A high-reliability fire detection method and system

Abstract

The application discloses a kind of high reliability fire detection method and system, it is related to fire alarm technical field, wherein detection method includes the following steps: S1, setting threshold value;S2, initialization background value, and the detection value is updated regularly and is updated initialization background value;S3, identify aerosol type;S4, identify personnel movement situation;S5, identify high humidity environment;S6, identify high temperature environment;S7, judge fire alarm.The detection system includes: threshold setting module, initialization module, smoke detection module, radar system, humidity detection module, temperature detection module, background value updating module and alarm module.The application relies on radar system to judge the personnel movement state of detection environment, combines smoke, temperature and humidity and other factors detection, and sets different levels alarm threshold to judge, so as to facilitate auxiliary enhancement fire detector to the identification ability of non-fire smoke, reduce the false alarm probability under non-fire smoke condition.

Description

Technical Field

[0001] This invention relates to the field of fire alarm technology, specifically to a highly reliable fire detection method and system. Background Technology

[0002] Currently, fire alarm systems are an essential component of building facilities, ensuring the fire safety of people moving within the buildings. When a fire or other incident occurs in a building, the fire alarm system will promptly issue a fire alarm, allowing people inside the building to escape in time and reducing casualties.

[0003] In existing fire alarm systems, photoelectric smoke detectors are one of the commonly used fire triggering devices. Most existing photoelectric smoke detectors adopt a dual-optical-path detection method. By calculating the changes in detection values ​​on different optical paths, they can distinguish between interfering substances such as water vapor and fire smoke, and set a larger alarm threshold for interfering substances to improve the detector's ability to prevent false alarms.

[0004] However, existing fire detection and alarm systems still have shortcomings: over time, the photoelectric smoke detectors used are easily contaminated by dust, grease, and other pollutants. Once the contamination reaches a certain level, the detector's sensitivity and other parameters will change, causing the detector to misjudge fire smoke as interfering substances, thus failing to provide timely fire warnings. Furthermore, factors such as smoke, temperature, and humidity are easily affected by changes in environmental factors. For example, ambient temperature and humidity can vary significantly with the seasons or due to factors such as the use of air conditioning indoors. Relying solely on these factors for fire alarm judgment can easily lead to inaccurate detection results and false alarms. Summary of the Invention

[0005] The purpose of this invention is to provide a highly reliable fire detection method and system to solve the technical problem that existing fire detection alarm identification methods only detect and judge factors such as smoke, temperature and humidity, which easily leads to inaccurate detection and judgment results and false alarms.

[0006] The technical problem to be solved by this invention can be achieved through the following technical solution:

[0007] A highly reliable fire detection method, applied to a dual-optical-path photoelectric smoke detector, is characterized by comprising the following steps:

[0008] S1. Set the aerosol type threshold, humidity threshold Hg, and temperature threshold Tg; obtain the smoke ratio r, humidity value H, and temperature value T; the aerosol type threshold is the scattering power ratio threshold rg used to distinguish the aerosol type;

[0009] S2. Initialize the baseline value, periodically update the detection value and update the baseline value;

[0010] S3. Determine whether the smoke ratio r is greater than the scattered power ratio threshold rg; if yes, set the alarm threshold to Th1 and then proceed to S7; if no, proceed to S4.

[0011] S4. Detect whether there are people in abnormal motion in the environment through the radar system; if yes, set the alarm threshold to Th3 and then proceed to S7; if no, proceed to S5.

[0012] S5. Determine if the humidity value H is greater than the humidity threshold Hg; if yes, set the alarm threshold to Th3 and then proceed to S7; if no, proceed to S6.

[0013] S6. Determine whether the temperature value T is less than the temperature threshold Tg. If yes, set the alarm threshold to Th2 and then proceed to S7; otherwise, set the alarm threshold to Th1 and then proceed to S7.

[0014] S7. Determine whether the smoke detection value increment Δ is greater than the current alarm threshold. If yes, then trigger an alarm; otherwise, jump to S2.

[0015] As a further aspect of the present invention: the dual-optical-path photoelectric smoke detector includes a smoke detection optical path A and a smoke detection optical path B, and the initialization of the background value in step S2 includes initializing the background value B of the smoke detection optical path A. A And the background value B of the smoke detection optical path B. B .

