrating an example of determining a motion event of an object in a monitored space according to the present invention. [Figure 15] FIG. 10 is a diagram showing an example of determining a temperature change event in a monitored space according to the present invention. [Figure 16] FIG. 10 is a diagram showing an example of determining an event in a monitored space using a multidimensional data table for difference values ​​according to the present invention. [Figure 17] FIG. 10 is a diagram showing an example of determining an event in a monitored space using a multidimensional data table for difference values ​​according to the present invention. [Figure 18] FIG. 10 is a diagram showing an example of determining an event in a monitored space using a multidimensional data table for difference values ​​according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0027] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, but the present invention is not limited to or construed as being limited by the embodiments.

[0028] For the purposes of explaining the invention, its operating advantages, and objects attained by its practice, reference will now be made to preferred embodiments of the invention, which are illustrated and described in detail below.

[0029] First, the terms used in this application are merely used to describe specific embodiments and are not intended to limit the present invention, and singular expressions can include plural expressions unless the context clearly dictates otherwise. Furthermore, in this application, terms such as "include" or "have" are intended to specify the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, and should be understood not to preclude the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0030] In the description of the present invention, if it is determined that a detailed description of related known structures or functions may obscure the gist of the present invention, the detailed description will be omitted.

[0031] The spatial frequency response (FR) referred to in this invention is the sound pressure or phase measured by receiving an acoustic signal after emitting a single sound signal whose frequency changes over time or a complex sound containing multiple frequency components whose frequency does not change over time into a monitored space for each measurement period. A graph of the sound pressure or phase measured during one measurement period according to frequency is called a frequency response spectrum (FRS).

[0032] By measuring the frequency response spectrum, it is possible to identify an event occurring in a monitored space based on the degree and pattern of change. The present invention provides a technology that can identify the occurrence and type of an event more quickly and accurately.

[0033] The present invention compares a frequency response spectrum measured at a specific measurement period in a monitored space with a comparison frequency response spectrum in individual frequency units or frequency interval units to extract difference values ​​for each frequency, and determines the event situation in the monitored space based on the degree and pattern of fluctuation of the difference values ​​over frequency or time.

[0034] FIG. 1 is a diagram showing the configuration of an embodiment of a space monitoring system using acoustic signals according to the present invention.

[0035] The space monitoring system may include a frequency response measuring means 100, a database building means 200, a space situation determining means 300, and the like.

[0036] The frequency response measurement means 100 measures the frequency response of the space to be monitored at a measurement period, and can obtain the corresponding frequency response spectrum.

[0037] Furthermore, the frequency response measurement means 100 can compare a frequency response spectrum of a specific period with a comparison frequency response spectrum to calculate a difference value for each individual frequency or each frequency interval.

[0038] For example, a measurement value for each individual frequency or frequency interval extracted from a frequency response spectrum of a specific period may be compared with a measurement value for each individual frequency or frequency interval extracted from a frequency response spectrum of another period or a reference frequency response spectrum to calculate a frequency-specific difference value for sound pressure or phase. That is, the present invention may compare both spectra for each corresponding frequency to calculate a frequency-specific difference value for sound pressure or phase.

[0039] The database construction means 200 can organize, process and store the frequency-specific measurement values ​​for each measurement period extracted by the frequency response measurement means 100.

[0040] Furthermore, the database construction means 200 can organize, process and store the frequency-specific difference values ​​calculated by the frequency response measurement means 100 .

[0041] For example, the database construction means 200 may store each difference value by matching it with the frequency or the measurement time, the measurement time interval of the frequency response spectrum for a specific period, and the measurement time interval of the frequency response spectrum for another measurement period. That is, the database construction means 200 may generate and store a multidimensional data table for the difference values. The database construction means 200 may build a database by updating the multidimensional data table with the difference values ​​calculated for each new measurement period.

[0042] The space situation determination means 300 can determine the situation of the monitored space based on the measurement value or difference value generated by the frequency response measurement means 100. Here, the space situation determination means 300 can determine the situation of the monitored space by accurately distinguishing the type of event that occurred in the monitored space within a shorter time period using the measurement value information and difference value information stored in the database construction means 200. For example, the space situation determination means 300 can determine the event situation of the monitored space based on the degree and pattern of fluctuation of the difference value in a selected frequency interval or time interval.

[0043] Hereinafter, each configuration of the space monitoring system according to the present invention will be described with reference to an embodiment.

[0044] FIG. 2 is a block diagram of an embodiment of the frequency response measuring means of the space monitoring system according to the present invention.

[0045] The frequency response measurement means 100 may include a frequency response measurement section 110, a measurement value extraction section 130, a difference value calculation section 150, and the like.

[0046] For example, the frequency response measurement unit 110 may include an acoustic signal emitter 111, an acoustic signal processor 113, and an acoustic signal receiver 115, and may measure a frequency response of a space to be monitored using an acoustic signal. The frequency response measurement unit 110 may emit an acoustic signal to the space to be monitored for each measurement period, receive the acoustic signal, and measure a frequency response of the space for each measurement period.

[0047] The acoustic signal emitter 111 includes a means for emitting an acoustic signal, such as a speaker, and can emit an acoustic signal into the monitored space. Here, the acoustic signal emitter 111 can emit various types of acoustic signals.

[0048] For example, the audio signal emitter 111 may emit only one frequency sound at a particular time, but may emit a single audio signal whose frequency changes continuously or stepwise over time, or may emit a complex audio signal containing multiple frequency components whose frequency does not change over time.

[0049] The acoustic signal receiver 115 may include various measuring means such as a microphone capable of measuring sound pressure, sound intensity, and the like.

[0050] The acoustic signal emitter 111 and the acoustic signal receiver 115 may be configured as a single device and placed in the same location, or the acoustic signal emitter 111 and the acoustic signal receiver 115 may be configured as different devices and placed in different locations apart from each other.

[0051] The acoustic signal processor 113 can provide an acoustic signal to be emitted into the monitored space to the acoustic signal emitter 111. The acoustic signal processor 113 can also measure the frequency response of the space based on the acoustic signal received by the acoustic signal receiver 115.

