SCI -801 is a professional micro-instrumentation, which can online monitor TVOC, temperature, and humidity in the atmospheric environment. With wireless communication technology, a large number of sensor nodes can communicate with servers securely and send large environmental data to the cloud platform. Conventional Air Quality Monitoring System does not cover most places of cities/ towns and cannot accurately represent where the pollution is coming from since it is costly.
Benefits
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Customization on specification according to customer requirement. (808, 804, 801)
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Auto data information recording every five minutes, real time update on monitoring network.
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Smart mode switch for solar panel ensures one month continuous performance without sunshine.
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Double filtration system gives the sensors a longer life-time.
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Active risk control system reports and records any abnormal data and then sends it through a message delivery system to the end user for reminding.
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No operating condition requirement, no shelter required.
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Independent different module assembled, which makes maintenance easier.
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Auto monitoring network system upgrading from cloud.
Measurement Performance
Model
SCI-801
SCI-801 parameter
TVOC, Temp, RH
Time Resolution
10s
Power
Municipality (220V), Solar Panel (12V)
Dimension
220*220*300 (mm)
Operating Condition
T(-20-55) ℃, RH(0%-95%)
Communication Mode
GPRS
Battery
Lead acid storage battery
Operating Length
One month without any power supply
Weight
2.4Kg (5.3lb)
Storage Condition
-40℃-55℃,
Sensor Quality Control
Sailbri Cooper’s sensor instruments have a rigorous three stage quality assurance and calibration process. In the first stage each individual sensor is challenged with standard gases to screen out low performing sensors. The second stage involves generating calibration files unique to each sensor unit using a custom machine learning algorithm and the sensor’s response to complex pollutant mixtures, varying temperature and varying humidity in a controlled test chamber. Once in the field, sensors can be periodically re-calibrated with neural networking algorithms to improve sensor response to complex ambient conditions. This cloud-based calibration can be done automatically during field deployment using existing reference method monitors or with portable instruments.
