Building a solution model for a real life problem has always been an inspiration for me. We are all aware that today environmental pollution has risen at such a level that it's becoming a serious challenge for all the human efforts which is being carried out. Global warming , Ocean Pollution, Weather changes, Water Cycle everything is related to each other.. Hence I got my idea.

What it does

My idea is to use Neo4j to find out the possible industries responsible for the pollution in an area by linking them with their respective area's air/water quality measures and disease cases, so that immediate actions can be taken on root level with proof.

How we built it

I started off with simple graph model and prepared a sample dataset using data available on internet. Loaded & linked them in Neo4j and exposed it via GraphQL API.

Main highlights • City nodes along with their air quality measures (PollutionLevel node) – the air quality measures will be there at every fixed interval of time (monthly/quarterly/yearly). • Pollutant nodes found in those areas and what disease are associated with them. • These companies must be using some raw materials and following manufacturing process which can be linked/related to the pollutants & hazardous chemicals. • Linking the disease cases/reports with the chemicals/pollutants and finding out the potential industries behind it.

Challenges we ran into

The collection of data to support my idea.

What's next for Industrial Pollution Analysis using Neo4j - Euler Idea

Addition of more entities such as other factors contributing to pollution apart from industries, detailed process involved in industries so that pollutant links can be done better, different categories of pollution, defining of links between raw materials and industrial process.

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