[0016] As a further aspect of the present invention: the step S2 of periodically updating the detection value and updating the background value includes:

[0017] Based on the real-time smoke detection values ​​V corresponding to smoke detection optical paths A and B A V B The corresponding data, including air humidity H and ambient temperature T, are overwritten and updated to obtain real-time detection values.

[0018] The real-time detection values ​​and historical baseline values ​​are weighted and summed.

[0019] As a further aspect of the present invention: the formula for calculating the smoke ratio r is:

[0020] r = (V A -B A ) / (V B -B B ).

[0021] As a further aspect of the present invention, the formula for calculating the increment Δ of the smoke detection value is as follows:

[0022] Δ=V A -B A .

[0023] As a further aspect of the present invention: the radar system in step S4 includes a human body recognition module, a position detection module, and a counting module.

[0024] As a further aspect of the present invention: the detection of whether there are people in abnormal motion states in the environment through the radar system includes the following steps:

[0025] Step 1: Determine whether a human body is present in the detection area using the human body recognition module; if not, mark the detection area as a place without people in abnormal movement; if yes, proceed to Step 2.

[0026] Step 2: Periodically detect the location of the human body using the position detection module, and calculate the displacement difference S based on the locations of adjacent human bodies. t Based on displacement difference S t Calculate the instantaneous velocity V of the target person using the time interval t. p Determine the instantaneous velocity V of the target person. p Is it 0? If no, proceed to step three; if yes, then based on the instantaneous velocity V... p A static continuous time of 0 is used to determine whether there are personnel in abnormal motion states;

[0027] Step 3: Set the total detection time to t 总 Counting threshold X, personnel movement speed threshold V m ; Several instantaneous velocities V p With velocity threshold V m Compare and statistically analyze the instantaneous velocity V. p Greater than the speed threshold V m The total number of times 'a'; when the detection time of the position detection module reaches the total detection time 't'. 总 Then, the total number of times 'a' is compared with the counting threshold 'X'. If the total number of times 'a' is greater than the counting threshold 'X', the movement state of the personnel in the detection environment is determined to be abnormal; otherwise, they are marked as personnel with no abnormal movement state.

[0028] As a further aspect of the present invention: the instantaneous motion velocity V p A static continuous time of 0 is used to determine whether there are personnel in an abnormal motion state, including:

[0029] Statistical instantaneous velocity V p The static continuous time t1 is set to 0, and a timing threshold t is set. m The static continuous time t1 is compared with the timing threshold t. m Comparison; when the static continuous time t1 equals the timing threshold t mThe system activates high-definition cameras distributed throughout the detection environment to capture images of people's faces, performs facial feature recognition, and determines whether the person is conscious. If yes, the person is marked as having no abnormal movement; otherwise, the person is marked as having abnormal movement.

[0030] As a further aspect of the present invention: the high-definition camera performs facial feature recognition based on a face recognition module, and the method for determining whether a person is awake is as follows:

[0031] Determine whether the facial recognition module has detected the facial eye features; if not, mark the person's status as unconscious.

[0032] If yes, then further determine whether the eye features indicate a closed eye state; if yes, then mark the person's status as unconscious; if no, then mark the person's status as conscious.

[0033] A high-reliability fire detection system, comprising:

[0034] The threshold setting module is used to set alarm thresholds, aerosol type thresholds, humidity thresholds, and temperature thresholds;

[0035] The initialization module is used to initialize the baseline value.

[0036] The smoke detection module is used to update the smoke detection values ​​periodically.

[0037] The radar system is used to periodically update the movement status of people in the environment.

[0038] Humidity detection module, used to update humidity detection values ​​periodically;

[0039] The temperature detection module is used to update the temperature detection value periodically;

[0040] The background value update module is used to update the background value;

[0041] The alarm module is used to issue a fire smoke alarm.

[0042] The beneficial effects of this invention are:

[0043] 1. This invention periodically updates the background and detection values ​​of various fire-affecting factors such as smoke, temperature, and humidity. It also uses a radar system to detect the movement of people in the environment in real time. By tracking and analyzing the positions of people in the detected environment, the invention effectively calculates their movement speed and compares it with a set speed threshold. This facilitates the determination of whether the movement is abnormal. If abnormal movement is detected, a corresponding alarm threshold is set, and a fire alarm is triggered. Otherwise, the temperature and humidity in the detected environment are monitored, and the corresponding alarm threshold is adjusted for judgment. This avoids false alarms caused by factors such as moisture and dust. In short, it relies on the radar system to determine the movement of people in the detected environment, combined with the detection of factors such as smoke, temperature, and humidity, and sets different alarm thresholds for judgment. This helps to enhance the fire detector's ability to identify non-fire smoke, reduces the probability of false alarms in non-fire smoke conditions, and improves the product's anti-interference capability against non-fire smoke.

