Intelligent dustproof mask capable of monitoring fatigue state of miner in real time

Abstract

The invention discloses an intelligent dustproof mask capable of monitoring the fatigue state of a miner in real time. The intelligent dustproof mask comprises a physiological signal sensor, an eye monitoring sensor, an attitude sensor, a display and communication system, a communication module, a battery and power management system, an air filtering system and a control module. The physiological signal sensor, the eye monitoring sensor and the attitude sensor input collected information into the control module, and the signal output end of the control module is connected with the display and communication system. The control module is in two-way communication with the communication module, the control module sends data to the communication module, and the communication module transmits a received external instruction to the control module; and the battery and the power management supply power to each module. The safety of miners is remarkably improved, the fatigue state can be monitored in real time and fed back in time, accidents caused by fatigue are effectively prevented, and the life safety of the miners is guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of dust masks, and in particular to an intelligent dust mask capable of monitoring the fatigue state of miners in real time. Background Art

[0002] When working underground, miners are exposed to harsh environments such as high temperature, low oxygen, and dust for a long time. These factors put miners at great physical burden and health risks. In particular, when they are fatigued, their reaction ability, attention, and judgment will be significantly reduced, making accidents and safety hazards very likely to occur. Therefore, real-time monitoring of miners' fatigue status and taking effective early warning measures are crucial to ensure the safety of miners.

[0003] Traditional miner safety monitoring systems rely on external environmental monitoring (such as gas concentration, temperature and humidity, etc.) or regular physical examinations, but these methods cannot accurately reflect the physical condition of miners in real time. In recent years, with the development of smart wearable devices and sensor technology, combining smart monitoring systems with protective equipment (such as masks, protective clothing, etc.) has become an emerging solution to improve miner safety.

[0004] At present, there are some products related to smart dust masks on the market, but their functions are mainly concentrated in the following aspects:

[0005] 1. Smart protective mask

[0006] Some smart protective masks are already equipped with sensor systems that can monitor miners' breathing and gas concentrations in real time. These products usually integrate filters and sensors to ensure the safety of miners by detecting harmful gases (such as methane, carbon monoxide, etc.) in the mine environment. For example, some smart protective masks with gas sensors can automatically adjust the air circulation in the mask according to the gas concentration to prevent miners from inhaling harmful substances. However, this type of mask mainly focuses on environmental monitoring and does not directly solve the problem of real-time monitoring of miners' fatigue status.

[0007] 2. Wearable devices based on physiological parameter monitoring

[0008] Some wearable devices (such as smart bracelets and smart chest straps) are already able to monitor miners' physiological indicators (such as heart rate, pace, skin galvanic response, etc.) and transmit data to the monitoring center via Bluetooth or wireless networks. These devices use physiological data to assess the fatigue level of miners and issue alarms through vibration or sound. Although such devices can monitor miners' fatigue status to a certain extent, they are usually not integrated into protective equipment such as masks, and the monitoring accuracy is limited.

[0009] 3. Miner health monitoring system

[0010] In recent years, some mining companies have begun to try to deploy complete miner health monitoring systems in mines. These systems combine environmental monitoring, behavioral monitoring, and physiological data monitoring technologies. For example, some companies install sensors on miners' clothing or helmets to track miners' body temperature, heart rate, location and other information in real time, and analyze miners' fatigue through cloud platforms. These systems can effectively monitor the health status of miners, but they do not integrate all monitoring functions into one device and usually do not have dustproof functions. Summary of the invention

[0011] In order to overcome the above technical problems, the purpose of the present invention is to provide an intelligent dust mask that can monitor the fatigue status of miners in real time. The dust mask significantly improves the safety of miners, can monitor and promptly feedback the fatigue status in real time, effectively prevent accidents caused by fatigue, and ensure the life safety of miners.

[0012] In order to achieve the above object, the technical solution adopted by the present invention is:

[0013] An intelligent dust mask capable of real-time monitoring of miners' fatigue status, comprising a physiological signal sensor, an eye monitoring sensor, a posture sensor, a display and communication system, a communication module, a battery and power management, an air filtration system, and a control module;

[0014] The physiological signal sensor, eye monitoring sensor and posture sensor input the collected information into the control module, and the signal output end of the control module is connected to the display and communication system;

[0015] The control module communicates with the communication module in a two-way manner, the control module sends data to the communication module, and the communication module transmits the received external instructions to the control module;

[0016] The battery and power management provide power for each module.

[0017] The physiological signal sensor is connected to the control module, and the physiological signal sensor is used to transmit physiological data in real time to analyze fatigue status;

[0018] Physiological signal sensors include heart rate sensors and breathing sensors;

[0019] The physiological signal sensor is installed on the inner side of the embedded mask and contacts the facial area;

[0020] The facial area is divided into a forehead contact area and both sides of the nose / cheeks. The forehead contact area is used to monitor heart rate and body temperature using integrated flexible electrodes or optical sensors.

[0021] The wings of the nose / cheeks are used to detect breathing rate, using airflow or pressure difference sensors.

[0022] The heart rate sensor and breathing sensor use a photoplethysmography (PPG) sensor to monitor the heart rate; the PPG sensor measures tiny changes in blood flow through the skin surface to obtain heart rate information, and the breathing rate is achieved by monitoring chest movement through an airflow sensor;

[0023] The PPG sensor is used in conjunction with the ECG sensor (electrocardiogram sensor) to monitor heart rate changes in real time. The data is transmitted to the control unit through electric current, processed and output to the display module.

[0024] The eye monitoring sensor is connected to the control module, and is used to monitor visual fatigue indicators such as blinking frequency and eyelid closure;

[0025] The eye monitoring sensor is a camera or an infrared sensor;

[0026] The eye monitoring sensor is located at the top inside of the mask, near the brow bone area, directly above the eyes; a miniature infrared camera or infrared sensor is aimed at both eyes to monitor blinking frequency and eyelid closure.

[0027] The eye sensor uses infrared eye tracker opening and closing detection technology. The eye monitoring system irradiates the eye area with an infrared light source to detect eyelid movement or eyeball activity. The camera collects eye images and analyzes the opening and closing of the eyes through an image processing algorithm.

