CN118330133A - Smoke detection method, device, program product and storage medium - Google Patents
Smoke detection method, device, program product and storage medium Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 101
- 239000000779 smoke Substances 0.000 title claims abstract description 60
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 claims abstract description 120
- 229910002092 carbon dioxide Inorganic materials 0.000 claims abstract description 60
- 239000003571 electronic cigarette Substances 0.000 claims abstract description 33
- 235000019504 cigarettes Nutrition 0.000 claims abstract description 30
- 230000006399 behavior Effects 0.000 claims abstract description 29
- 239000002245 particle Substances 0.000 claims abstract description 26
- 230000000391 smoking effect Effects 0.000 claims abstract description 19
- 238000000034 method Methods 0.000 claims abstract description 16
- 230000000873 masking effect Effects 0.000 claims abstract description 9
- 239000012855 volatile organic compound Substances 0.000 claims abstract description 8
- 239000001569 carbon dioxide Substances 0.000 claims abstract description 4
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
- Y02A50/20—Air quality improvement or preservation, e.g. vehicle emission control or emission reduction by using catalytic converters
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Abstract
The application provides a smoke detection method, a smoke detection device, a program product and a storage medium. The method comprises the following steps: judging whether the concentration of particulate matters in the current air exceeds a preset standard or not; if the concentration of the particulate matter exceeds the preset standard, judging whether the concentration of carbon dioxide CO2 and the concentration of the volatile organic compound TVOC are mutated or not; if only the CO2 concentration is suddenly changed, triggering a cigarette alarm; if the CO2 concentration and the TVOC concentration are not suddenly changed, triggering an electronic cigarette alarm; and if only the TVOC concentration is mutated, judging that the smoking covers the behavior. The application provides a multi-sensing integrated detection system, which combines the concentration of air particles, the concentration of TVOC and the concentration of CO2 to carry out combination logic judgment, effectively solves the complex conditions of false alarm, artificial masking and the like while accurately distinguishing electronic cigarettes from cigarettes, and realizes high-accuracy smoke detection.
Description
Technical Field
The present application relates to the field of security monitoring technologies, and in particular, to a smoke detection method, a device, a program product, and a storage medium.
Background
Smoking has great damage to human health, and secondhand smoking also constitutes a potential threat to the health of others. With the increasing concern of society about public health problems, smoking has become a social problem to be solved.
On the one hand, conventional smoke detectors have significant limitations in detecting electronic cigarettes and cigarettes. Because the smoke discharged by the electronic cigarette and the cigarette has differences in composition and concentration with the common smoke, the traditional smoke detector cannot accurately detect the discharge of the electronic cigarette equipment and give an alarm, and the detection effect is poor.
On the other hand, currently marketed e-smoke detectors rely primarily on a single sensor to detect smoke concentration in the air. The single detection mode can not effectively distinguish the electronic cigarette from the traditional cigarette, and is easily interfered by substances such as aerosol, cleaning products, steam and the like, so that false alarm or covering phenomenon is caused.
In recent years, camera monitoring technology has been applied to smoking behavior detection. Firstly, when the human body is in a blind area (such as shielded and opposite to a camera), the technology cannot accurately analyze smoking behavior, and the detection rate and the detection accuracy are not high. Second, this technique may involve infringement of the privacy of citizens, and may not adequately secure personal privacy.
Therefore, there are many shortages in the current market for the detection technology of electronic cigarettes and cigarette smoking, and a technical scheme is needed to meet the requirements of accurately and efficiently detecting electronic cigarettes and cigarettes.
Disclosure of Invention
Aiming at the defects in the prior art, the application provides a smoke detection method, a device, a program product and a storage medium, which aim to solve the problems of low detection precision, single detection mode and the like of the traditional smoke detector, and realize high-efficiency and accurate detection of electronic cigarettes and ensure privacy safety through a multi-sensor fusion technology and event detection logic.
In a first aspect, the present application provides a smoke detection method, the method comprising:
S1, judging whether the concentration of particulate matters in the current air exceeds a preset standard or not;
s2, judging whether the concentration of carbon dioxide CO2 and the concentration of the volatile organic compound TVOC are mutated or not if the concentration of the particulate matters exceeds the preset standard;
S3, triggering a cigarette alarm if only the concentration of the CO2 is suddenly changed; if the CO2 concentration and the TVOC concentration are not suddenly changed, triggering an electronic cigarette alarm; if only the TVOC concentration is mutated, it is determined that the smoking masking behavior is performed.