[0044] 2. When the radar system detects and calculates the movement speed of people in the environment, the present invention continuously calculates the instantaneous movement speed multiple times within a set time period and counts the number of times the speed exceeds the speed threshold. Only when the number of instantaneous speeds exceeding the speed threshold by people in the environment reaches the set number within the set time period can it be determined as an abnormal escape state. This avoids the situation where people fall briefly and have no movement speed during the escape process, which would cause inaccurate judgment of the movement state and affect the fire alarm judgment result.

[0045] 3. When the radar system of this invention detects that a person in the environment is not moving, it performs facial and eye feature recognition and analysis to determine whether the person in the environment is awake. Based on whether the person in the non-moving state in the environment is awake, a corresponding alarm threshold is set to facilitate effective fire alarm judgment and reduce the possibility of misjudgment while ensuring the safety of personnel. Attached Figure Description

[0046] The invention will now be further described with reference to the accompanying drawings.

[0047] Figure 1 This is a block diagram illustrating the logical principle of a highly reliable fire detection method according to the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] like Figure 1As shown, a highly reliable fire detection method is applied to a dual-path photoelectric smoke detector, but it can also be applied to a multi-path photoelectric smoke detector. This explanation primarily uses a dual-path method as an example. The dual-path photoelectric smoke detector includes a smoke-detecting module. The detection method specifically includes the following steps:

[0050] S1. Set the fire alarm threshold Th, aerosol type threshold, humidity threshold Hg, and temperature threshold Tg. The alarm threshold Th is divided into three levels: Level 1 threshold Th1, Level 2 threshold Th2, and Level 3 threshold Th3, with the three levels decreasing in order: Th1 > Th2 > Th3. Also, obtain the smoke ratio r, humidity value H, and temperature value T. The aerosol type threshold is the scattering power ratio threshold rg used to distinguish aerosol types. Here, aerosol scattering refers to the scattering of light by aerosol particles. When light waves encounter aerosol particles, scattering occurs, meaning the direction and intensity of the light wave change. The scattering power ratio refers to the relative magnitude of the light power scattered by aerosol particles from different directions or of different types. The humidity threshold Hg is used to determine whether the ambient humidity reaches a high humidity level. The temperature threshold Tg is used to determine whether the ambient temperature reaches a high temperature level.

[0051] S2. Initialize the background value; It should be noted that the dual-path photoelectric smoke detector includes smoke detection optical path A and smoke detection optical path B. The initialization of the background value includes initializing the background value of smoke detection optical path A and the background value of smoke detection optical path B. The initialization background value of smoke detection optical path A is marked as B. A The background value of the initial smoke detection optical path B is marked as B. B The background value refers to the value of the basic or stable state of a system or device under specific conditions, without external interference or the presence of a specific target object. Therefore, the initial background value here refers to the detection value detected by the smoke-detecting module of the dual-optical-path photoelectric smoke detector in a smoke-free state, which is the most basic original value.

[0052] S3. Periodically update detection values; the smoke detection module of the dual-path photoelectric smoke detector periodically collects the photoelectric signal intensity of smoke detection optical path A and smoke detection optical path B, and converts it into real-time smoke detection values, which are marked as V respectively. A V B The system uses a radar system to periodically detect personnel movement, detecting signal R. A humidity module periodically collects the resistance value of a humidity-sensitive resistor and calculates the air humidity value H based on the resistance-humidity relationship curve. A temperature module periodically collects the resistance value of a thermistor and calculates the temperature value T, updating the detected values ​​(i.e., periodically updating the numerical value V). A V B R, H, T, to obtain real-time detection values.

[0053] S4. Periodically update the background value; the background value here includes the background value B of the smoke detection optical path A. A The background value B of the smoke detection optical path B B The background value B of the smoke detection optical path A is periodically acquired. A The background value B of the smoke detection optical path B B The update method is to update once every 4 hours, and the real-time detection value and the historical baseline value are weighted and summed. The real-time detection value has a weight of 1 / 8 and the historical baseline value has a weight of 7 / 8. The historical baseline value is the baseline value obtained at the time of each time the baseline value is updated.