[0028] Using infrared LEDs (infrared light-emitting diodes) and photoelectric sensors combined with eye tracking technology, fatigue is monitored by calculating the degree of eye closure; real-time data is analyzed by an embedded processor and combined with other physiological parameters to determine whether miners are at risk of fatigue.

[0029] The specific image processing algorithm is:

[0030] Step 1. Baseline calibration

[0031] Eye opening baseline value I open : When the user opens his eyes and remains still, the average reflected light intensity is collected for 10 seconds;

[0032] Eyes closed baseline value I close : The average intensity of reflected light when the user closes his eyes;

[0033] Step 2. Real-time closure calculation

[0034] Normalized reflection intensity:

[0035]

[0036] Step instantaneous closure C(t):

[0037]

[0038] Infrared LED array: installed on the top inside of the mask (above the brow bone), it projects infrared light (wavelength 850nm or 940nm) to both eyes at a specific angle (30°-45°).

[0039] Photoelectric sensors: Symmetrically distributed on both sides of the LED, receiving infrared light reflected from the eyeball and eyelid

[0040] The posture sensor is connected to the control module to detect the action signal of head tilt and abnormal body posture (such as falling);

[0041] The attitude sensor is an accelerometer / gyroscope;

[0042] The attitude sensor is located at the top of the mask. The attitude sensor integrates a three-axis accelerometer and a gyroscope to detect the tilt angle of the head;

[0043] The accelerometer / gyroscope is used to detect the posture and movement of the miner's head. The three-axis accelerometer measures the movement changes of the head, and the gyroscope detects the rotation angle of the head. The combined use can provide complete posture monitoring data.

[0044] A low-power acceleration sensor (MEMS accelerometer) is combined with a gyroscope to detect the miner's head movements in real time and determine whether the miner is in a state of fatigue (frequent lowering of the head, slow head movement, etc.).

[0045] The fatigue status determination basis based on MEMS accelerometers and gyroscopes is as follows:

[0046] Step 1. Data collection and preprocessing

[0047] Accelerometer data: measures the linear acceleration of the head in three axes (X / Y / Z), including gravity components and motion acceleration;

[0048] Gravity separation: Separate dynamic motion acceleration through a high-pass filter to eliminate static gravity interference;

[0049] Motion Amplitude Calculation: Using Acceleration Vector and Formula quantify the intensity of head movements;

[0050] Gyroscope data: measures the angular velocity of the head around three axes (pitch, roll, yaw);

[0051] Angle integration: Integrate the angular velocity over time to obtain the head posture angle (such as pitch angle) to determine the amplitude of lowering or raising the head;

[0052] Step 2. Fatigue motion feature extraction

[0053] Frequent head-down detection judgment basis:

[0054] Pitch Angle Threshold: Set the pitch angle (head-down angle) to exceed -20° (with horizontal as 0°) as a valid head-down action;

[0055] Frequency threshold: If the number of times of lowering the head in a unit of time (e.g., 10 minutes) is ≥5 times, it is judged as "frequent lowering of the head";

[0056] Slow head movement detection is based on:

[0057] Acceleration amplitude threshold: When the dynamic acceleration amplitude is less than 0.2g (g is the acceleration due to gravity), it is considered as slow head movement.

[0058] Duration threshold: If the slow state lasts for >30 seconds, it is judged as "bradykinesia".

[0059] Abnormal shaking detection judgment basis:

[0060] Gyroscope angular velocity variance: Calculate the variance of the angular velocity. If the variance is > 50 degrees, 2 / s 2 , indicating irregular shaking of the head.

[0061] Combined with accelerometer data: If the acceleration amplitude during shaking is >1.5g, it is judged as "abnormal shaking".

[0062] Step 3. Multi-dimensional data fusion and fatigue level assessment

[0063] Weight distribution:

[0064] Frequent bowing of the head (weight 40%), slow movement (weight 30%), abnormal shaking (weight 30%);

[0065] Fatigue index = (low-frequency head bowing score × 0.4) + (slow movement score × 0.3) + (abnormal shaking score × 0.3);

[0066] Classification alarm:

[0067] Mild fatigue (index ≥ 60): triggers a voice prompt and recommends a short rest;

[0068] Severe fatigue (index ≥ 85): trigger a strong vibration alarm and upload data to the monitoring center;

[0069] Step 4. Anti-interference and adaptive optimization

[0070] Dynamic threshold adjustment: Based on individual differences of miners (such as height and movement habits), a 10-minute baseline calibration is performed during initial use to automatically adjust the pitch angle threshold and acceleration amplitude threshold;

[0071] Noise Filtering:

[0072] The acceleration data were smoothed using the sliding window averaging method (window length 1 second);

[0073] Use Kalman filter to optimize gyroscope angle integration and reduce cumulative error;

[0074] Step 5. Real-time performance and low power consumption guarantee

[0075] Sampling frequency: The sensor data sampling rate is set to 50Hz to balance accuracy and power consumption;

[0076] Sleep strategy: If there is no significant movement (acceleration amplitude <0.1g for 5 seconds), the sensor enters low-power mode and only maintains basic monitoring.

[0077] The three-axis accelerometer and gyroscope are integrated in the center of the top of the mask (close to the center of gravity of the head), fixed by a rigid bracket, and rigidly connected to the main structure of the mask to ensure that the sensor moves synchronously with the head. The sensor module is encapsulated in a dust-proof and shock-proof housing to avoid mine dust intrusion or mechanical shock interference. When installed, it should be close to the center of gravity of the miner's head to minimize motion noise and improve posture detection accuracy.

[0078] The control module is a microprocessor / embedded system;

[0079] The input of the control module is used to receive all sensor data and perform fusion analysis (combining heart rate and eye data to determine fatigue level);

[0080] The output side of the control module sends instructions to the display system, communication module, and air filtration system according to the algorithm results. The control module is set behind the bridge of the nose in the center of the inner side of the mask;

[0081] The control module includes a main control chip and a storage unit. The main control chip is an embedded microprocessor (ARM Cortex-M series) responsible for data fusion and decision-making;

[0082] The storage unit is adjacent to the main control chip and caches sensor data.