In one possible embodiment, the method step S3 includes:
S31, triggering a cigarette alarm if only the concentration of the CO2 is suddenly changed;
S32, triggering an electronic cigarette alarm if the CO2 concentration and the TVOC concentration are not suddenly changed;
And S33, judging that the smoking covers the behavior if only the TVOC concentration is suddenly changed.
In one possible embodiment, before the step S1, the method further includes: in response to detecting the human presence signal, each sensor is awakened to begin acquisition.
In one possible embodiment, the human presence signal refers to: human infrared signals and/or voice signals.
In one possible embodiment, the method further comprises:
And triggering an event alarm corresponding to the preset keyword under the condition that the preset keyword is identified from the collected voice signal.
In one possible embodiment, the method further comprises:
if the concentration of the particulate matters does not exceed the preset standard and the concentration of CO2 in the air is suddenly changed, judging that the personnel is increased;
And if the concentration of the particulate matters does not exceed the preset standard and the concentration of TVOC in the air is suddenly changed, judging that the condition of non-smoking interference is caused.
In one possible embodiment, the method further comprises:
And judging whether the behavior of the interference equipment exists according to the real-time angular velocity information, and triggering a forced disassembly alarm when the behavior of the interference equipment is detected.
In a second aspect, there is provided a smoke detection apparatus configured to perform:
Acquiring the concentration of the particles acquired by a particle sensor, and judging whether the concentration of the particles exceeds a preset standard;
If the concentration of the particulate matters exceeds the preset standard, judging whether the concentration of CO2 collected by the CO2 sensor and the concentration of TVOC collected by the TVOC sensor are suddenly changed;
If only the CO2 concentration is suddenly changed, triggering a cigarette alarm; if the CO2 concentration and the TVOC concentration are not suddenly changed, triggering an electronic cigarette alarm; if only the TVOC concentration is mutated, it is determined that the smoking masking behavior is performed.
In one possible implementation, the apparatus is further configured to perform at least one of:
judging whether personnel exist or not based on human existence signals acquired by the PIR sensor and/or the voice detection module;
identifying the voice signals collected by the voice detection module, and triggering corresponding event alarms;
And judging whether the behavior of the interference equipment exists or not based on real-time angular velocity information acquired by the angular velocity sensor, and triggering a forced disassembly alarm when the behavior of the interference equipment is detected.
In a third aspect, there is provided a computer program product comprising computer programs/instructions which when executed by a processor implement the smoke detection method provided in the first aspect.
In a fourth aspect, there is provided a computer-readable storage medium having stored therein at least one program that is executed by a processor to implement the smoke detection method as provided in the first aspect.
The technical scheme provided by the application at least comprises the following technical effects:
(1) The multi-sensor integrated detection system is provided, the combination analysis is carried out based on the professional sensor and the algorithm logic, the event type is judged according to different combination indexes, and the detection with high accuracy can be realized. The particle concentration and distribution condition in the air are detected by using the particle (Particulate Matter, PM) sensor, and the electronic cigarette and the cigarette can be distinguished by matching with the TVOC sensor and the CO2 sensor, so that the false alarm and covering conditions of combustion, spraying and natural volatilization are solved.
(2) By combining the passive infrared (PASSIVE INFRARED, PIR) technology and voice detection assistance, the PIR sensor is used for recognizing the existence of a person and then waking up the calculation module, and the working state of the calculation module is controlled in a triggering manner so as to save the power consumption rate, thereby improving the endurance of the smoke detector and the confidence of judging the electronic cigarette. In addition, the keyword detection is realized by adopting a voice detection module (such as Mic), and adverse events such as fighting, spoofing and the like can be effectively prevented.
(3) Compared with a camera detection scheme, the application adopts the sensor to collect air data 360 degrees without dead angles, and the problem of detection dead areas is avoided; in addition, the camera is independent of visible light images, so that the privacy of citizens is effectively guaranteed, the camera can be applied to places such as toilets and dressing rooms, and the limitation of the traditional camera detection scheme is broken through.
The application provides a multi-sensor integrated detection system, which combines the combination of a plurality of sensor acquisition indexes to judge event types, carries out combination logic judgment based on air particulate matter concentration, TVOC concentration and CO2 concentration, and effectively solves the complex conditions of false alarm, artificial masking and the like while accurately distinguishing electronic cigarettes from cigarettes, thereby realizing high-accuracy smoke detection.