[0052] For example, if the acoustic signal is a complex sound consisting of multiple frequency components, the acoustic signal processor 113 can convert the received acoustic signal into the frequency domain using a Fourier transform (FT) or a fast Fourier transform (FFT) to measure the spatial frequency response and obtain a frequency response spectrum from the converted signal.

[0053] As another example, if the acoustic signal is a single sound whose frequency changes continuously or stepwise over time, the acoustic pressure or phase value that changes over time can be measured and replaced with the acoustic pressure or phase value that changes over frequency. In this case, the acoustic signal processor 113 can directly measure the spatial frequency response without Fourier transforming the received acoustic signal. From this, the frequency response spectrum can be obtained.

[0054] The measurement value extractor 130 can extract measurement values ​​for sound pressure or phase from the frequency response spectrum for each individual frequency or each frequency interval. The measurement values ​​extracted by the measurement value extractor 130 for each measurement period can be transmitted to the database constructor 200 for organization and storage.

[0055] The difference value calculation section 150 can calculate a difference value by comparing the frequency response spectrum of a specific period with the frequency response spectrum to be compared in correspondence with each other in individual frequency units or in frequency interval units.

[0056] Here, the comparison frequency response spectrum may be a frequency response spectrum of another period or a reference frequency response spectrum, which may be a frequency response spectrum measured in a calm state where no significant event occurs in the monitored space.

[0057] As an example, the difference value calculation unit 150 may calculate a difference value by comparing a measurement value extracted from a frequency response spectrum of a specific period with a measurement value extracted from a frequency response spectrum of another period or a reference frequency response spectrum, in units of corresponding individual frequencies or in units of frequency sections.

[0058] For example, the difference value calculation section 150 can calculate a difference value by comparing the frequency response spectrum of a specific period with the frequency response spectrum of multiple other measurement periods. For example, the difference value can be calculated by comparing the frequency response spectrum of the current period with the frequency response spectrum of many previous periods, such as the frequency response spectrum of one period before, the frequency response spectrum of two periods before, etc.

[0059] The difference values ​​calculated by the difference value calculation unit 150 can be organized and stored in the database construction means 200.

[0060] FIG. 3 is a block diagram showing an embodiment of the database construction means of the space monitoring system according to the present invention.

[0061] The database construction means 200 may include a measurement value information processing unit 210, a difference value information processing unit 220, a data management unit 230, and a database 250. The database 250 may be configured as a single integrated storage medium, or may be configured as separate storage media for a measurement value information storage unit 260 and a difference value information storage unit 270. The database 250 may also be configured by selectively using a permanent storage medium such as a hard disk or a temporary storage medium such as a buffer, or by both of them.

[0062] The measurement value information processing unit 210, in cooperation with the frequency response measurement means 100, can organize the measurement values ​​extracted from the frequency response spectrum for each measurement interval in the order of individual frequencies or in the order of measurement times, and store them in the database 250. Preferably, the measurement value information processing unit 210 can store the measurement value information in the measurement value information storage unit 260 in association with the frequency or the measurement time.

[0063] The differential value information processing unit 220 can receive differential value information in conjunction with the frequency response measurement means 100 , organize and process the information, and store it in the differential value information storage unit 270 .

[0064] As an example, the differential value information processing unit 220 can store each differential value by matching it with the frequency or the measurement time, the measurement time interval of the frequency response spectrum of the specific period being compared, and the measurement time interval of the frequency response spectrum of another measurement period being compared.

[0065] Furthermore, when new difference value information is acquired or when an update period has passed, the difference value information processing unit 230 can update the database by reflecting the new difference value information.

[0066] The data management unit 230 can maintain and manage the data stored in the measurement value information storage unit 260 and the difference value information storage unit 270 .

[0067] As an example, if the number of measurement information stored in the measurement information storage unit 260 exceeds the preset number of pieces to be stored or the retention time of the stored measurement information exceeds the preset retention time, the data management unit 230 may sequentially remove measurement information with older measurement periods from the measurement information storage unit 260.

[0068] As an example, if the number of pieces of differential value information stored in the differential value information storage unit 270 exceeds the preset number of pieces to be stored or the retention time of the stored differential value information exceeds the preset retention time, the data management unit 230 may sequentially remove differential value information with older measurement periods from the differential value information storage unit 260.

[0069] In this way, the database construction means 200 can organize, process, and cumulatively store measurement value information and difference value information, including the above-mentioned configuration, and provide the stored data when determining the situation in the monitored space.

[0070] FIG. 4 is a block diagram of an embodiment of the space situation determination means of the space monitoring system according to the present invention.

[0071] The space situation determination means 300 may include a data analysis unit 310, an event situation determination unit 330, a situation information providing unit 350, and the like.

[0072] The data analysis unit 310 can receive difference value information calculated by comparing a plurality of frequency response spectra from the database construction unit 200. The data analysis unit 310 can then analyze the degree and pattern of change in the difference values.

[0073] The event situation determination unit 330 can determine the situation of the target space based on the analysis result of the data analysis unit 310.

[0074] For example, the event status determination unit 330 may compare the analysis results of the degree of change and the change pattern of the difference value with the determination criteria information to determine the status of the monitored space.

[0075] The data analysis unit 310 analyzes the difference value, and the event status determination unit 330 determines the status of the monitored space based on the difference value, as will be described in detail later with reference to the following embodiments.

[0076] The status information providing unit 350 can provide the status information of the monitored space determined by the event status determining unit 330 to the user or manager.

[0077] The status information provided by the status information providing unit 350 may include various event status information such as an intrusion into the monitored space, a fire, etc. In addition, the status information providing unit may provide a multidimensional data table image that represents the current status of the monitored space over time.

[0078] The present invention also provides a space monitoring method using an acoustic signal. Hereinafter, the space monitoring method according to the present invention will be described with reference to the above-described embodiment of the space monitoring system according to the present invention.

[0079] To determine the specific nature of an event that occurred in a monitored space, it is necessary to observe the fluctuation pattern of the frequency response spectrum. In conventional technology, to investigate the spectrum fluctuation pattern, each time a spectrum is measured, the newly measured spectrum is compared with a reference spectrum. Therefore, if the spectrum is measured once every five seconds, the spectrum fluctuation pattern can be observed at five-second intervals.