[0083] The control module is responsible for receiving data from sensors and performing real-time analysis, judging the fatigue status of miners according to the set algorithm, and issuing warnings through display screens or sending alarms through wireless communication, using efficient embedded systems for data processing and decision-making. The control module needs to have the functions of real-time data collection, analysis and feedback, processing data from various sensors and responding in real time.

[0084] Specifically:

[0085] Step 1. Sensor data preprocessing

[0086] Accelerometer data filtering:

[0087] The acceleration data were smoothed using the sliding window averaging method, with a window length of N = 10 (corresponding to 0.2 seconds and a sampling rate of 50 Hz);

[0088]

[0089] Gyroscope angle integration:

[0090] Integrate the angular velocity ω over time to calculate the pitch angle θ (head-down angle):

[0091] θ[t]=θ[t-1]+ω y [t]·Δt

[0092] Among them, ω y is the pitch axis angular velocity, Δt = 0.02s;

[0093] Step 2. Feature extraction and fatigue determination

[0094] Frequent head-down detection judgment formula:

[0095] Pitch angle threshold: If θ<-20°, it is recorded as a valid head-down action.

[0096] Frequency threshold: If the number of times of lowering the head within 10 minutes is ≥5, it is judged as fatigue;

[0097] Slow head movement detection

[0098] Dynamic acceleration calculation:

[0099] Among them, g x , g y , g z is the gravity component, separated by high-pass filtering;

[0100] Judgment formula: If A dynamic <0.2g for >30 seconds was considered bradykinesia;

[0101] Abnormal shaking detection

[0102] Angular velocity variance calculation:

[0103] (N=50, window length 1 second, is the mean angular velocity within the window)

[0104] Judgment formula: If σ 2 >50deg 2 / s 2 And A dynamic >1.5g, considered as abnormal shaking;

[0105] Step 3. Multi-sensor data fusion and fatigue index calculation

[0106] Weight distribution:

[0107] Physiological signals (heart rate, breathing rate): weight 30%;

[0108] Eye monitoring (blinking frequency, pupil reaction): weight 30%;

[0109] Posture data (bowing, shaking): weight 40%;

[0110] Fatigue Index formula: Fatigue Index = 0.3·S physio +0.3·S eye +0.4·S posture

[0111] Scoring Rules:

[0112] S physio : A heart rate that exceeds the baseline value by 10% is scored as 20 points, and abnormal breathing is scored as 10 points. The total score is normalized to 0-100.

[0113] S eye : A 50% decrease in blink frequency is worth 30 points, abnormal pupil dilation is worth 20 points, and the total score is normalized.

[0114] S posture : Frequent bowing of the head is scored 40 points, slow movement is scored 30 points, abnormal shaking is scored 30 points, and the total score is normalized;

[0115] Hierarchical alarm strategy:

[0116] Mild fatigue (index 60-84): The OLED screen displays a yellow warning and the buzzer beeps briefly.

[0117] Severe fatigue (index ≥ 85): triggers a red alarm, continuous beeping, and uploads an emergency signal to the monitoring center via Wi-Fi.

[0118] Real-time data processing flow:

[0119] Data acquisition: synchronously read all sensor data at 50Hz;

[0120] Preprocessing: filtering, gravity separation, angle integration;

[0121] Feature extraction: calculate frequency, amplitude, variance and other indicators;

[0122] Fatigue assessment: weighted score and index calculation;

[0123] Feedback and communication: trigger local alarms or remote transmission based on the results;

[0124] The display and communication system (micro transparent OLED display or vibration alarm or LED warning light) is driven by the control module, directly receives instructions and displays the real-time status ("fatigue warning") or triggers an alarm;

[0125] The display and communication system is installed on the outer forehead area of ​​the mask, and the micro transparent OLED display (displaying fatigue level, battery level, etc.) is installed on the outer forehead and is visible to the wearer;

[0126] A vibration motor or LED warning light (which indicates fatigue status through touch / visual sense) is installed near the side ear.

[0127] The display screen shows real-time monitoring data (heart rate, eye closure, etc.) and warning information (fatigue alarm). It needs to have the characteristics of low power consumption and high visibility.

[0128] The display screen is embedded in the right outer edge of the mask (non-main field of view) and adopts a translucent design to ensure that miners can view warning information (such as abnormal heart rate and fatigue alarm) through peripheral vision.

[0129] The communication module (Bluetooth / Wi-Fi / ) is controlled by the control module, and uploads the fatigue status and sensor data to an external device (monitoring center or mobile phone App); the communication module is installed on the top of the mask and is a Wi-Fi / Bluetooth / LoRa antenna, which extends upward to enhance signal penetration.

[0130] When moderate fatigue is detected: the air filtration system automatically increases the air volume by 20% (stimulating facial perception), the OLED displays a yellow warning icon, and the buzzer emits a 2kHz intermittent reminder tone;

[0131] In severe fatigue state: trigger the emergency braking protocol (send GPS coordinates to the dispatch center through the communication module), start the backup power supply forcibly, and activate the mask positioning flash mark.

[0132] The battery and power supply side of the power management provide power for all electronic modules (sensors, control modules, communication modules, display systems);

[0133] The management side of the battery and power management is used to monitor the battery power, feedback low-battery warnings through the control module, and optimize energy consumption distribution (adjust sensor sampling frequency);

[0134] The battery and power management are installed at the bottom of the mask, which is a detachable battery compartment: symmetrically distributed on the left and right, with balanced weight (such as a 18650 lithium battery pack); the power management chip is integrated in the battery compartment to monitor the charging and discharging status in real time.

[0135] The air filtration system is used to receive instructions from the control module (such as adjusting the fan speed according to the breathing frequency), and the air filtration system is installed at the lower front part of the mask;

[0136] The air filtration system uses a small HEPA (high efficiency particulate air) filter or activated carbon filter, which can effectively filter harmful gases and particles. A fan or air pump is used to provide air flow to ensure that filtered air enters the mask and is breathable.

[0137] The HEPA filter is installed at the air inlet on the front of the mask, and the activated carbon layer is located at the rear end of the filter; micro centrifugal fans are embedded on both sides of the mask to drive external air through the filter into the breathing chamber.

[0138] An outlet valve is set on the HEPA filter. The outlet valve is a one-way exhaust valve on both sides to discharge carbon dioxide and maintain the balance of breathing resistance.

