SCI - Model 608 - Criteria Pollutant Sensor Monitor
From Air Quality Monitor
SCI’s sensor division incorporates state of the art sensor technology that has been enhanced with a machine learning calibration system and convenient cloud-based data acquisition platform. SCI sensor products merge with the Internet of Things (IoT), digital electronics, machine learning, and data visualization technologies to deliver precise air quality and meteorological data in real-time. Our sensor products have been used in fenceline/community monitoring, pollution source screening, wildfire/smoke monitoring, and smart city projects.
SCI-608 – Criteria Pollutant Monitoring is a low-cost air quality monitoring solution designed for accurate highly time-resolved measurement of criteria pollutant levels. The SCI-608 – Criteria Pollutant Monitoring utilizes state of the art sensor technology enhanced with a machine learning calibration system and a convenient cloud-based data acquisition and visualization system. The monitor has been extensively field-tested, is easy to install, and can provide the user with real-time data within minutes of setting up.
- Solar Power/Wall AC Power
- Easy to deploy
- Wide range: ng/dscm to mg/dscm
- Dispersive sampling
- Global communication module
- Real Time Alternative for Samplers
- Smart Cities
- Pollution Source Identification and Locating
- Traffic Pollution Monitoring
- Industrial Fence Line Monitoring
- Emergency Monitoring
- Air Quality Model Validation
- Community Based Monitoring
- Pollution Migration Mapping
- Power Supply: DC 12V, Solar
- Power Consumption: Less than 3 watts
- Operating Temperature Range: -20 to 55 ºC
- Atmospheric Pressure: 645 to 795 mmHg
- Relative Humidity: 15 to 90%
- Communication: GPRS (2G/3G/4G), RS232
- Size: 220 x 220 x 300 mm
- Weight: 2.6 kg (5.75 lbs)
- Software: Cloud: For instrument and data management. Runs on secure severs accessed via web browser
- Mounting: Pole Mounting Bracket Included
SCI 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 recalibrated 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 mobile instruments.
SCI sensors have demonstrated excellent correlation with reference method sensors with corelation coefficients as folows: CO = 0.97, NO2 = 0.93, O3 = 0.975, SO2 = 0.89, PM2.5 = 0.96, PM10 = 0.8
SCI sensor data is uploaded to the cloud and data can be visualized using a number of useful graphics that turn sensor data into useful information. Data can be accessed via the internet or with an app on your mobile device.