Drawings
Fig. 1 is a schematic diagram of a smoke detection device according to an embodiment of the present application;
FIG. 2 is a schematic illustration of a mutation in particulate matter concentration according to an embodiment of the present application;
FIG. 3 is a graph of CO2 absorption versus wavelength provided by an embodiment of the present application;
FIG. 4 is a schematic diagram of a TVOC sensor provided by an embodiment of the application;
Fig. 5 is a schematic view of another smoke detection device according to an embodiment of the present application;
fig. 6 is a flowchart of a smoke detection method according to an embodiment of the present application;
FIG. 7 is a schematic diagram of the operation of a PM2.5 sensor provided by an embodiment of the application;
Fig. 8 is a graph of a change in a value of a TVOC sensor according to an embodiment of the present application;
Fig. 9 is a flowchart of another smoke detection method according to an embodiment of the present application.
Detailed Description
For further illustration of the various embodiments, the application is provided with the accompanying drawings. The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate embodiments and together with the description, serve to explain the principles of the embodiments. With reference to these matters, one of ordinary skill in the art will understand other possible embodiments and advantages of the present application. The components in the figures are not drawn to scale and like reference numerals are generally used to designate like components. The term "at least one" in the present application means one or more, and the term "plurality" in the present application means two or more.
The application provides a smoke detection method, a device and a program product, and the technical scheme of the application is described below by means of a plurality of examples combined with the accompanying drawings and specific implementation modes.
The embodiment of the application provides a smoke detection device which is integrated with various sensors and can accurately distinguish the smoke conditions of electronic cigarettes and cigarettes.
In an embodiment of the present application, a smoke detection apparatus includes: a computing module and a plurality of sensors, the plurality of sensors comprising at least: particulate matter sensors (PM sensors), CO2 sensors, and volatile organic compound (Total Volatile Organic Compounds, TVOC) sensors. Fig. 1 is a schematic diagram of a smoke detection device according to an embodiment of the present application, where the device at least includes a computing module, a particulate matter sensor, a CO2 sensor, and a TVOC sensor.
The calculation module is used as a calculation and control center of the smoke detection device. The computing module is, for example, a microcontroller (Microcontroller Unit, MCU), a central processing unit (Central Processing Unit, CPU), but may also be other general purpose Processor, digital signal Processor (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), off-the-shelf Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the computing module may be any conventional processor. The computing module may utilize various interfaces and lines to connect various portions of the overall device (e.g., sensors, wireless communication modules, etc.).
The PM sensor is used to analyze the concentration of dust particles of different sizes, such as PM1.0, PM2.5, and PM10, in air. Considering that aerosol particles of electronic cigarettes and cigarettes are generally small particles, actual judgment is based on PM1.0 and PM 2.5. Fig. 2 is a schematic diagram of abrupt change of concentration of particulate matters according to an embodiment of the present application, where each coordinate point in fig. 2 corresponds to a concentration value on an ordinate and corresponds to a time on an abscissa. The left graph in fig. 2 is an electronic particulate matter concentration variation graph, the right graph is a particulate matter concentration variation graph of a cigarette, and detected particulate matter includes: PM1.0, PM2.5, and PM10.
In one possible embodiment, a PM2.5 laser dust sensor is selected that supports detection of suspended particulate matter counts in the range of 0.3 to 10 microns. The particulate matter sensor can be used for detecting smoke components of electronic cigarettes and cigarettes, and PM values can be suddenly changed due to the fact that a large amount of solid particulate matters and liquid particulate matters are generated when the electronic cigarettes and the cigarettes are used. Therefore, whether the smoke is drawn or not can be judged according to whether the concentration of the particulate matters exceeds the standard.
Wherein, the CO2 sensor is used for detecting the content (concentration) of CO2 in the detected gas. Illustratively, the CO2 Sensor is a Non-dispersive infrared gas analyzer (Non-DISPERSIVE INFRARED GAS Sensor, NDIR). Each gas in nature absorbs light, and CO2 gas is particularly sensitive to infrared with a wavelength of 4.26um, as shown in fig. 3, and fig. 3 is a graph of CO2 absorption versus wavelength provided by an embodiment of the present application. NDIR is the attenuation of the radiant energy transmitted through a measuring chamber based on the absorption of infrared radiation by CO2 in a specific wavelength band, the degree of attenuation being dependent on the CO2 content of the gas being measured.
