Since the outbreak of the coronavirus pandemic, good ventilation is an important factor in preventing the virus. The biggest contributor to carbon dioxide in an indoor space is people exhaling. Higher levels of CO2 in a building are an indicator of poor ventilation which increases the risk of the virus spreading and causes a variety of health issues. Hence real-time monitoring of CO2 level helps decide if ventilation is poor and keep good air quality. To fight with COVID-19, Milesight offers a LoRaWAN® indoor air quality monitoring solution.
Schools at different educational stages may run into the same problem of creating a better and safer indoor ambience for students and teachers. Milesight is confident to provide certain solutions to address these challenges.
Students tend to be more mobile throughout the day and much of the day is spent near or on the floor. Young students in these classrooms are also less likely to follow rules regarding face masks, hand hygiene and physical distancing. To encourage preventive behaviors, teachers can increase the frequency of classroom ventilation.
The lower grade students need enough fresh air that must be provided to achieve a daily average concentration of CO2 during occupied core hours. The controlled ventilation system is having a significant effect on the overall performance of the classroom environments.
The recommended ventilation should be provided to limit the concentration of carbon dioxide in all teaching and learning spaces. These heavily populated environments mean high school students are exposed and vulnerable to air pullutants much more so than when outdoors. Most importantly, then can suffer prolonged exposure to high levels of CO2 and increasing the risk of cathing the COVID-19.
CO2 is the primary indicator of indoor air quality(IAQ) and high concentrations are a tell-tale sign that stale air is not being replaced quickly enough in relation to the occupancy levels of the room. The ventilation monitoring has always been considered as a difficulty to tackle. The LoRaWAN® indoor air quality monitoring solution is cater to help improve classroom ventilation and protect college students from this infectious disease.
The COVID-19 solution consists of hardware and software, including end nodes, gateway and cloud platform. Place a UG65 LoRaWAN® Gateway at the top of the building to set up a LoRaWAN® network, covering the whole school; place an AM107 ambiance monitoring sensor in each classroom to detect CO2 level; connect UC1114 LoRaWAN® controller with control the panel of ventilator fans to uses relay out to turn on/of them. Milesight IoT Cloud offers remote monitoring, alert and auto control.
COVID-19 Solution Scenario: Clean Air Auto Control
CO2 concentrations above 1000 ppm are likely to cause feelings of discomfort, such as fatigue, loss of concentration or headaches. Concentrations above 750 ppm are likely to cause stiffness and odors. For the sake of students and teachers, once AM107 detects that the concentrations are above 700 ppm, Milesight IoT Cloud will automatically turn on the ventilation fan and turn off the fan after concentrations fall back to 500 ppm, keeping air quality in proper condition and saving energy.
Solution Scenario: Extra Applications
AM107 ambiance monitoring sensor consists of multiple smart sensors that detect temperature, humidity, motion (PIR), light, CO2, TVOC and barometric pressure. Combined with the smart trigger system of Milesight IoT Cloud, UC1114 can smartly use relay out to turn on/of equipment like light bulbs, ventilators and air conditioners. In conclusion, the solution can also be used for smart air comfort control, smart lighting, room occupancy monitoring, and so on.
COVID-19 Solution Benefits
1. Turnkey Solution
Includes end nodes, gateway and cloud platform
2. Real-Time Monitoring, Alert and Control
Get alert and auto ventilation to keep good IAQ
3. Reduce Risk and Improve Air Quality
Reduce concentrations of virus, pollen, dust and VOCs
4. High Network Capacity
One gateway covers a 2km radius area, supporting up to 2000 sensors