[0080] As mentioned above, in order to quickly and accurately determine the type of event that has occurred in the monitored space, it is necessary to observe the spectrum fluctuation pattern more quickly, for example, at intervals of 0.05 seconds. However, it is practically impossible to measure the spectrum at intervals of 0.05 seconds.

[0081] In the present invention, when a measured spectrum is compared with a comparison target spectrum, the comparison is not made on a spectrum-by-spectrum basis, but on a frequency-by-frequency basis that constitutes the spectrum.

[0082] For example, suppose a spectrum consists of 100 points representing sound pressure in 1 Hz increments, starting from 1001 Hz to 1100 Hz. The prior art compares a spectrum consisting of 100 points with a comparison spectrum consisting of 100 points to calculate a single difference value. For example, if there is a 2.4% difference between the two spectra, a single difference value of 2.4% is extracted.

[0083] In the present invention, each of the 100 frequency-specific sound pressure values ​​constituting one spectrum is compared with the corresponding 100 frequency-specific sound pressure values ​​of a comparison spectrum to extract 100 difference values. Therefore, if the measurement time for a spectrum consisting of 100 points is 5 seconds, a sound pressure value corresponding to one frequency is extracted every 0.05 seconds. Therefore, according to the present invention, one difference value is calculated at intervals of 0.05 seconds.

[0084] In the prior art, one difference value is generated at intervals of 5 seconds, but in the present invention, one difference value is generated at intervals of 0.05 seconds, which allows for much faster and more accurate determination of the type of event occurring in the monitored space. How this is possible will be described in detail below.

[0085] FIG. 5 shows a flowchart of one embodiment of a space monitoring method according to the present invention.

[0086] The frequency response measurement means 100 measures the spatial frequency response of the monitored space (S110), and based on this, can obtain a frequency response spectrum (S120).

[0087] For example, the frequency response measurement unit 100 may emit or receive an acoustic signal to or from the monitored space at each measurement period. Here, the acoustic signal may be a complex sound signal consisting of multiple frequency components whose frequency does not change over time, as described above, or a single sound signal whose frequency changes continuously or stepwise over time.

[0088] The frequency response measuring means 100 measures the frequency response of the space for each measurement period based on the received acoustic signal, and based on this, can obtain a frequency response spectrum for sound pressure or phase for each measurement period.

[0089] An example of obtaining a frequency response spectrum in the present invention will be described with reference to Fig. 6. Fig. 6 shows a case where a frequency response spectrum is obtained using an acoustic signal whose frequency continuously changes over time.

[0090] As shown in FIG. 6(a), the frequency response measuring means 100 measures the time t S From t E An emitted sound 411 whose frequency continuously changes from fmin to fmax during the measurement period up to can be emitted into the monitored space.

[0091] Here, the magnitude of the sound pressure of the emitted sound emitted by the frequency response measuring means 100 into the monitored space is, as shown in FIG. 6(b), S From t E It can be set to the same magnitude 413 with a frequency that continuously changes from fmin to fmax during the measurement period.

[0092] 6(c) shows a frequency response spectrum 415 measured by the frequency response measurement means 100 after receiving sound in the monitored space. S From t E Since the frequency of the emitted sound changes continuously from fmin to fmax, the sound pressure of the received sound is S From t E During the measurement period up to , the frequency response spectrum 415 can be measured corresponding to the frequency from fmin to fmax.

[0093] The acoustic signal received by the acoustic signal receiver 115 of the frequency response measuring means 100 is the sum of many signals that are reflected and refracted at various parts of the monitored space and then enter the receiver, so the received acoustic signal is affected by the physical environment of the monitored space. Therefore, even though the magnitude of the emitted sound 411 emitted by the frequency response measuring means 100 into the monitored space is the same for each frequency (413), the frequency response spectrum 415 acquired by the frequency response measuring means 100 in the monitored space appears to have different magnitudes for each frequency.

[0094] The frequency response measurement means 100 can extract measurement values ​​for sound pressure or phase value for each individual frequency or each frequency interval from the frequency response spectrum acquired for each measurement period (S130). An example of extracting measurement values ​​for each individual frequency or each frequency interval from the frequency response spectrum will be described with reference to FIG.

[0095] Figure 7(a) shows a case where the frequency response measurement means 100 emits a single sound acoustic signal 421 whose frequency changes stepwise from f1 to f6 during a measurement period from time t1 to t7 into the monitored space, and acquires a frequency response spectrum 423 using the received sound received from the monitored space.

[0096] Frequency response measurement means 100 can extract sound pressure measurement values ​​424 for individual frequency units from frequency response spectrum 423. In this case, the frequency of emitted sound 421 changes stepwise from f1 to f6 during the measurement period from time t1 to t7, so that measurement values ​​424 for each of the individual frequency units f1 to f6 can be extracted on frequency response spectrum 423 corresponding to this.

[0097] Figure 7(b) shows a case where the frequency response measuring means 100 emits a single sound acoustic signal 425 into the monitored space, whose frequency continuously changes from fmin to fmax during the measurement period from time t1 to t7, and acquires a frequency response spectrum 427 using the received sound received from the monitored space.

[0098] The frequency response measurement means 100 divides the frequency response spectrum 427 into frequency intervals, calculates the average or representative value of the sound pressure value for each frequency interval (f1 to f2, f2 to f3, etc.), and extracts the measurement value 428 for each frequency interval.

[0099] The frequency response measurement means 100 provides the extracted measurement values ​​to the database construction means 200, and the database construction means 200 can organize and process the measurement values, match them with the corresponding frequency or the corresponding measurement time for each measurement period, and store the measurement values.

[0100] The frequency response measurement means 100 can compare the frequency response spectrum of a specific period with the frequency response spectrum to be compared in individual frequency units or in frequency interval units, and calculate the difference value for each individual frequency unit or each frequency interval unit (S140).

[0101] As an example, the frequency response measurement means 100 can extract measurement values ​​for individual frequencies or frequency intervals from the frequency response spectrum of a specific period, compare them with measurement values ​​for individual frequencies or frequency intervals extracted from the frequency response spectrum of one or more other periods stored in the database construction means 200, and calculate a difference value for each individual frequency or frequency interval.