The TVOC sensor module is a metal oxide semiconductor sensor based on a gas absorption phenomenon (redox reaction) that causes a change in the sheet resistance of the sensor, as shown in fig. 4, and fig. 4 is a schematic diagram of a TVOC sensor according to an embodiment of the present application. When the measured gas concentration in the environment where the TVOC sensor is located is higher, the conductivity of the sensor will change accordingly.
In one possible embodiment, the smoke detection device further comprises: PIR sensor and voice detection module for detecting whether someone exists. Two significant features of human body can be detected through PIR and the voice detection module, so that the confidence level is improved for detecting smoking behaviors. The human existence characteristics are: the human body temperature is constant (about 37 °); the person produces sound to produce sound waves.
Wherein, the human body emits infrared rays with the wavelength ranging from 3 μm to 15 μm at a constant body temperature (about 37 ℃). When infrared rays released by a human body are gathered to the PIR element, the element loses charge balance when receiving the change of infrared radiation of the human body, charges are released outwards, and signals can be generated after detection.
The voice detection module is, for example, a Micro-Electro-MECHANICAL SYSTEM Microphone (MEMS), which uses a small electret Microphone to collect sound waves from the detection range. An electret microphone is a capacitor with an electret film that converts weak acoustic vibrations into a micro-pulsating electrical signal.
In other possible embodiments, the smoke detection device further comprises an angular velocity sensor, which may be used to measure a stress sensor of an object rotating in space about an axis, supporting the conversion of the angular velocity of the object into a corresponding electrical signal output, typically an analog or digital signal. The angular velocity sensor is mainly used to measure the angular velocity of the rotation of an object, as well as the angle of rotation relative to a set of fixed reference frames or the angular change per unit time. The shaftly and precessiveness can be used for effectively preventing the behavior of personnel attempting to disassemble or tamper with the equipment.
In other possible embodiments, the smoke detection device further comprises: the system comprises an LED alarm module, a wireless communication module and a power supply module. Illustratively, the LED alert module includes an LED drive and an LED light, for example, RGB ALERTING LED supporting the three colors red, green and blue. The wireless communication module is, for example, a LoRa module or an NFC chip. The power supply module is, for example, a conventional DC power supply mode, and may also be power over ethernet (Power over Ethernet, poE). Of course, various possible embodiments of the LED alert module, the wireless communication module, and the power supply module may be freely combined, which is not limited in the present application.
Fig. 5 is a schematic diagram of another smoke detection device according to an embodiment of the present application, as shown in fig. 5, the smoke detection device includes: MCU as control and computation center, PM2.5 sensor, TVOC sensor, CO2 sensor, LED drive and RGB ALERTING LED, angular velocity sensor for tamper resistance, PTR for human presence detection, voice detection module (MEMS Mic) and its audio digital to analog converter (A to D), wireless communication module (Lora/NFC), power supply module (PoE/DC).
The following describes the smoke detection method provided by the embodiment of the application in combination with the description of each functional module of the smoke detection device, and the smoke detection method can be executed by the calculation module. Fig. 6 is a flowchart of a smoke detection method according to an embodiment of the present application, as shown in fig. 6, the method at least includes the following steps S1 to S3.
S1, judging whether the concentration of particulate matters in the current air exceeds a preset standard.
The predetermined criterion is, for example, a particle concentration value A. Mu.g/m 3 as a judgment criterion.
In one possible embodiment, as shown in fig. 7, when laser light irradiates on suspended particles in air to generate scattering, the PM sensor can collect the scattered light, and the equivalent particle size of the generated scattered particles can be deduced using the amplitude and angle data of the scattered radiation. After the calculation Module (MCU) obtains the amplitude and angle data, the relation between the time domain and the frequency domain is obtained through Fourier transformation, so that the number of the particles with different particle diameters in the unit volume of the particles can be obtained, namely, the concentration of the particles is obtained. Fig. 7 is a schematic diagram of the operation of a PM2.5 sensor according to an embodiment of the present application.
In one possible implementation, before step S1, the computing module is in a sleep state, and in response to detecting a human presence signal, wakes up the respective sensor to start acquisition. Illustratively, if the PIR sensor detects a human infrared signal, the calculation module is triggered, and after the calculation module starts to operate, the CO2 sensor, the PM2.5 sensor, the voice detection module and the like are awakened to start to collect.