[0139] Beneficial effects of the present invention:

[0140] The present invention uses multiple sensors (such as physiological signal sensors, eye monitoring sensors, and posture sensors) for comprehensive monitoring, and can identify the fatigue state of miners in real time and issue warnings. Compared with the limitation that traditional masks or helmets cannot effectively identify fatigue states, the present invention significantly improves the safety of miners. The smart mask monitors fatigue states in real time and promptly provides feedback, which can effectively prevent accidents caused by fatigue and protect the lives of miners.

[0141] The present invention integrates multiple sensors to comprehensively monitor the miners' physiological data (such as heart rate, respiratory rate), eye closure, head posture and other indicators, and accurately evaluates the miners' fatigue status through data fusion analysis. The complementarity and cross-validation of different sensor data make fatigue monitoring more accurate and comprehensive. Through multi-dimensional monitoring and data fusion, not only the accuracy of fatigue detection is improved, but also the possibility of missed detection and false alarm is reduced.

[0142] The present invention is equipped with a wireless communication module, which can upload the miners' health data to the background monitoring system in real time, so that external managers can monitor the miners' health status at any time and detect potential fatigue risks in time. In addition, the smart mask can directly feedback fatigue warnings to miners through the display screen, reminding miners to rest in time. The present invention realizes real-time feedback and remote monitoring of miners' fatigue status, which not only enhances miners' self-protection awareness, but also provides managers with more efficient emergency response means.

[0143] The present invention uses an efficient battery management system to optimize battery usage and power distribution, which can ensure the stability of sensors, displays, communication systems and other equipment during long-term operation. The system monitors the battery status to avoid over-discharge, thereby extending the use time and ensuring that the equipment does not fail due to power problems. The optimization of the battery management system enables the present invention to maintain stable operation during long-term use, ensuring that the safety monitoring of miners is not affected by battery life issues. BRIEF DESCRIPTION OF THE DRAWINGS

[0144] Figure 1 This is a schematic diagram of the eye data monitoring process of the present invention.

[0145] Figure 2 This is a schematic diagram of the physiological data monitoring process of the present invention.

[0146] Figure 3 This is a schematic diagram of monitoring head data according to the present invention.

[0147] Figure 4 This is a principle block diagram of the present invention.

[0148] Figure 5 This is a schematic diagram of the dust mask structure. DETAILED DESCRIPTION

[0149] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0150] like Figure 1-Figure 5 The smart dust mask that can monitor the fatigue status of miners in real time is shown in the figure. When miners wear the smart dust mask, they can not only effectively prevent dust and harmful gases from harming the miners' respiratory system, but also track the miners' physiological status in real time through the integrated physiological monitoring system. The mask is equipped with advanced sensors that can continuously monitor the miners' heart rate, respiratory rate, body temperature and other key physiological indicators.

[0151] When miners experience physical exhaustion, overwork, abnormal breathing, etc. in the working environment, the algorithm built into the mask will automatically analyze these physiological data and process them in real time.

[0152] If an abnormality occurs, the system can immediately sound an alarm, prompting miners or relevant staff to take emergency measures. In addition, the equipment is also equipped with a remote data transmission function, which can upload the miners' physiological data to the background monitoring system in real time for on-site managers to track and evaluate.

[0153] If the mask or monitoring equipment fails, the system will automatically detect and send a fault notification, reminding maintenance personnel to check and repair the equipment in time to ensure the safety of miners.

[0154] The method for determining equipment failure is:

[0155] Step 1: Periodic self-test (on startup and every hour)

[0156] Self-test content:

[0157] All sensors are powered on and verified.

[0158] The communication module sends a test signal to the background and receives a response.

[0159] Battery voltage, temperature and power detection.

[0160] Fan speed and air flow sensor baseline calibration.

[0161] Step 2: Real-time data monitoring and abnormality determination

[0162] Data rationality check:

[0163] Physiological data: heart rate (40-180 BPM), respiratory rate (8-30 times / minute).

[0164] Eye data: closure degree (0-100%), blink frequency (≥5 times / minute).

[0165] Attitude data: pitch angle (-90° to +90°), dynamic acceleration (<5g).

[0166] Threshold trigger: If the sensor data exceeds the threshold for three consecutive times, it is marked as "abnormal".

[0167] Step 3: Fault classification and prioritization

[0168] Emergency failure (immediate notification): power failure (battery level <5%), complete communication interruption, CO2 concentration exceeding the standard.

[0169] Important faults (notified within 10 minutes): sensor failure, air filtration system blockage.

[0170] General faults (notified within 1 hour): insufficient signal strength, redundant verification warning.

[0171] Step 4: Trigger the multi-level notification mechanism

[0172] Feedback from miners: Mask vibration + OLED screen displays fault code.

[0173] Background notification: send fault code and GPS coordinates to the monitoring center via Wi-Fi / LoRa. SMS / App push to maintenance personnel (priority based on fault level).

[0174] Step 5: Enter Safe Mode

[0175] Emergency measures: Turn off non-essential modules (such as display) to extend battery life. Enable backup filters (such as dual filter design). Continue to send positioning signals until repaired.

[0176] The smart masks worn by miners are equipped with sensors specifically designed to monitor eye status, which can collect real-time health data on the miners' eyes through multiple indicators such as eye movement, intraocular pressure, and pupil reaction. These data include but are not limited to eye fatigue, blinking frequency, and intraocular pressure changes.

[0177] The smart masks worn by miners are equipped with sensors specifically designed to monitor eye status, which can collect real-time health data on the miners' eyes through multiple indicators such as eye movement, intraocular pressure, and pupil reaction. These data include but are not limited to eye fatigue, blinking frequency, and intraocular pressure changes.

[0178] When miners work in an environment with high temperature, low oxygen and high dust content, these eye physiological indicators can reflect the miners' fatigue level or potential health problems, such as blurred vision, dry eyes, etc., and may even indicate more serious health risks.

[0179] Data collection process

[0180] Blinking frequency: The infrared sensor monitors the opening and closing movements of the eyelids and calculates the number of blinks per minute.

