R-NOX Air Quality Monitoring System
Full stack service that provides accurate environmental data, analytics,predictions, reporting.
It includes low-cost sensor network and cloud-based platform for real-time analytics of air quality in the sanitary protection zone, fugitive emissions, gas leaks.
Do you face with:
- Frequent Citizens complaints?
- High environmental taxes?
- Heavy fines?
- High costs of traditional monitoring?
We have solution —
R-NOX Monitoring System
low-cost sensor network for constant air quality monitoring
- Real-time monitoring of CO, NO2, SO2, O3, PM1, PM2.5, PM10 (can be expanded with other sensors);
- Automatic data acquisition, validation and reporting;
- Analytics and visualisation of received data (real-time dashboards);
- Prediction of high-risk situations;
- Fast detection, provides alarms at given limit levels;
- Remote devices control and callibration.
Cloud-based platform for real-time analytics processing.
- Simultaneous data collection from multiple locations;
- Real time measurement results;
- Emission differention from nearby pollution sources;
- Air pollution dispersion modelling;
- High-risk situation forecasting;
- Suggestions for emission optimization.
Why R-NOX Air Monitoring System?
measurements and reports are made automatically
monitors are deployed in large numbers across the factory and generate more accurate data
cost effective solution, low operating and maintenance costs
real time analytical dashboard can be customized for your needs
frequent maintenance is not required
SENSORS LONG LIFETIME
- Relationship with citizens/government improvement
- Environmental taxes reduction
- Heavy penalties avoiding
- Money saving
- Automated reporting
- Disputable situation avoiding
- High-risk situations forecasting
Provide citizens and government with accurate and accessible data 24/7.
The tax may be reduced by the amount of capital investments that have been disbursed.
Real-time analytics help to control emission and allows to avoid incidents before they occur.
Need for costly gas sampling equipment can be removed.
Environmental engineer’s workload can be reduced.
Emission can be differentiated from nearby pollution sources.
Air pollution diffusion on nearby communities can be prevented by predictive modelling.