In one possible embodiment, the human presence signal refers to: human infrared signals and/or voice signals. Specifically, the PIR and voice detection module can detect the obvious characteristics of human existence, namely the human body temperature and the generated sound wave, so that the confidence level is improved for detecting the smoking behavior.
In one possible embodiment, a PM2.5 laser dust sensor is selected that supports detection of suspended particulate matter counts in the range of 0.3 to 10 microns. The PM2.5 sensor can be used for detecting smoke components of electronic cigarettes and cigarettes, and PM values can be suddenly changed due to the fact that a large amount of solid particles and liquid particles are generated when the electronic cigarettes and cigarettes are used. Therefore, whether the smoke is drawn or not can be judged according to whether the concentration of the particulate matters exceeds the standard.
The PIR sensor is used for recognizing the existence of a person and then waking up the calculation module, and the working state of the calculation module is controlled in a triggering mode to save the power consumption rate, so that the endurance of the smoke detector is improved, and the confidence of judging the electronic cigarette is improved.
S2, judging whether the concentration of carbon dioxide CO2 and the concentration of the volatile organic compound TVOC are mutated or not if the concentration of the particulate matters exceeds a preset standard.
In the embodiment of the application, the concentration of CO2 detected by the CO2 sensor can be used for distinguishing cigarettes from electronic cigarettes. The electronic cigarette and the cigarette have combustion difference, the main components generated by heating the tobacco tar of the electronic cigarette are aerosol and liquid particles, and a great amount of solid particles and CO2 are generated by igniting the cigarette, so that the measured value of the CO2 sensor is suddenly changed and continuously increased.
In the embodiment of the application, the measured value of the TVOC sensor is used for avoiding the detection of false alarm and covering (interference) behaviors. The TVOC concentration may vary with the increase in activity within the detection range, for example, volatile organic compounds may be released using perfumes, hair sprays, cleaning products, etc., resulting in an increase in TVOC concentration; the overall trend is rapidly and linearly rising, and slowly falls back after reaching the saturation state, as shown in fig. 8, and a numerical variation diagram of a TVOC sensor provided in the embodiment of the present application in fig. 8 is shown.
S3, triggering a cigarette alarm if only the concentration of CO2 is suddenly changed; if the CO2 concentration and the TVOC concentration are not suddenly changed, triggering an electronic cigarette alarm; if only the TVOC concentration is mutated, it is determined that the smoking masking behavior is occurring.
In one possible implementation, the present step S3 includes S31 to S33.
S31, if only the concentration of CO2 is suddenly changed, triggering a cigarette alarm.
Specifically, the decision logic for a cigarette alarm may be expressed as: "PM1.0 is greater than or equal to A mug/m 3, PM2.5 is greater than PM1.0; mutation of CO2 concentration value; the TVOC concentration value was stable.
S32, triggering an electronic cigarette alarm if the CO2 concentration and the TVOC concentration are not suddenly changed.
Specifically, the judgment logic of the electronic cigarette alarm can be expressed as follows: "PM1.0 is greater than or equal to A mug/m 3, PM2.5 is greater than PM1.0; the concentration value of CO2 is stable; the TVOC concentration value was stable.
And S33, judging that the smoking covers the behavior if only the TVOC concentration is suddenly changed.
Specifically, the decision logic for smoke masking behavior can be expressed as: "PM particulate matter does not exceed a detection threshold; the concentration value of CO2 is stable; TVOC concentration value mutation).
In some embodiments, if the concentration of the particulate matter collected in step S1 does not exceed the preset standard and the concentration of CO2 collected in step S2 is mutated, then an increase in personnel is determined.
In some embodiments, if the concentration of the particulate matter collected in step S1 does not exceed the preset standard and the TVOC concentration collected in step S2 is mutated, it is determined that the smoke is not disturbed. Non-smoking interference conditions are, for example, sprays, natural volatile perfumes, etc.
The application realizes a multi-sensor integrated detection system, which is based on the combination analysis of professional sensors and algorithm logic, judges event types according to different combination indexes, and can realize the detection with high accuracy. The PM sensor is used for detecting the concentration and distribution of particulate matters in the air, and the TVOC sensor and the CO2 sensor are matched, so that the electronic cigarette and the cigarette can be distinguished, and meanwhile, the false alarm and covering conditions of combustion, spraying and natural volatilization are solved.