[0181] Eyelid closure degree: The degree of eyelid closure (i.e. the percentage of eyelid closure) is calculated by the change in the intensity of reflected light.

[0182] Pupil reaction: Monitor changes in pupil size through an infrared camera or photoelectric sensor to determine whether the pupil's reaction to light is normal.

[0183] Changes in intraocular pressure: Changes in intraocular pressure are inferred through indirect eye movement data (such as eyelid closure frequency and pupil response).

[0184] Fatigue determination basis

[0185] Reduced blinking frequency: The normal blinking frequency is 15-20 times per minute. If the blinking frequency is less than 5 times per minute, it may indicate that the miner is in a state of fatigue.

[0186] Increased eyelid closure: If the eyelid closure C(t) exceeds 50% and lasts for a long time (such as more than 5 seconds), it may indicate that the miner is in a state of fatigue.

[0187] Abnormal pupil responses: If the pupils are sluggish or abnormally dilated to light, this could indicate that the miner is fatigued or at risk for health problems.

[0188] Changes in intraocular pressure: The frequency of eyelid closure and pupil response data are used to infer whether the intraocular pressure is abnormally elevated. Elevated intraocular pressure may be a sign of eye fatigue or underlying health problems.

[0189] Fatigue level assessment

[0190] Mild fatigue: If the blinking frequency drops to 5-10 times per minute and the eyelid closure C(t) is between 30% and 50%, the system determines it as mild fatigue. At this time, the mask will display a yellow warning icon through the OLED display and emit intermittent beeps to remind miners to rest.

[0191] Moderate fatigue: If the blinking frequency is less than 5 times per minute and the eyelid closure C(t) exceeds 50%, the system determines it as moderate fatigue. At this time, the mask will automatically increase the air volume of the air filtration system (increase by 20%), and display a yellow warning icon through the OLED display, and the buzzer will emit a 2kHz intermittent reminder sound.

[0192] Severe fatigue: If the blinking frequency is extremely low (less than 2 times per minute) and the eyelid closure C(t) exceeds 70%, the system will determine it as severe fatigue. At this time, the mask will trigger the emergency braking protocol, send the GPS coordinates to the dispatch center through the communication module, start the backup power supply forcibly, and activate the mask positioning flash mark.

[0193] Identification of potential health problems

[0194] Blurred vision or dry eyes: If the system detects a significant decrease in blinking frequency and an increase in eyelid closure, it may indicate that the miner is experiencing blurred vision or dry eyes. At this time, the system will remind the miner to pay attention to eye health through the OLED display and recommend eye rest or use of eye drops.

[0195] Abnormal increase in intraocular pressure: If the eyelid closure frequency and pupil response data indicate abnormal increase in intraocular pressure, the system will issue an emergency alarm to remind miners of possible eye health risks (such as glaucoma) and recommend immediate medical examination.

[0196] When abnormal eye data is detected, the smart dust mask will analyze and process the data through a built-in algorithm.

[0197] For example, if the system detects that a miner's intraocular pressure is abnormally high or the blinking frequency is abnormal, the system will immediately sound an alarm. This data will not only be prompted on the mask, but also uploaded to the background monitoring system in real time through wireless transmission, with detailed eye health data, for further evaluation and feedback by remote monitoring personnel or on-site managers.

[0198] Through the background monitoring system, managers can obtain the eye health status of miners at work and take necessary preventive measures or intervene in time. In addition, if the eye monitoring device of the mask fails, the system will automatically identify and send a fault notification, reminding maintenance personnel to inspect or replace the equipment in time to ensure that the equipment is always in good working condition, thereby avoiding potential threats to the health and safety of miners.

[0199] One of the core functions of the smart dust mask worn by miners is to monitor the movements and postures of the miners' heads, including head movements such as bowing and shaking. Through sophisticated sensors and algorithms, the smart mask can effectively capture and analyze these head movement data, providing more comprehensive monitoring support for mine management.

[0200] Specifically, the built-in accelerometers, gyroscopes and other sensors in the smart dust mask can monitor the movement changes of the miners' heads in real time. For example, the system can identify whether the miners frequently lower their heads, shake their heads, or have abnormal behaviors such as sudden and violent head shaking. These head movement data can reflect the miners' working status, such as fatigue, lack of concentration, and even possible risk of head injury.

[0201] When the system detects abnormal head movements, such as frequent bowing or shaking of the miner's head, which may be due to fatigue caused by long hours of work, or the miner encounters some kind of discomfort, the smart mask will immediately analyze the data. If these abnormal movements exceed the preset safety threshold, the system will trigger an alarm and transmit the data to the background monitoring system in real time via the wireless network. At this time, the background management personnel can quickly receive warnings, timely evaluate the miner's status, and determine whether intervention measures are needed.

[0202] Method for determining safety threshold

[0203] 1. Individual baseline calibration

[0204] Initial data collection: When a miner wears the mask for the first time, the system automatically records 10 minutes of physiological and posture data (such as pitch angle, acceleration amplitude, angular velocity variance, etc.) to establish an individual behavior baseline.

[0205] Threshold calculation formula: θ threshold =μ θ -2σ θ

[0206] μ θ : Mean pitch angle (head-down angle) during baseline period.

[0207] σ θ : Standard deviation of the pitch angle during the baseline period.

[0208] Laboratory and field testing verification

[0209] Setting empirical thresholds: By simulating the fatigue state of miners in the laboratory and combining actual field data, we can determine the general safety threshold:

[0210] Pitch angle threshold: Head down more than -20° (covering the normal range for most miners).

[0211] Movement amplitude threshold: dynamic acceleration <0.2g (values ​​below this are considered bradykinesia).

[0212] Angular velocity variance threshold: Angular velocity variance>50deg 2 / s 2 (Indicates abnormal shaking).

[0213] Safety margin design: retain a 10%-20% safety margin when setting the threshold to avoid false alarms due to individual differences or environmental interference.

[0214] The background monitoring system can not only receive head movement data from the smart mask, but also conduct a comprehensive analysis of this data with other physiological data of the miners (such as heart rate, breathing rate, etc.). Through big data analysis, managers can have a more comprehensive understanding of the health status of miners and make timely warnings of potential risks. For example, if a miner frequently shakes his head during work, accompanied by physiological changes such as increased heart rate or rapid breathing, the system will analyze the health risks that the miner may face based on these multi-dimensional data, and issue an emergency notice, recommending immediate rest or medical intervention measures.

