Our client in the environmental industry works with regularly checking the air quality, and providing the data to other agencies responsible for air pollution. A key to its success is the valuable and prompt data gathered from the sensors and the proper display of the same. To provide even better insights, our client decided to implement a solution that will process big data retrieved from a number of sensors and produce and improve the insights from the air quality statistics measures.
The main goal of the effort was to create an application for processing and analyzing specific parameters and particles present in the air, including the presence of PM10 particles and other compounds.
We have created a solution for this module in Python programming language and we have used the power of Apache Spark in order to tame the data.
⋮IWConnect delivered a cost-effective and robust solution that optimally performs processing and analysis of the big data using Apache Spark, along with statistical calculations needed for analysis.
On the whole, the solution provided enabled the client to make the collection, process and analysis of data more efficient. This, in turn, enhances the experience of the agencies receiving the data.
Complex analyses of air pollution factors of the governmental agencies, non-profit organizations and other groups and individuals for mitigating harmful effects of air pollution and increasing public awareness.
Improved decision-making process with the help of the results from the application.
Improved accuracy of the result and the plots.
Improved performance because of the usage of Apache Spark for big data.