[0102] As another example, the frequency response measurement means 100 may extract measurement values ​​for individual frequencies or frequency intervals from a frequency response spectrum of a specific period, compare the extracted measurement values ​​with the measurement values ​​for the individual frequencies or frequency intervals of a reference frequency response spectrum, and calculate a difference value for each individual frequency or frequency interval. Here, the reference frequency response spectrum may be a frequency response spectrum that can be measured in a calm state where no event situation occurs in the monitored space.

[0103] An example of comparing frequency response spectra to calculate a difference value will be described with reference to FIG.

[0104] As shown in (a) of FIG. 8, a measurement value 432 extracted in each individual frequency unit from a frequency response spectrum 431 of a current measurement period and a measurement value 434 extracted in each individual frequency unit from a frequency response spectrum 433 of a previous measurement period can be matched according to the number of individual frequency units to calculate a difference value d between the measurement values ​​432 and 434.

[0105] In this way, the frequency response spectrum 431 of the current measurement period is compared with the frequency response spectrum 433 of the immediately preceding measurement period in correspondence with each other in individual frequency units, and the calculated difference value can be obtained as shown in Figure 8(b). Similar to this process, the frequency response spectrum of a specific measurement period can also be compared with the reference frequency response spectrum in correspondence with each other to calculate the difference value.

[0106] The calculated difference value can be provided to the database construction means 200, and the database construction means 200 can process, organize and store the difference value (S150).

[0107] For example, the database construction means 200 can store the difference values ​​by matching them with the frequency or the measurement time, the measurement time interval of the frequency response spectrum of the specific period compared, and the measurement time interval of the frequency response spectrum of the other measurement period compared. Furthermore, the database construction means 200 can generate and store a multidimensional data table for the difference values.

[0108] 9 shows an example of a multidimensional data table for differential values ​​according to the present invention. Fig. 9 shows data tables 510 and 520 for differential values ​​calculated by comparing the frequency response spectrum of the current period with the frequency spectra of the previous 10 measurement periods in individual frequency intervals, in which the spatial frequency response is measured by emitting a single sound whose frequency continuously changes from 3098 Hz to 4078 Hz over a 6-second measurement period, and comparing the frequency response spectra in individual frequency intervals.

[0109] In the data tables 510 and 520, the b value 511 indicates the center frequency of each frequency interval unit, which is an individual frequency from 4000 Hz to 4076 Hz, and the individual frequency can be replaced with the measurement time for the corresponding frequency in the current measurement period. Alternatively, the b value 511 can be embodied as a data table by matching the corresponding frequency and the corresponding measurement time.

[0110] The a value 513 indicates the measurement time interval for the frequency response spectrum measurement time of a specific period compared to the measurement time of the frequency response spectrum of other measurement periods, i.e., the frequency response measurement time 6 seconds before the current period, and the frequency response measurement time 60 seconds before the previous period, which is the 10th period.

[0111] FIG. 9(a) is an example of a data table 510 in which difference values ​​are indicated by color classification, and FIG. 9(b) is an example of a data table 520 in which difference values ​​are indicated by bar height classification.

[0112] The difference values ​​515, 525 between the frequency-specific measurement value of a specific measurement period and the frequency-specific measurement value of a measurement period 6 seconds prior can be indicated by color or bar height divisions. In this way, the difference values ​​from the current period to the period 60 seconds prior can be embodied as color or bar height divisions and implemented as a multidimensional data table.

[0113] Furthermore, Figure 9 shows a data table for difference values ​​obtained by comparing the frequency response spectrum of a specific measurement period with the frequency response spectrum of multiple other measurement periods. Such a data table can be generated for each measurement period to generate a higher-dimensional data table. That is, although not shown in Figure 9, a data table can be generated with each of multiple measurement periods as a specific period, and a higher-dimensional data table can be generated by applying the c value to each specific period as another axis. The database construction means 200 can then update the multidimensional data table to reflect the difference values ​​obtained for each new measurement period.

[0114] The space situation determination means 300 determines the degree of fluctuation or fluctuation pattern of the difference value based on the difference value obtained by comparing the frequency response spectrum for each measurement period stored in the database (S160), and based on this, can determine the event situation occurring in the monitored space (S170).

[0115] Preferably, the space situation determination means 300 can grasp the degree or pattern of fluctuation of the difference value in the selected frequency interval or time interval, and can immediately determine the occurrence of an event in the monitored space and also determine the type of the event.

[0116] Hereinafter, a method for distinguishing the type of event occurring in a monitored space based on the degree or pattern of fluctuation of differential values ​​according to the present invention will be described with reference to various embodiments.

[0117] 10 shows an example of the degree of fluctuation and fluctuation pattern of the difference value for each different event type according to the present invention. In this example, the frequency response spectrum of the monitored space is measured using a single sound signal whose frequency changes over time for each measurement period, and the frequency response spectrum of the current measurement period is compared with the frequency response spectrum of another measurement period to calculate the difference value.

[0118] (a) of Figure 10 shows the difference value obtained by comparing the frequency response spectrum of the current measurement period with the frequency response spectrum of a period 6 seconds prior, (b) of Figure 10 shows the difference value obtained by comparing the frequency response spectrum of the current measurement period with the frequency response spectrum of a period 30 seconds prior, and (c) of Figure 10 shows the difference value obtained by comparing the frequency response spectrum of the current measurement period with the frequency response spectrum of a period 60 seconds prior.

[0119] The graph on the left in Figure 10 shows the degree and pattern of fluctuation in the differential value when there has been no movement in the monitored space for the past 60 seconds, but a sudden movement occurs at the current time. Because there was no movement 6, 30, or 60 seconds ago, the spectra measured at these times are similar. Therefore, when comparing the currently measured spectrum with the spectra from 6, 30, and 60 seconds ago, the shapes of the differential values ​​are also similar. If an intrusion into the monitored space occurs and the intruder is moving within the monitored space, the differential value will suddenly change or fluctuate overall within the G1 range.

[0120] The graph on the right of Figure 10 shows the degree and pattern of fluctuation in the difference value when a fire breaks out in the monitored space 60 seconds prior and the temperature continues to rise. In the case of a fire, temperature changes are not significant over a period of approximately 6 seconds, so the difference value calculated by comparing the current time point with 6 seconds prior does not change significantly overall and fluctuates at a constant level within the G2 range. However, because the temperature continues to rise over time in the case of a fire, the temperature difference between the two points in time increases the longer the measurement interval between the spectra being compared. Therefore, the difference value calculated by comparing the current time point with 30 seconds prior shows a larger overall change and takes on a shape similar to a sine curve within the G3 range. Meanwhile, the difference value calculated by comparing the current time point with 60 seconds prior shows a significantly larger overall change and takes on a shape similar to a sine curve within the G4 range.

