Indoor air quality in hospitals and other healthcare facilities has been a hot topic for decades. To monitor the air quality in a room is easy, but to monitor it in a large building with many rooms is quite complex. Negative health effects of waste hospital gases such as carbon dioxide, carbon monoxide, harmful gases and vaporized disinfectants (formaldehyde, ethylene oxide) are widely known. Hospitals and health care facilities have a unique collection of potentially risky compounds, which in turn increases the pressure to monitor and control air quality in these facilities. Each of the above contaminants can have a negative impact on health, depending on the length of exposure, the level of contaminants, and other factors. Indoor air quality monitoring can also reveal the presence of pollutants that you do not know, leading to new mitigation strategies. Temperature and humidity are two other characteristics of hospital indoor air quality that directly affect patient comfort and thus patient satisfaction.
Most hospitals do their best to implement management policies and procedures that help manage and mitigate indoor pollutants, but employ advanced technology to help proactively identify air quality issues. IoT technology provides a cost-effective way to help hospitals meet indoor air quality standards. Like those used in other industries, the IoT gives you more control over your environment (in this case, especially indoor air quality) through remote monitoring. IoT sensors located in various areas of the facility can measure temperature, humidity, volatile organic compounds, dust particles, CO2, etc. in near real time. You can then analyze and interpret this data to create an action plan to restore healthy indoor air quality. The IoT remote monitoring system also acts as an automatic tracking / logging system for vaccine storage areas, facilitating compliance with CDC guidelines. IOT Based Air Pollution Monitoring System monitors the Air quality over a web server (AWS) using Internet and will trigger an alarm when the air quality goes down beyond a certain threshold level, means when there are sufficient amount of harmful gases present in the air like CO2, CO, smoke, alcohol, NH3, sulfide, and benzene. When the microcontroller reaches the maximum limit of temperature, humidity, oxygen, dust, and chemical gases with a predetermined value, the buzzer will sound. All data will be stored in the fog and cloud then if a problem occurs outside the specified conditions, in addition to the buzzer sounding, there will be an incoming massage to telegram as a notification. The system will show temperature and humidity. The system can be installed anywhere in hospital.
Figure 1. Writing Diagram
In the picture above is a plan of the tool to be made where the tool consists of: ESP32 Microcontroller, Humidity Sensor, PM2.5 Sensor (GP2Y1014AU0F), MQ135 Sensor, Buzzer, Adapter, Cable Jumper, Protoboard and Box. After planning, the next step is assembling and configuring sensors and equipment and packing them in a box which will make it easier if we want to move the tool. As seen in the image below.
Figure 2. Sensor Box Packing
After each component is declared to work, then the connection to the FOG is carried out. We use laptop as our FOG. And then connect to node-red server and XAMMP.
After that we try to connect to cloud service, we use Amazon Web Service as our cloud. We use EC2 service. For IoT class, we get this service for free, with 100$US limit. This is the step to setting up cloud service for our project.
Figure 3. testing on ESP32, sensor components and FOG
After that we try to connect to cloud service, we use Amazon Web Service as our cloud. We use EC2 service. For IoT class, we get this service for free, with 100$US limit. This is the step to setting up cloud service for our project.
Figure 4. The Cloud dashboard
If measurement value is out of range, notification will be sent to telegram by node-red (as fog). The obstacles we got when doing the experiment were incorrect sensor readings, components that didn't work anymore and when connecting to coding, there were several errors so we recoded
Figure 5. Telegram Notification
After doing this experiment, we were able to know that the need for air quality in the hospital was very important. All aspects must be considered so that the environment remains comfortable and healthy. This tool is very sensitive so it can be used anywhere. We also managed to solve existing problems such as the process of testing the tools one by one, coding, using github to creating our own website during the tool creation process.
The IoT system worked. It can store data to database in fog and cloud. The fog can send notification to telegram and turn on buzzer if the reading is out of range
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