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BACKGROUND
Due to the outbreak of the epidemic, people's personal protection awareness has been strengthened unprecedentedly, and various masks have entered life. Masks have become essential daily necessities in life.
At the same time, new problems also arise during the long-term use of masks, such as poor ventilation and ventilation of masks, different wearing requirements in different places, wearing comfort, and so on. In order to achieve a good filtering effect, the mesh of the filter mesh is very small, and wearing it for a long time can easily cause breathing difficulties, hypoxia, and chest tightness. Recently, there have even been cases of suffocation due to wearing masks for outdoor sports.
The use of disposable masks is huge and cannot be recycled. With the outbreak of the COVD-19, masks have become a new source of pollution. A new type of marine debris, a mask, was also discovered in a recent marine cleaning activity.
The current masks have a single function, only the protection has no perception ability. After a long period of wear, the protective ability decreases, and the human body cannot perceive the concentration information of harmful substances in the environment. Blindly staying in the area contaminated by harmful substances for a long time, and finally causing the human body to inhale the harmful substances.
Through the background introduction, it can be concluded that a new type of intelligent mask that can independently control the opening and closing filter according to different scenarios, can be reused and self-disinfecting and cleaning, can detect environmental information and judge the active protection of the risk index is necessary.
PROJECT
This project has designed a new type of smart mask that takes into account both the breathability of the wear and the filtering effect. It can intelligently evaluate the risk index of the current environment and realize the automatic opening and closing of the filter. To achieve smooth breathing in a safe environment, reduce the number of times the hand touches the mask, and reduce the risk of infection. According to the infrared temperature measurement module, air quality sensor, temperature and humidity sensor, and camera, etc., including the front target temperature, environmental CO2 concentration, VOCs index of organic pollutants, environmental temperature and humidity data, crowd aggregation in the field of view, the proportion of people wearing masks for synthesis Estimate the current danger index, and use it as an indicator to control the opening and closing of the valve partition of the micro steering gear to realize the opening and closing of the mask. The self-disinfection of the mask is realized by the ultraviolet lamp inside when the mask is not suitable. And communicate with the mobile phone APP through the Bluetooth protocol, present data to the user also issue an alarm under the necessary environment.
SOLUTION
The system design is divided into two parts, consisting of the mask body and supporting mobile phone APP.
The main part of the mask includes: K210 main control development board for mask detection and logic control main control part, reading each sensor data and executing instructions sent by APP; BLE low energy Bluetooth module (nRF52810) is used for mask theme and mobile phone APP information communication; LED indicator light is used to indicate the current danger index and Bluetooth connection; ultraviolet UVLED is used for internal self-disinfection; OV2640 camera is used to obtain the front view image; micro steering gear is used to control the opening and closing state of the mask ventilation valve partition ; TCH233B touch module is used to manually open and close the partition sensor; GY906IR infrared temperature measurement module is used to measure the temperature of the target in front; CCS811 carbon dioxide & volatile organic compound sensor detects the CO2 concentration and organic pollutant index in the environment; HDC1080 temperature and humidity sensor Used to detect temperature and humidity information in the environment.
The mobile phone APP contains functions such as presenting detection data, setting modes, controlling partitions, and danger alarm reminders.
The mask-wearing target detection uses the Yolo2 tiny neural network model to calculate the total number of people in the field of view, as well as the number of people wearing masks and the number of people wearing no masks. The neural network model is trained by open-source datasets.
The shell structure of the mask adopts a layered design, the front end is a vent, and the steering gear controls the partition to rotate to open and close the ventilation valve. The housing has a sunken recess and is composed of an upwardly protruding cover plate. Space allows the ambient air to contact the outside sensor so that the sensor does not need to be completely exposed, which effectively prevents liquid splashing from damaging the sensor.
There are many factors that affect the ability of virus transmission, including but not limited to the degree of personnel gathering, the proportion of people wearing masks, the temperature and humidity of the environment, etc. In order to more intuitively understand the safety level of the current user environment, determine whether it is easy to infect the virus, and choose protective measures, we inferred the formula for calculating the virus transmission risk level based on the direct quantitative relationship between the various factors listed above and the virus transmission ability . We divided the virus transmission level into ten levels, representing different levels of virus transmission risk.
Hazard level = CO2 factor + population factor + temperature factor + humidity factor
CO2 factor=1 (CO2 concentration 350ppm-450ppm)
=2 (CO2 concentration 450ppm-1000ppm)
=3 (CO2 concentration>=1000ppm)
Number factor=0 (total number<=3)
= Percentage of people without mask*2 (total number of 3-6 people)
= Percentage of people without masks* 5 (total number of people above 6)
Temperature factor=1 (5-20 degrees)
=0.5 (20-30 degrees)
=0.1 (30 degrees -40 degrees)
=0 (above 40 degrees)
Humidity factor = 0.7 (humidity return value 0-0.23)
=1 (humidity return value 0.23-0.3)
=0.5 (return value of humidity 0.3-0.4)
=0 (humidity return value above 0.4)
MAKING
Perform a functional experimental test on the work, the test results are as follows:
① Realize the detection of crowd information target in front view, obtain the number of people and wear masks
② Realize the acquisition of environmental information through multi-sensors and calculate the risk index in the current environment to independently control the opening and closing of the steering gear to realize the opening and closing of the ventilation valve
③ Realize the functions of Bluetooth communication, data transmission, order issuing, alarm reminding, etc. between the mask body and mobile phone APP
④ Can open and close the partition manually
⑤ Sterilize the inside ultraviolet lamp while charging
The smart mask can judge the status of the mask and the number of people in the current field of view through the camera to achieve the function of automatically closing the mask ventilation valve in a crowded situation, so that the mask ventilation valve automatically opens when there are few people in an open place .
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