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How we use Google Cloud Platform to calculate air quality worldwide

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By Emil Fisher on December, 4 2016
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December 2016 update:

BreezoMeter, a popular service featured in Google Cloud Platform Blog. 
[Post originally published in June 2016.]


BreezoMeter has very big ambitions but our mission is simple: To improve the wellbeing of billions of people worldwide which are exposed to air pollution every day. You can think of BreezoMeter as the weather of air quality; Using our unique algorithms, we’re calculating the dispersion of air pollution in real time to provide reliable, location based air quality data. In what resolution you ask? at a city block level resolution.

As a startup, the pressure on our developers is massive. Constantly improving….Everything! This force us to be focused and efficient. As a Big Data company, choosing the right cloud platform was extremely critical for us. After examining several cloud platforms, we chose to work with GCP.

Google Cloud Platform enables us to focus on delivering value to our customers rather than dealing with DevOps, maintenance and scaling issues. Have you stopped and asked yourself how good is the air you are breathing right now? We did! And we need to provide this data in real time… Take a look at this air quality time lapse video demonstrating how we compute air quality data in real time, using GCP. For reference, red is low air quality.. Green is excellent… As seen in the video, pollution changes and disperse at the course of minutes and hours. That needs a lot of computing power…!

GCP provides us a technological piece of mind and enables us to focus our technological efforts on our critical challenges, to keep driving our business forward. I would like to share with you 3 quick examples on how exactly Google Cloud Platform does that:

  1. Google’s managed solutions has been a game-changer for us. How? Thanks to App Engine, dealing with API queries is super dynamic. We don’t have to worry about:
    • Load balancing
    • Operating Systems
    • Servers maintenance
    • Scaling issues
    • And erratic load changes. We just upload our code…… and let Google handle everything else.

     

  2. Let's talk about endless calculation resources: As we’ve seen in the air quality time lapse video, we deal with massive data loads (which are Petabytes per month). We have to be able to calculate billions of pollutants’ concentrations around the globe using our complex algorithms. For example, to calculate air pollution in the US, in a city block level resolution, we use BigQuery to analyze ~50 Gigabytes of raw data every few minutes. Now imagine doing so in dozens of countries in parallel…
  3. Finally GCP is also a Sandbox for our data scientists: Google Cloud Datalab has significantly reduced the cycle of developing and deploying new algorithms. Before Datalab:
    • computation was done locally on physical machines and was limited
    • analyzing real data was problematic
    • the algorithms were written in a different programming language than our operational code, so we always had to rewrite our algorithms.Now we develop and test our algorithms directly on the cloud, with the same programming language used by our developers – which is Python.

Today, BreezoMeter’s data is being used by many different kinds of companies from smart home products like air purifiers, to real estate reports, smart cities, health, automotive and more. The opportunities here are endless.

In our vision, when you take your son and daughter to the park, or you are on your way to work or having dinner with your loved ones, you really know what you’re breathing and how it impacts your health. Therefore, for such a responsibility, we had to choose the most scalable, flexible and innovative cloud platform. GCP was and still a great match for us.

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