[0121] When the temperature of the monitored space changes, the frequency response spectrum measured in the monitored space shifts to the left (in the case of cooling) or right (in the case of heating) in proportion to the temperature change. When the temperature change is small, the frequency shift is also small, and the frequency-unit difference value d between the two spectra is also small (650). However, the larger the temperature change, the larger the frequency shift, so the frequency-unit difference value d between the two spectra also increases. Due to the frequency shift, d inevitably becomes negative in some frequency regions and positive in other frequency regions. Therefore, when viewed over the entire spectrum, d has a shape with alternating negative and positive intervals, like a sine curve (670). Here, the period in which the difference value d rises and falls like a sine curve is similar to the period of the frequency response spectrum. In other words, if the shape of the frequency response spectrum is identical to a sine curve, when a frequency shift occurs, the shape of the difference value d that appears also becomes a sine curve, and its period is identical to the period of the frequency response curve.

[0122] In this way, the change pattern of the spectral difference values ​​appears uniquely depending on whether the event occurring in the monitored space is a temperature change or a physical shape change, so according to the present invention, it is possible to very quickly and accurately determine the type of event that has occurred in the monitored space.

[0123] First, the event determination when an object movement occurs in the monitored space will be described with reference to FIGS.

[0124] Assume that difference values ​​are calculated as shown in Fig. 11. For convenience of explanation, Fig. 11 shows the difference values ​​as lines, but in reality, the difference values ​​appear as points corresponding to different frequencies, as shown in Figs. 12 to 14.

[0125] 11 to 14 show the difference values ​​corresponding to the measurement times, and the measurement times can be replaced with the frequencies. As described above, the difference values ​​can be matched with one or more of the frequencies or the measurement times and stored in a database. If a specific measurement period and the frequency are known, the measurement time corresponding to the frequency can be found, and conversely, if the measurement time is known, the specific measurement period and frequency can be found.

[0126] In FIG. 11, A is a calm state in which no significant situation occurs in the monitored space. The process by which the space situation determining means 300 determines the situation of the monitored space will be described with reference to FIG.

[0127] The data analysis unit 310 of the space situation determination means 300 can scan the difference values ​​in chronological order to analyze the degree and pattern of fluctuation of the difference values ​​720. In the case of Fig. 12, the data analysis unit 310 of the space situation determination means 300 can scan the difference values ​​in chronological order to determine whether the difference values ​​are within a first reference range S1 in a certain time period P1.

[0128] As described above, due to the inherent physical characteristics of the monitored space, the difference value fluctuates below a certain level when the monitored space is in a calm state. Therefore, the degree of fluctuation of the difference value when the monitored space is in a calm state can be grasped and the first reference range S1 can be set. The first reference range S1 can be set differently depending on the situation of the monitored space.

[0129] In the case of Figure 12, the data analysis unit 310 of the spatial situation judgment means 300 can determine that each difference value 721 in the first time interval P1 is within the first reference range S1, and that the monitored space is in a peaceful state during such first time interval P1.

[0130] Here, the first time interval P1 can be selected as a time interval long enough to determine that the monitored space is in a calm state. For example, it is difficult to simply determine that the monitored space is in a calm state just because there are no significant fluctuations in the differential values ​​measured within the monitored space for one consecutive second. This is because, for example, if an intruder moves within the monitored space and then remains stationary for several seconds, the differential values ​​may be within the reference range for several seconds even though the monitored space is not in a calm state. On the other hand, if there are no significant fluctuations in the measured differential values ​​for five minutes or more, the monitored space can be determined to be in a calm state without movement. In this way, boundary conditions for determining that the monitored space is in a calm state can be appropriately set according to the characteristics of the monitored space. In this case, the boundary conditions must satisfy two criteria: (1) for a certain period of time, and (2) the amount of change in the differential values ​​must be maintained below a certain level.

[0131] The first time interval P1 may be a relatively long time, for example, 10 seconds or more. For example, if one spectrum measurement period is 6 seconds, the first time interval P1 may be a long time corresponding to multiple measurement periods. Such a first time interval P1 may be appropriately set depending on the conditions of the monitored space.

[0132] For example, the data analysis unit 310 of the space situation determination means 300 may calculate the degree of scattering of the difference values ​​in the first time interval P1, and analyze the degree and pattern of fluctuation of the difference values ​​based on the degree of scattering.

[0133] Indices that are often used to express the degree of dispersion include, for example, standard deviation, variance, absolute deviation, range, and interquartile range. The present invention also includes the root mean square error (Root Mean Square Error) used in linear regression analysis as one of the indices that express the degree of dispersion. Using the Root Mean Square Error as an index of dispersion can improve the accuracy of detection, especially when a temperature change occurs in the monitored space.

[0134] The data analysis unit 310 of the space situation determination means 300 can calculate the dispersion of the difference values ​​721 in the first time period P1 and analyze whether the dispersion of the difference values ​​is maintained below a first criterion.

[0135] If the dispersion of difference values ​​calculated in a calm state where no significant events occur in the monitored space is D0, the first criterion can be, for example, 1.1 to 3 times D0.

[0136] The appropriate threshold value for the various criteria described below, including the first criterion, may vary greatly depending on the user and the intended use. For example, if one wants to reduce false positives for a certain sensor, the threshold should be increased. In this case, the probability of false negatives increases. Conversely, if one wants to reduce the probability of false negatives, the threshold should be decreased. In this case, the probability of false positives increases. However, for example, false positives may not be a major problem for certain intended uses, but false negatives may have fatal consequences. Conversely, false positives may be a very annoying problem for some users. Therefore, the specific threshold value that is appropriate depends on the characteristics of the monitored space and user, the intended use of the sensor, and the severity of false positives and false negatives.