In other embodiments, the computing module determines whether there is an interfering device behavior according to the real-time angular velocity information during operation, and triggers a forced disassembly alarm when the interfering device behavior is detected.
In other embodiments, the voice detection module may assist the PIR in determining whether a person is present. Further, the voice detection module performs keyword detection at the same time to judge the occurrence of a specific event.
Specifically, the computing module triggers an event alarm corresponding to a preset keyword under the condition that the preset keyword is identified from the voice signal collected by the voice detection module.
The voice detection module firstly collects indoor sound waves and performs analog-to-digital conversion to output an electric signal, and the calculation module uses Fourier transform to the electric signal to obtain a frequency spectrum of the electric signal and identifies whether the frequency spectrum accords with a human voice frequency spectrum; further, a frequency band corresponding to a predetermined keyword spectrum is detected from the continuous spectrum. Keywords are, for example, specific phrases (e.g., life saving, help, etc.), events corresponding to duress, campus violence, fighting behavior, etc.
The application adopts the voice detection module (such as Mic) to realize keyword detection, and can effectively prevent bad events such as fighting, spoofing and the like.
In order to facilitate understanding of the logic association between the above various possible embodiments, the embodiment of the present application provides a flowchart of another smoke detection method, referring to fig. 9, when the pir detects a human infrared signal, the interrupt signal wakes the MCU through the pin, and various sensors start real-time response and continuous acquisition. The particle detection threshold (preset standard) is set to be A mug/m 3, and when the concentration of the particles collected and calculated by the PM2.5 sensor meets detection logic, PM1.0 is more than or equal to A mug/m 3, PM2.5 is more than PM1.0, the smoking behavior can be primarily judged. The CO2 sensor and the TVOC detect air quality change simultaneously, the comprehensive PM2.5 sensor detection value realizes reporting the alarm, and the alarm type includes:
1) The alarm of the electronic cigarette is that PM1.0 is more than or equal to A mug/m 3, and PM2.5 is more than PM1.0; the concentration value of CO2 is stable; TVOC concentration value stable ";
2) Cigarette alarm- "PM1.0 is more than or equal to A mug/m 3, PM2.5 is more than PM1.0; mutation of CO2 concentration value; TVOC concentration value stable ";
3) The volatile organic compound covers the behavior alarm- "PM1.0 is more than or equal to A mug/m 3, PM2.5 is more than PM1.0; mutation of CO2 concentration value; TVOC concentration value mutation ";
4) Interference behavior does not alert — PM particulate matter does not exceed a detection threshold; the concentration value of CO2 is stable; TVOC concentration value mutation).
The voice detection assists PIR to judge whether personnel exist or not, and meanwhile, independent detection can be carried out, and specific phrases (such as life saving, help and the like) can be intercepted to trigger stress (campus violence, fighting actions) alarm.
Compared with a camera detection scheme, the application adopts the sensor to collect air data 360 degrees without dead angles, and the problem of detection dead areas is avoided; in addition, the camera is independent of visible light images, so that the privacy of citizens is effectively guaranteed, the camera can be applied to places such as toilets and dressing rooms, and the limitation of the traditional camera detection scheme is broken through.
In summary, the application provides a multi-sensor integrated detection system, which combines the combination of a plurality of sensor acquisition indexes to judge event types, carries out combination logic judgment based on air particulate matter concentration, TVOC concentration and CO2 concentration, and effectively solves the complex conditions of false alarm, artificial masking and the like while accurately distinguishing electronic cigarettes from cigarettes, thereby realizing high-accuracy smoke detection.
In an embodiment of the present application, the computing module may include, but is not limited to, a processor and a memory. It will be appreciated by those skilled in the art that the constituent structures of the computing modules described above are merely examples of computing modules and are not limiting of computing modules, and may include more or fewer components than those described above, or may combine certain components, or different components. For example, the computing module may further include an input/output device, a network access device, a bus, etc., which is not limited by the embodiment of the present application.
Further, as an implementation, the Processor may be a Central processing unit (Central ProcessingUnit, CPU), other general purpose Processor, digital signal Processor (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), off-the-shelf Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like that is a control center of the computing module, with various interfaces and lines connecting various portions of the overall computing module.