[0215] In addition, if the monitoring equipment of the smart mask fails, the system will automatically identify and issue a fault alarm, and promptly notify maintenance personnel to conduct inspections and repairs, ensuring that miners are always in a good safety monitoring state. This real-time feedback mechanism of smart equipment has greatly enhanced the miners' sense of security in harsh working environments and reduced potential health risks.

[0216] Example:

[0217] The smart dust mask is a device that integrates multiple advanced technologies and is designed to provide all-round safety protection for miners. Its external structure design is centered on the dust filtration system, and its internal structure includes multiple high-precision sensor modules, battery and power management systems, and data processing and feedback systems. The functions of each part work together to ensure that miners can monitor their health status in real time in high-risk environments and take immediate countermeasures when abnormalities occur.

[0218] External structure: dust filter system

[0219] The external structure of the smart dust mask is designed with the miners’ respiratory protection in mind. The mask’s dust filter system uses highly efficient filter materials that can effectively filter harmful dust, toxic gases and harmful particles in the air, protecting miners from the effects of polluted air in their working environment. The system can automatically adjust the airflow and filtering effect according to changes in the environment, ensuring that miners can still get fresh air during long hours of work, reducing the risk of lung diseases and other respiratory problems.

[0220] Internal structure: sensor module, battery and power management

[0221] The sensor module is the core component of the smart dust mask and is responsible for real-time monitoring of the miner's physiological status. The module includes multiple sensors, which are used to monitor different physiological indicators:

[0222] Physiological sensors: These sensors mainly monitor important physiological data of miners, such as heart rate, respiratory rate, body temperature, etc. Changes in heart rate and respiratory rate can reflect the miners' physical load, fatigue level and potential health risks. By accurately measuring these data, the system can determine whether the miners are in an overloaded working state, or whether they have symptoms such as shortness of breath and abnormal heart rate, so as to provide early warning and avoid the occurrence of health problems.

[0223] Eye sensor: Eye sensors are used to monitor the eye movement of miners, including frequent eye blinking, pupil reaction, etc. These data can help determine whether miners have eye fatigue, blurred vision and other problems, especially when working for long hours, in poor ambient light or in the presence of air pollution. Eye fatigue is an important factor that causes miners to lose concentration and react slowly. By monitoring eye movement data, smart masks can effectively avoid the resulting safety hazards.

[0224] Posture sensor: Posture sensors are used to monitor miners' head movements, including bowing and shaking. These movements can reflect miners' fatigue or lack of concentration. For example, frequent bowing or shaking of the head may mean that the miner is extremely tired or at risk of head injury. By monitoring these posture changes, the smart mask can detect potential dangers in time and issue an alarm.

[0225] The battery and power management system ensures the stable operation of the smart dust mask during long-term work. The system is designed with high-efficiency batteries and adopts intelligent power management solutions to automatically adjust power distribution to ensure that the energy requirements of each module are met during work, while extending the battery life. The battery system also supports fast charging and long-term use. Even in harsh mining environments, miners do not need to frequently replace batteries, reducing maintenance costs and inconvenience.

[0226] Data processing module: signal processing and fatigue state analysis

[0227] The built-in data processing module of the smart dust mask is responsible for real-time processing and analysis of the data collected by all sensors. This module is mainly divided into two parts:

[0228] Signal processing: The raw data collected by the sensor will be pre-processed and filtered through the signal processing module to remove noise and interference to ensure the accuracy and reliability of the data. Signal processing includes efficient processing of heart rate, breathing rate, eye movement and posture data to provide accurate input for subsequent analysis.

[0229] Fatigue status analysis: This module uses algorithms to analyze the miners' physiological data, especially fatigue-related indicators (heart rate, respiratory rate, eye movement and head movement, etc.), to determine the miners' fatigue status. By comparing the miners' real-time data with the normal range, the system can assess the miners' fatigue level. If the fatigue status exceeds the safety threshold, the system will automatically sound an alarm to remind the miners to rest or make other necessary interventions.

[0230] Display and feedback system: wireless communication and real-time monitoring

[0231] The display and feedback system is responsible for delivering the processing results to the miners in the form of visual or auditory feedback, and uploading the data to the background monitoring system through the wireless communication module. Specifically, the system feedback can be divided into the following ways:

[0232] Feedback from miners: When a miner's physiological state is abnormal, the smart dust mask will provide feedback through the display or sound alarm. For miners, timely feedback means they can quickly identify their physical condition and avoid overwork or health problems. For example, the mask will sound an alarm when the heart rate is too high, or remind miners to rest through the display inside the mask.

[0233] Backstage monitoring system: All collected data will be transmitted to the backstage monitoring system through the wireless communication module. System managers can view the miners' physiological status, posture data and fatigue status in real time through the backstage platform, and conduct remote monitoring and intervention. If the backstage system finds that the miners' status is at risk, managers can take timely measures, such as arranging miners to rest, change positions or conduct health checks.

[0234] Through the wireless communication module, the system can also be linked with other intelligent devices, such as environmental monitoring systems, construction site security systems, etc., to further improve the overall safety of mining operations.

[0235] The smart dust mask integrates dust filtration systems, physiological monitoring sensors, data processing modules and wireless communication technology to build a comprehensive miner health and safety monitoring platform. It can not only effectively protect miners from harmful gases and dust, but also monitor their physiological data and behavior status in real time, detect potential health risks in a timely manner through intelligent analysis, and provide feedback through wireless communication systems to ensure the safety of miners at work. In high-risk environments such as mines, the application of smart dust masks has undoubtedly greatly improved the safety level of miners.

[0236] The present invention integrates multiple sensors (physiological signal sensors, eye monitoring sensors, posture sensors) to conduct multi-dimensional and comprehensive monitoring of the miners' fatigue status. This multi-level monitoring method is more accurate than a single sensor monitoring system and can fully capture the miners' fatigue symptoms.

[0237] Physiological signal sensors monitor miners’ heart rate, breathing rate and other physiological data.