[0054] S5. Identify the aerosol type; calculate the smoke ratio r, and determine if the smoke ratio r is greater than rg. If yes, set the alarm threshold to Th1, and then proceed to S9; otherwise, proceed to S6. The formula for calculating r is:

[0055] r = (V A -B A ) / (V B -B B ).

[0056] It should be noted that since dust concentrations in the environment are often high, a maximum alarm threshold Th1 is set to prevent false alarms.

[0057] S6. Identify personnel movement; The radar system detects whether there are personnel in abnormal movement states in the environment. Abnormal movement states refer to personnel whose movement speed in the detection environment exceeds a certain value within a set detection time and who are in an escape state. If yes, the alarm threshold is set to Th3, and then proceed to S9; otherwise, proceed to S7. The radar system detects personnel movement by transmitting and receiving electromagnetic waves.

[0058] The aforementioned radar system includes a human recognition module, a location detection module, and a counting module. The method by which the radar system detects whether there are people in abnormal motion states in the environment is as follows:

[0059] Step 1: The human body recognition module identifies whether there are people in the detection environment. If not, the detection area is marked as a person without abnormal movement. If so, the radar system continuously tracks the dynamic position of the target person based on the target tracking algorithm, and establishes a three-dimensional coordinate system based on the space of the detection environment. The position of the target person is projected into the three-dimensional coordinate system. Based on the coordinate position of the target person, the direction of the electromagnetic beam emitted by the position detection module is adjusted in real time through phased array technology, so that the target person is always within the coverage of the beam. Here, the phased array technology uses a computer to control the phase and amplitude of each electromagnetic wave radiation unit, so that these units can synthesize main beams with different phases and perform phase changes in both axes, thereby achieving precise control of the signal space beam. Then, proceed to Step 2.

[0060] Step 2: The location detection module periodically emits electromagnetic waves towards the target person, then receives and analyzes the reflected electromagnetic waves. The location of the target person is detected using FMCW waveform processing technology. Electromagnetic waves are transmitted and received at intervals t, and the target person's location is detected once. This interval t can be set to the second level, such as 2 or 3 seconds, and the total detection time is t. 总 , t 总 The time interval can be 30 seconds; and the displacement difference S is calculated based on the location of the target personnel in two consecutive intervals. t Then based on the displacement difference S t Calculate the instantaneous velocity V of the target person using the time interval t. p =S t / t;

[0061] The aforementioned FMCW waveform processing technology involves using a frequency-modulated radar to transmit a continuous wave with a linearly varying frequency and receiving the reflected signal. By measuring the frequency difference between the transmitted and reflected signals, the target's distance and velocity can be calculated.

[0062] Step 3: The radar system also includes a comparison module and a counting module, setting the personnel movement speed threshold V. m The instantaneous velocity V obtained each time p With V m The instantaneous velocity V is statistically analyzed by comparing data through the comparison module. p Greater than the speed threshold V m The total number of times 'a' is calculated, and a counting threshold 'X' is set; if V p Greater than V m The counting module increments the total number of counts 'a' by 1; V p Less than V m When the total detection time t is reached, no change in count occurs. 总Then, the accumulated total number of times 'a' is compared with the counting threshold 'X' using a comparison module. If 'a' is greater than 'X', the detected environment is determined to be in an abnormal escape state, and there is a high probability of a fire. Therefore, the alarm threshold is set to 'Th3', and the process proceeds to S9. If 'a' is less than 'X', it means that people in the environment are only running occasionally. Therefore, the detected environment is determined to be in a normal movement state, with no abnormal movement, and the probability of a fire is low. The process proceeds to S7. The counting method used here is mainly to avoid false judgments caused by people falling due to panic during escape in the event of a fire, resulting in a short period of inactivity.