[0137] 12, if the dispersion of the difference value of the first reference time P1 is less than the first reference, the event situation determination unit 330 of the space situation determination means 300 may determine that the monitored space is currently in a calm state. Here, how long P1 is set to or how large the first reference of dispersion is set to can be appropriately set depending on the purpose of use of the sensor and the situation of the space, as described above.

[0138] 11, B indicates a state where the first intrusion occurs while the monitored space is maintaining a calm state. Here, the process by which the space situation determination means 300 determines the situation of the monitored space will be described with reference to FIG.

[0139] In the process of scanning the difference values ​​in chronological order, the data analysis unit 310 of the spatial situation determination means 300 can determine that the difference value was not large in the first time interval P1, but that the difference value becomes large in the second time interval P2 following the first time interval. Here, the setting of the first time interval P1 has been described above. Meanwhile, the second time interval P2 must be set to a time interval suitable for determining whether an intrusion has first occurred, depending on the spatial situation and the detection purpose, and therefore, a time interval of, for example, 0.1 to 5 seconds can be selected.

[0140] 13, if the variance of the difference values ​​731 in the first time interval P1 is less than the first criterion, while the variance of the difference values ​​in the second time interval P2 exceeds the second criterion, the data analysis unit 310 of the space situation determination means 300 can determine that movement first occurred in the monitored space in the second time interval P2. Here, the second criterion can be set to a value equal to or greater than the first criterion.

[0141] Meanwhile, various indices or concepts can be used to set the criteria for determining whether an initial movement has occurred within the monitored space. However, even if such various criteria are applied, such a determination method can also be included as a type of determination method using dispersion. For example, in FIG. 13, if the absolute value of the difference value d is maintained within the S1 range and exceeds the S2 range at a specific time point while remaining within the S1 range, it can be determined that an initial movement has occurred at that time point. However, such a determination method can be considered a type of "method of determination based on dispersion." For example, if the "absolute value of the difference value d" is used as an index indicating dispersion and the width of the second time interval P2 is minimized, the two representations become completely identical.

[0142] Referring to Figure 13, it can be seen that the present invention differs from the prior art in two ways. First, in the prior art, the difference between the currently measured spectrum and a spectrum measured at another time is calculated on a spectrum-by-spectrum basis, so only the fact that an event occurred within the time interval in which the current spectrum was measured is known, but the type of event is not known. Second, in the prior art, only the point in time in which the event occurred is estimated to be a certain point within the time interval in which the current spectrum was measured, and the exact time at which the event occurred is not known. In contrast, in the present invention, it is known that the event first occurred in the second time interval P2, and further that the type of event is an intrusion.

[0143] In Figure 11, C is a difference value change pattern when it can be determined that there is movement in the monitored space, even though it cannot be said that movement has occurred for the first time. When movement occurs for the first time, as in the case of B in Figure 11, the second criterion can be set relatively low because there is a clear contrast between the calm state and the state in which movement first occurred. However, it is preferable that the third criterion, which is used to determine that an intrusion is currently being maintained, be greater than the second criterion. Of course, the third criterion can also be the same as the second criterion.

[0144] When the monitored space remains calm, the variance of the difference values ​​must be small, whereas when there is movement, the variance of the difference values ​​must be high. However, the appropriate level of variance at which to issue an alarm must be determined depending on the characteristics of the monitored space and the user, the purpose of use, and the severity of false detections and missed detections.

[0145] FIG. 14 shows the variation of the difference value over measurement time. As mentioned above, the measurement time can be replaced with the corresponding frequency. Referring to FIG. 14, the data analysis unit 310 of the space situation assessment unit 300 can identify a third time period P3 in which the difference value increases and decreases beyond the third reference range S3. The data analysis unit 310 of the space situation assessment unit 300 can analyze the degree and pattern of change in the difference value 740 over the third time period (or frequency period) P3.

[0146] As an example, the data analysis unit 310 of the space situation determination means 300 calculates the degree of dispersion for the difference value 741 in the third time (frequency) interval P3, and if the degree of dispersion of the difference value exceeds the third criterion, it can be determined that there is movement in the monitored space. Here, as mentioned above, the third criterion can be set to, for example, a value slightly larger than the second criterion.

[0147] The appropriate setting of the third time (frequency) interval P3 can be evaluated from two aspects.

[0148] First, to distinguish between motion in the monitored space and temperature changes, the third time (frequency) interval P3 must be narrower than the interval in which temperature changes can cause fluctuations in the difference value. That is, a narrow interval is set so that the difference value cannot fluctuate significantly even when there is a temperature change. If a fluctuation in the difference value is measured in this narrow interval, it can be determined that there is motion in the monitored space. However, when there is a temperature change, the width of the interval in which the difference value can fluctuate significantly is proportional to the width of the peak in the frequency response spectrum. Therefore, the third time (frequency) interval P3 must be narrower than the width of the peak in the frequency response spectrum, preferably less than 20% of the peak width.

[0149] Second, if the measurement time interval between the two spectra to be compared is sufficiently short, it can be reasonably assumed that the temperature change in the monitored space between the measurement times of the two spectra is not significant. In such a case, fluctuations in the difference value due to temperature changes can be ignored, and only fluctuations in the difference value due to movement can be considered. Therefore, if the measurement time interval between the two spectra to be compared is sufficiently short, the third time interval P3 can be set to the time required for an intruder to move to a certain extent, for example, approximately 0.1 to 5 seconds.

[0150] Meanwhile, various indices or concepts may be introduced to set criteria for determining the presence of movement. However, even if such various criteria are applied, such a determination method can also be included as a type of determination method using dispersion. For example, in the case of FIG. 14, the data analysis unit 310 of the space situation determination means 300 may determine that movement has occurred in the monitored space if the average absolute value of the difference value 741 exceeds the first average criterion AVE1 during the third time period P3 and the difference value 741 changes from a negative value to a positive value M1 and from a positive value to a negative value M2.

[0151] 11 to 14 show the difference values ​​according to the measurement time, but the measurement time can be changed to the frequency. That is, as described above, the frequency in each measurement period can be matched with the measurement time corresponding to the frequency in the measurement period, so that the measurement time can be changed to the frequency as needed to express the change in the difference value.

[0152] Next, the event determination when a temperature change occurs in the monitored space will be described with reference to FIG.