[0238] Eye monitoring sensors detect the miners’ eye status, especially eye closure, as a sign of fatigue.

[0239] The posture sensor determines the miner's fatigue level by monitoring the movement of the miner's head (bowing, shaking).

[0240] Real-time data processing and feedback mechanism, through the integrated control module, the mask can process the data collected by the sensor in real time, and analyze it according to the preset algorithm to determine whether the miner is in a state of fatigue. If a fatigue signal is detected, the control module will issue a warning to the miner through the display or communication module, and transmit the data to the external monitoring system in real time.

[0241] Data collection and preprocessing, fatigue motion feature extraction, multi-dimensional data fusion and fatigue level assessment have been given above

[0242] Feedback from miners:

[0243] Display feedback: The OLED display on the outside of the mask displays real-time fatigue status (such as "fatigue warning") and key data such as heart rate and breathing rate.

[0244] Sound and vibration feedback: When mild fatigue is detected, the buzzer emits intermittent reminder sounds; when severe fatigue is detected, the buzzer sounds continuously and triggers the mask to vibrate.

[0245] Remote communication and monitoring:

[0246] Data transmission: Upload fatigue status and sensor data to the background monitoring system in real time via Bluetooth or Wi-Fi module.

[0247] Emergency braking protocol: When severe fatigue is detected, the system sends the GPS coordinates to the dispatch center through the communication module, starts the backup power supply forcibly, and activates the mask positioning flash mark.

[0248] The display system is used to provide direct feedback to individual miners, reminding them to take a break or take action.

[0249] The wireless communication module uploads real-time data to the background monitoring system for external managers to monitor.

[0250] Battery management and system stability. The mask's built-in efficient battery management system ensures the stability of the mask during long-term work, extends the usage time, and effectively manages the battery's charging and discharging status to avoid device failure due to power exhaustion.

[0251] The battery management system uses high-energy-density lithium batteries, combined with an efficient power management module, to monitor the battery's charge and discharge status in real time.

[0252] When the battery power is below 20%, the system automatically reduces the sensor sampling frequency to extend battery life.

[0253] Low power design:

[0254] When the miner is stationary (such as the acceleration amplitude is less than 0.1g for 5 seconds), the system automatically enters low-power mode and only maintains basic monitoring functions.

Claims

1. An intelligent dust mask capable of monitoring the fatigue status of miners in real time, characterized in that: Including physiological signal sensors, eye monitoring sensors, posture sensors, display and communication systems, communication modules, battery and power management, air filtration systems and control modules; The physiological signal sensor, eye monitoring sensor and posture sensor input the collected information into the control module, and the signal output end of the control module is connected to the display and communication system; The control module communicates with the communication module in a two-way manner, the control module sends data to the communication module, and the communication module transmits the received external instructions to the control module; The battery and power management are used to supply power to each module.

2. The intelligent dust mask capable of real-time monitoring of miners' fatigue status according to claim 1 is characterized in that: The physiological signal sensor is used to transmit physiological data in real time to analyze fatigue status; The physiological signal sensor includes a heart rate sensor and a breathing sensor; the physiological signal sensor is installed inside the embedded mask and contacts the facial area; The facial area is divided into a forehead contact area and both sides of the nose / cheeks. The forehead contact area is used to monitor heart rate and body temperature using integrated flexible electrodes or optical sensors. The nose / cheeks are used to detect breathing rate, using airflow or pressure difference sensors; The heart rate sensor and breathing sensor use photoelectric volume pulse wave sensors to monitor heart rate; the PPG sensor measures small changes in blood flow through the skin surface to obtain heart rate information, and the breathing rate is achieved by monitoring chest movement through an airflow sensor; The PPG sensor and ECG sensor are transmitted to the control unit through electric current, and then processed and output to the display module.

3. The intelligent dust mask capable of real-time monitoring of miners' fatigue status according to claim 1 is characterized in that: The eye monitoring sensor is used to monitor visual fatigue indicators such as blinking frequency and eyelid closure; The eye monitoring sensor is a camera or an infrared sensor; The eye monitoring sensor is located on the top of the inner side of the mask, near the brow bone area, just above the eyes; a miniature infrared camera or infrared sensor is aimed at both eyes to monitor blinking frequency and eyelid closure; The eye sensor uses infrared eye tracker opening and closing detection technology. The eye monitoring system irradiates the eye area with an infrared light source to detect eyelid movement or eyeball activity. The camera collects eye images and analyzes the opening and closing of the eyes through an image processing algorithm. Using infrared LEDs and photoelectric sensors combined with eye tracking technology, fatigue is monitored by calculating the degree of eye closure; real-time data is analyzed by an embedded processor and combined with other physiological parameters to determine whether miners are at risk of fatigue.

4. The intelligent dust mask capable of real-time monitoring of miners' fatigue status according to claim 3 is characterized in that: The specific image processing algorithm is: Step 1. Baseline calibration Eye opening baseline value I open : When the user opens his eyes and remains still, the average reflected light intensity is collected for 10 seconds; Eyes closed baseline value I close : The average intensity of reflected light when the user closes his eyes; Step 2. Real-time closure calculation Normalized reflection intensity: Step instantaneous closure C(t):

5. The intelligent dust mask capable of real-time monitoring of miners' fatigue status according to claim 1 is characterized in that: The posture sensor is used to detect motion signals of head tilt and abnormal body posture; The attitude sensor is located on the top of the mask. The attitude sensor integrates a three-axis accelerometer and a gyroscope to detect the tilt angle of the head; The accelerometer / gyroscope is used to detect the posture and movement of the miner's head. The three-axis accelerometer measures the movement changes of the head, and the gyroscope detects the rotation angle of the head. The combined use can provide complete posture monitoring data.