[0063] It should be noted that if step two involves calculating the instantaneous velocity V of the target person... p When the value is 0, the radar system uses a set timing module to independently time the continuous stationary time t1, and sets a timing threshold t. m V was calculated multiple times consecutively. p =O, the timing module maintains the timing state; if V appears... p ≠ 0, t1 returns to zero, if t1 = t m The system activates high-definition cameras distributed throughout the detection environment to capture facial images of personnel and perform facial feature recognition. To ensure the effectiveness of facial image capture, multiple high-definition cameras can be installed at various angles within the detection environment to determine whether the personnel are conscious. If so, it indicates that there are no personnel with abnormal movement in the detection environment, and the possibility of a fire is relatively small, proceeding to S7. If not, it indicates that there are personnel with abnormal movement in the detection environment, and an alarm threshold TH1 is set, proceeding to S9. Here, when it is determined that the personnel are not conscious, it is because the personnel may be in a resting state, such as taking a nap, or they may be unconscious due to the production of harmful substances from a fire. However, for the sake of life safety, in either case, to prevent a fire from occurring when the personnel are not conscious and causing serious casualties, it directly proceeds to S9 to determine a fire alarm. However, in order to reduce the probability of false alarms, the alarm threshold is set to TH1, which increases the determination level.

[0064] It should also be noted that the high-definition camera uses a facial recognition module to identify facial features. When determining whether a person is awake, the specific method is as follows: the facial recognition module identifies the person's face captured by the high-definition camera and extracts the eye features. If the eye features are extracted, the eye state is identified to determine whether the eyes are open or closed. If the eyes are open, the person is considered awake; if the eyes are closed, the person is considered not awake. If no eye features are extracted, the person is also considered not awake.

[0065] S7. Identify high humidity environment; The humidity module periodically collects the resistance value of the humidity-sensitive resistor and calculates the air humidity value H based on the resistance-humidity relationship curve. It determines whether the humidity value H is greater than Hg. If so, the alarm threshold is set to Th3, and then proceeds to S9. It should be noted that if the humidity value H exceeds the humidity threshold Hg, it means that the detected environment is very likely to have triggered the indoor fire sprinkler system due to a fire. When the humidity threshold Hg is set high, the ambient humidity is generally unlikely to exceed the humidity threshold Hg. Therefore, if the humidity threshold Hg is exceeded, the possibility of a fire is high. Hence, a lower alarm threshold of Th3 is set to facilitate fire alarm detection. If H is less than Hg, proceed to S8.

[0066] S8. Identify high-temperature environment; periodically collect the resistance value of the thermistor, and convert the temperature value T according to the thermistor relationship curve. Determine whether the temperature value T is less than Tg. If so, set the alarm threshold to Th2 and then proceed to S9; otherwise, set the alarm threshold to Th1 and then proceed to S9.

[0067] S9. Determine if a fire alarm is triggered; check if the smoke detection value increment Δ is greater than the current alarm threshold. If yes, trigger an alarm; otherwise, return to S3. The formula for calculating Δ is as follows:

[0068] Δ=V A -B A .

[0069] The present invention also discloses a high-reliability fire detection system, comprising: a threshold setting module, an initialization module, a smoke detection module, a radar system, a humidity detection module, a temperature detection module, a background value update module, and an alarm module.

[0070] The threshold setting module is used to set alarm thresholds, aerosol type thresholds, humidity thresholds, and temperature thresholds;

[0071] The initialization module is used to initialize the baseline value.

[0072] The smoke detection module is used to update the smoke detection values ​​periodically.

[0073] The radar system is used to periodically update the movement status of people in the environment.

[0074] Humidity detection module, used to update humidity detection values ​​periodically;

[0075] The temperature detection module is used to update the temperature detection value periodically;

[0076] The background value update module is used to update the background value; and

[0077] The alarm module is used to issue a fire smoke alarm.

[0078] The embodiments of the present invention have been described in detail above, but the embodiments of the present invention are not limited thereto and should not be considered as limiting the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the patent coverage of the present invention.