[0153] As described above with reference to FIG. 10, temperature changes due to the occurrence of a fire in a monitored space cause the differential value to change in a form similar to a sine curve over time, resulting in a fairly large overall change.

[0154] Figure 15 shows the case where the frequency response spectrum at the current time point after the fire has started and the frequency response spectrum before the fire has started are compared to calculate the difference value 750. Figure 15 shows the change in the difference value depending on the measurement time, but as mentioned above, each measurement time can be substituted for the frequency.

[0155] The data analysis unit 310 of the space situation assessment means 300 scans the differential values ​​to identify a fourth time (or frequency) interval P4 in which the overall differential values ​​change in a sine curve. Here, the fourth time (or frequency) interval P4 is preferably selected as an interval in which it is possible to confirm that the differential values ​​change in a form similar to a sine curve. For example, the entire time (frequency) interval forming one spectrum may be selected. Alternatively, an interval 1 to 5 times the peak width may be set at a frequency point where a peak exists in the frequency response spectrum.

[0156] As an example, the data analysis unit 310 of the space situation determination means 300 calculates the variance of the difference value 750 in the fourth time (frequency) interval P4 and analyzes whether the variance of the difference value in the fourth time (frequency) interval P4 exceeds a fourth criterion. Here, the fourth criterion must indicate that an event has occurred in the monitored space, and therefore may have a value similar to that of the third criterion, for example.

[0157] Furthermore, the data analysis unit 310 of the spatial situation judgment means 300 can calculate the degree of dispersion of the difference values ​​in a fifth time (frequency) interval P5 included in the fourth time (frequency) interval, and analyze whether the degree of dispersion of the difference values ​​in the fifth time (frequency) interval P5 is less than a fifth criterion.

[0158] Here, the fifth time (frequency) interval P5 is a time (frequency) interval suitable for observing that there is no sudden change in the difference value. For example, at a frequency point where a peak exists in the frequency response spectrum, the P5 interval must be smaller than the width of the peak, and preferably less than 20% of the peak width.

[0159] The fifth criterion is a criterion that must be used to determine whether the fluctuation range of the difference value is large compared to the case of intrusion, and therefore it would be preferable to set it at a level similar to or greater than the first criterion, for example.

[0160] On the other hand, when calculating the degree of dispersion by setting a fifth criterion, using the root mean square error as an index representing the degree of dispersion can improve the accuracy of temperature change determination. This is because, even if the "distance from the average of each difference value" is relatively large in the degree of dispersion in the fifth time (frequency) interval, if the "distance from the regression line of each difference value" is small, the change pattern of the difference value d is close to a sine curve, and therefore it can be determined that a temperature change has occurred. Therefore, for example, when measuring the degree of dispersion in other time intervals or frequency intervals, the standard deviation can be used, and when evaluating the degree of dispersion in the fifth time (frequency) interval, the root mean square error used in linear regression analysis can be used.

[0161] In this way, if the dispersion of the difference values ​​in the fourth time (frequency) interval P4 exceeds the fourth criterion and the dispersion of the difference values ​​in the fifth time (frequency) interval P5 is less than the fifth criterion, this means that the difference values ​​have a sign-shaped change pattern, and the data analysis unit 310 of the space situation judgment means 300 can determine that there is a temperature change in the monitored space.

[0162] Various indices or concepts may be introduced to set criteria for determining the presence of a temperature change. However, even if such various criteria are applied, such a determination method can also be included as a type of determination method using dispersion. For example, in the case of FIG. 15, the data analysis unit 310 of the spatial situation determination means 300 calculates the average and the average of the absolute values ​​of the difference values ​​751 in the fourth time (frequency) interval P4 and analyzes whether the average of the absolute values ​​of the difference values ​​exceeds the second average criterion AVE2 and is less than the third average criterion AVE3. Furthermore, it can identify M1, where the difference value 751 changes from a negative value to a positive value, and M2, where the difference value 751 changes from a positive value to a negative value, and analyze whether the frequency thereof is less than the second frequency criterion. If these conditions are met, the difference values ​​will generally resemble a sine curve, and the presence of a temperature change can be recognized.

[0163] Furthermore, the present invention can determine the status of a monitored space using a multidimensional data table for differential values. Figures 9 and 16 to 18 show an example of determining an event in a monitored space using a multidimensional data table for differential values ​​according to the present invention. Since the process of generating and saving multidimensional data tables such as those shown in Figures 16 to 18 in the present invention has been described above with reference to Figure 9, a detailed description thereof will be omitted.

[0164] In Figures 16 to 18(a), yellow indicates a case where the difference value d is close to 0, red indicates a large positive difference value, and blue indicates a large negative difference value. In Figure 9, it can be seen that there is no overall difference between the spectra measured in the current measurement cycle and the previous measurement cycle. In other words, this indicates a state in which a calm state is maintained with no movement or temperature changes in the monitored space.

[0165] The multidimensional data tables 810 and 820 shown in Figure 16 show that the difference values ​​have been fluctuating significantly and in a disordered manner for the past 60 seconds from the current time point. If the spatial situation determination means 300 applies the event determination process according to the previous embodiment, it can be determined that there is a change in the physical shape of the monitored space. More specifically, it can be determined that there is continuous movement of an object. This may be the case when a person is constantly moving in the monitored space.

[0166] The multidimensional data tables 830 and 840 shown in Figure 17 show a pattern 835 in which the difference values ​​change slightly to a certain level in the section before the 4036 Hz frequency, then begin to fluctuate significantly at the 4036 Hz frequency, and the difference values ​​change significantly up to 4076 Hz. By applying the event determination process of the spatial situation determination means 300 according to the previous embodiment, it can be determined that there is a change in the physical shape of the monitored space. More specifically, it can be determined that a calm state is maintained in the section before the 4036 Hz frequency, and then that the first movement of an object has occurred in the monitored space measured around the 4036 Hz frequency. This may be the case if an intruder has entered the monitored space.

[0167] 18, the multidimensional data tables 850 and 860 show a shape 870 in which the difference values ​​calculated by comparing the current measurement period with the measurement period 60 seconds ago generally resemble a sine curve. Furthermore, when the difference values ​​calculated by comparing measurement periods from 60 seconds ago to the current measurement period that are gradually closer to the present are examined, the difference values ​​appear as patterns 851, 852, 853, 861, 862, and 863, in which the change in the difference values ​​gradually decreases. By determining the degree and pattern of change in the difference values ​​using the event determination process performed by the space situation determination means 300 according to the previous embodiment, it can be determined that there is a temperature change in the monitored space. More specifically, it can be determined that a fire broke out 60 seconds ago and is currently progressing actively.