The memory may be used to store the computer program and/or modules, and the processor may implement various functions of the computing module by running or executing the computer program and/or modules stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for a function; the storage data area may store data created according to the use of the cellular phone, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart memory card (SMART MEDIA CARD, SMC), secure Digital (SD) card, flash memory card (FLASH CARD), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
The present application also provides a computer readable storage medium storing a computer program which when executed by a processor implements all or part of the steps of the above-described smoke detection method according to an embodiment of the present application.
The present application also provides a computer program product comprising computer programs/instructions which when executed by a processor implement all or part of the steps of the above-described smoke detection method according to the embodiments of the present application.
The modules/units of the computing module integration, if implemented as software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a software distribution medium, and so forth. It should be noted that the content of the computer readable medium can be appropriately increased or decreased according to the requirements of the legislation and the patent practice in the jurisdiction.
While the application has been particularly shown and described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the application as defined by the appended claims.
Claims (10)
1. A smoke detection method, the method comprising:
S1, judging whether the concentration of particulate matters in the current air exceeds a preset standard or not;
s2, judging whether the concentration of carbon dioxide CO2 and the concentration of the volatile organic compound TVOC are mutated or not if the concentration of the particulate matters exceeds the preset standard;
S3, triggering a cigarette alarm if only the concentration of the CO2 is suddenly changed; if the CO2 concentration and the TVOC concentration are not suddenly changed, triggering an electronic cigarette alarm; if only the TVOC concentration is mutated, it is determined that the smoking masking behavior is performed.
2. The smoke detection method as defined in claim 1, wherein prior to step S1, said method further comprises: in response to detecting the human presence signal, each sensor is awakened to begin acquisition.
3. The smoke detection method of claim 2, wherein said human presence signal is: human infrared signals and/or voice signals.
4. The smoke detection method of claim 1, wherein said method further comprises:
And triggering an event alarm corresponding to the preset keyword under the condition that the preset keyword is identified from the collected voice signal.
5. The smoke detection method of claim 1, wherein said method further comprises:
if the concentration of the particulate matters does not exceed the preset standard and the concentration of CO2 in the air is suddenly changed, judging that the personnel is increased;
And if the concentration of the particulate matters does not exceed the preset standard and the concentration of TVOC in the air is suddenly changed, judging that the condition of non-smoking interference is caused.
6. The smoke detection method of claim 1, wherein said method further comprises:
And judging whether the behavior of the interference equipment exists according to the real-time angular velocity information, and triggering a forced disassembly alarm when the behavior of the interference equipment is detected.
7. A smoke detection apparatus configured to perform:
Acquiring the concentration of the particles acquired by a particle sensor, and judging whether the concentration of the particles exceeds a preset standard;
If the concentration of the particulate matters exceeds the preset standard, judging whether the concentration of CO2 collected by the CO2 sensor and the concentration of TVOC collected by the TVOC sensor are suddenly changed;
If only the CO2 concentration is suddenly changed, triggering a cigarette alarm; if the CO2 concentration and the TVOC concentration are not suddenly changed, triggering an electronic cigarette alarm; if only the TVOC concentration is mutated, it is determined that the smoking masking behavior is performed.
8. The smoke detection device of claim 7, wherein said device is further configured to perform at least one of:
judging whether personnel exist or not based on human existence signals acquired by the PIR sensor and/or the voice detection module;
identifying the voice signals collected by the voice detection module, and triggering corresponding event alarms;
And judging whether the behavior of the interference equipment exists or not based on real-time angular velocity information acquired by the angular velocity sensor, and triggering a forced disassembly alarm when the behavior of the interference equipment is detected.
9. A computer program product comprising computer program/instructions which, when executed by a processor, implement the smoke detection method of any one of claims 1 to 6.
10. A computer-readable storage medium having stored therein at least one program that is executed by a processor to implement the smoke detection method of any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410311517.6A CN118330133A (en) | 2024-03-19 | 2024-03-19 | Smoke detection method, device, program product and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410311517.6A CN118330133A (en) | 2024-03-19 | 2024-03-19 | Smoke detection method, device, program product and storage medium |
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| CN118330133A true CN118330133A (en) | 2024-07-12 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN202410311517.6A Pending CN118330133A (en) | 2024-03-19 | 2024-03-19 | Smoke detection method, device, program product and storage medium |
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| Country | Link |
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| CN (1) | CN118330133A (en) |
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