Many cities around the world suffer periodic outbreaks of poor air quality caused by consumer and industrial action exacerbated by climatic conditions. Early detection of the precise type of air pollutants can help air quality boards to intervene and prevent health issues, eventually benefiting an entire community or population. Detection of chemical levels through sensors is challenged by the complex interaction between chemical sensor response, humidity, temperature, and molecular concentrations. Despite the complexity, definitive patterns exist between these variables. The challenge is cost-effectively recognizing and detecting these patterns.
A chemical sensor manufacturer/service provider collects time series data from deployed sensors. The data, composed of multiple time series values like molecular concentration, temperature, humidity, etc. are communicated to Azure IoT Hub. In addition to storing sensor measurements, Customer is also applying manually created rules using Azure Stream Analytics. Results are stored in Azure Storage Blocks, which are accessed using Azure Web Apps.
Using Falkonry’s integration with Azure IoT Suite, chemical sensor data is forwarded to Falkonry from the IoT Hub. Falkonry develops a cognitive model of patterns in the sensor data indicative of different chemicals such as VOC, NOx, CO, particulate matter, and Ozone. These models are applied to incoming streams from IoT Hub, and the results are placed in the Event Hub to be stored in the Azure Block Storage, which can now be visualized using modified Azure Web Apps. Without the need for data scientists, data from existing sensors can now be used to quickly and accurately classify presence of air pollutants in multiple locations.
By using Falkonry, sensor manufacturers are able to build a library of classified sensor signal patterns. Falkonry receives continuous feeds of chemical sensor signal data and returns the sensed chemical name (classification) to the sensor application. Results from an array of such sensors are used to locate sources of chemicals, thus mitigating the health effects on entire city populations.