[0168] Conventional techniques only focus on how much the currently measured spectrum differs from the previously measured spectrum, so while the fact that the two spectra are different indicates that some change occurred between the times the two spectra were measured, it is not possible to determine what specific event occurred.

[0169] However, the present invention goes beyond simply measuring how much the currently measured spectrum differs from a previously measured spectrum and instead closely observes how they differ. As a result, the time when the first intrusion into the monitored space occurred can be accurately determined (e.g., P2 in FIG. 13). Furthermore, for example, if the dispersion of the difference values ​​is high in a relatively narrow time (frequency) interval (e.g., P3 in FIG. 14), it can be determined that movement has occurred. Conversely, if the dispersion of the difference values ​​is low in a relatively narrow time (frequency) interval (e.g., P5 in FIG. 15), it can be determined that a temperature change has occurred.

[0170] According to the present invention, the frequency response spectrum for each measurement period of the monitored space is compared for each individual frequency or frequency section, and the degree and pattern of change in the difference values ​​are analyzed. This allows for faster and more accurate detection of changes in the physical conditions of the monitored space. Furthermore, the present invention provides the change pattern of the difference values ​​in a visual data table so that even non-experts can intuitively and easily grasp it.

[0171] The above description merely exemplifies the technical concept of the present invention. Those skilled in the art will appreciate that various modifications and variations may be made without departing from the essential characteristics of the present invention. Therefore, the embodiments described herein are for illustrative purposes only and are not intended to limit the technical concept of the present invention. The scope of the present invention should be interpreted in accordance with the following claims, and all technical concepts within the scope equivalent thereto should be construed as being within the scope of the present invention.

Claims

1. a frequency response measuring step of emitting an acoustic signal to a monitored space for each measurement period, receiving the acoustic signal, and acquiring a frequency response spectrum for each measurement period; a difference value calculation step of comparing the frequency response spectrum of a specific period with a comparison target frequency response spectrum in individual frequency units or in frequency interval units, and calculating a difference value for each individual frequency unit or each frequency interval unit; a difference value storing step of storing the difference value in a database by matching the difference value with at least one of the frequency and the measurement time; A space situation determination step of determining the situation of the monitored space based on the degree or pattern of fluctuation of the difference value depending on the frequency or measurement time.

2. The difference value calculation step compares the frequency response spectrum of a specific period with the frequency response spectrum of at least one other measurement period; 2. The method for monitoring a space using an acoustic signal according to claim 1, wherein the step of storing the difference value stores the difference value by matching it with the frequency or the measurement time, the measurement time interval of the frequency response spectrum of a specific period, and the measurement time interval of the frequency response spectrum of another measurement period.

3. The frequency response measuring step includes emitting a single sound acoustic signal into the monitored space, the frequency of which changes continuously or stepwise over time; 2. The method of claim 1, wherein the determining step determines that there is a change in physical shape of the monitored space in a second frequency interval or a second time interval when a degree of scattering of difference values ​​is maintained below a first criterion in a first frequency interval or a first time interval and then exceeds a second criterion in a second frequency interval or a second time interval.

4. 2. The method of claim 1, wherein the space situation determination step determines that there is a change in physical shape of the monitored space in a third frequency interval or a third time interval if a variance of the difference values ​​in the third frequency interval or the third time interval exceeds a third criterion.

5. 2. The method of claim 1, wherein the space situation determination step determines that there is a temperature change in the monitored space in the fourth frequency interval or the fourth time interval if a degree of dispersion of the difference values ​​in a fourth frequency interval or a fourth time interval exceeds a fourth criterion and if a degree of dispersion of the difference values ​​in a fifth frequency interval or a fifth time interval included in the fourth frequency interval or the fourth time interval is less than a fifth criterion.

6. a frequency response measuring means for emitting an acoustic signal into a monitored space at each measurement period, receiving the acoustic signal, measuring a frequency response spectrum at each measurement period, comparing the frequency response spectrum at a specific period with a comparison frequency response spectrum at each individual frequency or each frequency interval, and calculating a difference value at each individual frequency or each frequency interval; a database construction means for matching the difference value with at least one of the frequency and the measurement time and storing the matched difference value in a database; A space monitoring system using acoustic signals, characterized by including a space situation determination means for determining the situation of the monitored space based on the degree or pattern of variation in the difference value due to frequency or measurement time.

7. the frequency response measurement means compares the frequency response spectrum of a particular period with the frequency response spectrum of at least one other measurement period; 7. The space monitoring system using acoustic signals according to claim 6, wherein the database construction means stores the difference value by matching it with the frequency or the measurement time, the measurement time interval of the frequency response spectrum of a specific period, and the measurement time interval of the frequency response spectrum of another measurement period.

8. The frequency response measuring means emits a single sound acoustic signal into the monitored space, the frequency of which changes continuously or stepwise over time; 7. The space monitoring system using acoustic signals according to claim 6, wherein the space situation determination means determines that there is a change in the physical shape of the monitored space in the second frequency interval or the second time interval when the degree of dispersion of the difference values ​​between the first frequency interval or the first time interval is maintained below a first criterion and then the degree of dispersion of the difference values ​​in the second frequency interval or the second time interval exceeds a second criterion.

9. 7. The space monitoring system using acoustic signals according to claim 6, wherein the space situation determination means determines that there is a change in the physical shape of the monitored space in the third frequency interval or the third time interval if the dispersion of the difference values ​​in the third frequency interval or the third time interval exceeds a third criterion.

10. 7. The space monitoring system using acoustic signals according to claim 6, wherein the space situation determination means determines that there is a temperature change in the monitored space in the fourth frequency interval or the fourth time interval if the degree of dispersion of the difference values ​​in the fourth frequency interval or the fourth time interval exceeds a fourth criterion and if the degree of dispersion of the difference values ​​in the fifth frequency interval or the fifth time interval included in the fourth frequency interval or the fourth time interval is less than a fifth criterion.

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