6. The intelligent dust mask capable of real-time monitoring of miners' fatigue status according to claim 5 is characterized in that: The fatigue status is determined based on: Step 1. Data collection and preprocessing Accelerometer data: measures the linear acceleration of the head in three axes, including gravity components and motion acceleration; Gravity separation: Separate dynamic motion acceleration through a high-pass filter to eliminate static gravity interference; Motion Amplitude Calculation: Using Acceleration Vector and Formula quantify the intensity of head movements; Gyroscope data: measures the angular velocity of the head around three axes; Angle integration: Integrate the angular velocity over time to get the head posture angle, which is used to determine the amplitude of lowering or raising the head; Step 2. Fatigue motion feature extraction Frequent head-down detection judgment basis: Pitch angle threshold: set the pitch angle exceeding -20° as a valid head-down action; Frequency threshold: If the number of times of lowering the head in a unit of time is ≥5 times, it is judged as "frequent lowering of the head"; Slow head movement detection is based on: Acceleration amplitude threshold: When the dynamic acceleration amplitude is <0.2g, it is considered as slow head movement; Duration threshold: If the slow state lasts for >30 seconds, it is judged as "bradykinesia"; Abnormal shaking detection judgment basis: Gyroscope angular velocity variance: Calculate the variance of the angular velocity. If the variance is > 50deg2 / s2, it means that the head is shaking irregularly. Combined with accelerometer data: if the acceleration amplitude during shaking is >1.5g, it is judged as "abnormal shaking"; Step 3. Multi-dimensional data fusion and fatigue level assessment The weight distribution is divided into frequent head bowing, slow movement, and abnormal shaking; Fatigue index = (low-frequency head bowing score × 0.4) + (slow movement score × 0.3) + (abnormal shaking score × 0.3); Classification alarm: Mild fatigue (index ≥ 60): triggers a voice prompt and recommends a short rest; Severe fatigue (index ≥ 85): trigger a strong vibration alarm and upload data to the monitoring center; Step 4. Anti-interference and adaptive optimization Dynamic threshold adjustment: Based on the individual differences of miners, a 10-minute baseline calibration is performed during initial use to automatically adjust the pitch angle threshold and acceleration amplitude threshold; Noise Filtering: The acceleration data were smoothed using the sliding window averaging method; Optimize gyroscope angle integration using Kalman filter; Step 5. Real-time performance and low power consumption guarantee Sampling frequency: The sensor data sampling rate is set to 50Hz to balance accuracy and power consumption; Sleep strategy: If there is no significant movement, the sensor enters low-power mode and only maintains basic monitoring.

7. The intelligent dust mask capable of real-time monitoring of miners' fatigue status according to claim 1 is characterized in that: The control module is responsible for receiving data from sensors and performing real-time analysis, judging the fatigue status of miners according to the set algorithm, and issuing warnings through display screens or sending alarms through wireless communication. It uses efficient embedded systems for data processing and decision-making. The control module must have the functions of real-time data collection, analysis and feedback, process data from various sensors and respond in real time; The control module is a microprocessor / embedded system; The input of the control module is used to receive all sensor data and perform fusion analysis; The output side of the control module sends instructions to the display system, communication module, and air filtration system according to the algorithm results. The control module is set behind the bridge of the nose in the center of the inner side of the mask; The control module includes a main control chip and a storage unit. The main control chip is an embedded microprocessor responsible for data fusion and decision-making; The storage unit is adjacent to the main control chip and caches sensor data.

8. The intelligent dust mask capable of real-time monitoring of miners' fatigue status according to claim 7 is characterized in that: Specifically: Step 1. Sensor data preprocessing Accelerometer data filtering: The acceleration data were smoothed using the sliding window averaging method; Gyroscope angle integration: Integrate the angular velocity ω over time to calculate the pitch angle θ: θ[t]=θ[t-1]+ω y [t]·Δt Among them, ω y is the pitch axis angular velocity, Δt = 0.02s; Step 2. Feature extraction and fatigue determination Frequent head-down detection judgment formula: Pitch angle threshold: If θ<-20°, it is recorded as a valid head-down action. Frequency threshold: If the number of times of lowering the head within 10 minutes is ≥5, it is judged as fatigue; Slow head movement detection Dynamic acceleration calculation: Among them, g x , g y , g z is the gravity component, separated by high-pass filtering; Judgment formula: If A dynamic <0.2g for >30 seconds was considered bradykinesia; Abnormal shaking detection Angular velocity variance calculation: Judgment formula: If σ 2 >50deg 2 / s 2 And A dynamic >1.5g, considered as abnormal shaking; Step 3. Multi-sensor data fusion and fatigue index calculation Weight distribution: divided into physiological signals, eye monitoring and posture data; Fatigue Index formula: Fatigue Index = 0.3·S physio +0.3·S eye +0.4·S posture ; Hierarchical alarm strategy: Mild fatigue: the OLED screen displays a yellow warning and the buzzer sounds briefly; Severe fatigue: triggers a red alarm, continuous beeping, and uploads an emergency signal to the monitoring center via Wi-Fi.

9. The intelligent dust mask capable of real-time monitoring of miners' fatigue status according to claim 1 is characterized in that: The display and communication system directly receives instructions and displays real-time status or triggers an alarm; The display and communication system is mounted on the outer forehead area of ​​the mask, and the micro transparent OLED display is mounted on the outer side of the forehead and is visible to the wearer; The vibration motor or LED warning light is installed near the side ear; The communication module uploads the fatigue status and sensor data to an external device; The communication module is installed on the top of the mask and is a Wi-Fi / Bluetooth / LoRa antenna; When moderate fatigue is detected: the air filtration system automatically increases the air volume, the OLED displays a yellow warning icon, and the buzzer emits an intermittent reminder sound; In severe fatigue state: trigger the emergency braking protocol, start the backup power supply forcibly, and activate the mask positioning flash mark; The battery and the power supply side of the power management provide power to all electronic modules; The management side of the battery and power management is used to monitor the battery power, feedback low-battery warnings through the control module, and optimize energy consumption distribution.

10. The intelligent dust mask capable of real-time monitoring of miners' fatigue status according to claim 1, characterized in that: The air filtration system is used to receive instructions from the control module, and the air filtration system is installed at the lower front part of the mask; The air filtration system uses a small HEPA filter or an activated carbon filter; The HEPA filter is installed at the air inlet on the front of the mask, and the activated carbon layer is located at the rear end of the filter; the micro centrifugal fan is embedded on both sides of the mask to drive the external air into the breathing chamber through the filter; An outlet valve is set on the HEPA filter. The outlet valve is a one-way exhaust valve on both sides to discharge carbon dioxide and maintain the balance of breathing resistance.

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