Claims

1. A highly reliable fire detection method, applied to a dual-optical-path photoelectric smoke detector, characterized in that... Includes the following steps: S1. Set the aerosol type threshold, humidity threshold Hg, and temperature threshold Tg; obtain the smoke ratio r, humidity value H, and temperature value T; the aerosol type threshold is the scattering power ratio threshold rg used to distinguish the aerosol type; S2. Initialize the baseline value, periodically update the detection value and update the baseline value; S3. Determine whether the smoke ratio r is greater than the scattered power ratio threshold rg; If yes, then set the alarm threshold to Th1, and then proceed to S7; No, proceed to S4; S4. Detect whether there are people in abnormal motion in the environment through the radar system; if so, set the alarm threshold to Th3, and then proceed to S7. No, then proceed to S5; S5. Determine if the humidity value H is greater than the humidity threshold Hg; if yes, set the alarm threshold to Th3, and then proceed to S7. No, proceed to S6; S6. Determine whether the temperature value T is less than the temperature threshold Tg. If yes, set the alarm threshold to Th2 and then proceed to S7; otherwise, set the alarm threshold to Th1 and then proceed to S7. S7. Determine whether the smoke detection value increment Δ is greater than the current alarm threshold. If yes, then alarm; otherwise, jump to S2. The dual-optical-path photoelectric smoke detector includes smoke detection optical path A and smoke detection optical path B. Step S2, initializing the background value, includes initializing the background value B of smoke detection optical path A. A And the background value B of the smoke detection optical path B. B ; Step S2, which involves periodically updating the detection values ​​and updating the baseline values, includes: updating the real-time smoke detection values ​​V corresponding to smoke detection optical paths A and B. A V B The corresponding data, including air humidity H and ambient temperature T, are overwritten and updated to obtain real-time detection values. The real-time detection values ​​and historical baseline values ​​are weighted and summed. The formula for calculating the smoke ratio r is: r=(V A -B A ) / (V B -B B )。 2. The high-reliability fire detection method according to claim 1, characterized in that, The formula for calculating the increment Δ of the smoke detection value is as follows: Δ=V A -B A 。 3. The high-reliability fire detection method according to claim 1, characterized in that, The radar system in step S4 includes a human body recognition module, a position detection module, and a counting module.

4. The high-reliability fire detection method according to claim 3, characterized in that, The process of detecting whether there are people in abnormal motion in the environment using a radar system includes the following steps: Step 1: Determine whether a human body is present in the detection area using the human body recognition module; if not, mark the detection area as a place without people in abnormal movement; if yes, proceed to Step 2. Step 2: Periodically detect the location of the human body using the position detection module, and calculate the displacement difference S based on the locations of adjacent human bodies. t Based on displacement difference S t Calculate the instantaneous velocity V of the target person using the time interval t. p Determine the instantaneous velocity V of the target person. p Is it 0? If no, proceed to step three; if yes, then based on the instantaneous velocity V... p A static continuous time of 0 is used to determine whether there are personnel in abnormal motion states; Step 3: Set the total detection time to t 总 Counting threshold X, personnel movement speed threshold V m ; Several instantaneous velocities V p With velocity threshold V m Compare and statistically analyze the instantaneous velocity V. p Greater than the speed threshold V m The total number of times 'a'; when the detection time of the position detection module reaches the total detection time 't'. 总 Then, the total number of times 'a' is compared with the counting threshold 'X'. If the total number of times 'a' is greater than the counting threshold 'X', the movement state of the personnel in the detection environment is determined to be abnormal; otherwise, they are marked as personnel with no abnormal movement state.

5. The high-reliability fire detection method according to claim 4, characterized in that, The instantaneous velocity V p A static continuous time of 0 is used to determine whether there are personnel in an abnormal motion state, including: Statistical instantaneous velocity V p The static continuous time t1 is set to 0, and a timing threshold t is set. m The static continuous time t1 is compared with the timing threshold t. m Comparison; when the static continuous time t1 equals the timing threshold t m The system activates high-definition cameras distributed throughout the detection environment to capture images of people's faces, performs facial feature recognition, and determines whether the person is conscious. If yes, the person is marked as having no abnormal movement; otherwise, the person is marked as having abnormal movement.

6. The high-reliability fire detection method according to claim 5, characterized in that, The high-definition camera uses a facial recognition module to identify facial features of people. The method for determining whether a person is awake is as follows: Determine whether the face recognition module has detected the facial eye features; No, then mark the person's status as unconscious; If yes, then further determine whether the eye features indicate a closed eye state; if yes, then mark the person's state as unconscious. If not, mark the person's status as awake.

7. A high-reliability fire detection system for implementing the high-reliability fire detection method according to claim 1, characterized in that, include: The threshold setting module is used to set alarm thresholds, aerosol type thresholds, humidity thresholds, and temperature thresholds; The initialization module is used to initialize the baseline value. The smoke detection module is used to update the smoke detection values ​​periodically. The radar system is used to periodically update the movement status of people in the environment. Humidity detection module, used to update humidity detection values ​​periodically; The temperature detection module is used to update the temperature detection value periodically; The background value update module is used to update the background value; The alarm module is used to issue a fire smoke alarm.

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