Inspiration

Our core inspiration came from the issues that we face annually in Malaysia as Malaysians, every time the monsoons or tides come in, certain areas will be flooded, and hundreds of families will be displaced and even torn apart forever. What we're trying to do is use neo4j to link up all kinds of useful data to help predict the occurrences of natural disasters.

What it does

What the application does is gather real-time data from users and historical data to predict the occurrence of natural disasters and help mitigate the damage caused. Then the authorities of that region will be able to send out warnings to the users in the affected area.

Why neo4j is suitable

Neo4j is a graph database that is useful for extrapolating data in interesting ways that one might >otherwise overlook. Given enough data that is linked together, it will become easier and easier to make accurate predictions regarding multiple types of disasters and how to mitigate and alert people >to take the necessary precautionary actions to ensure their safety. With how effective neo4j is at >querying the data that is connected to one another, we can more effectively pinpoint the disaster area, >and where else the disaster will propagate towards. It is also useful in deducing natural disasters that >might cause other disasters, such as earthquakes that cause Tsunamis

How we built it

We built it using the tools that were provided and most of the work was done in neo4j aura, React and more importantly, a lot of coffee.

Challenges we ran into

We found out about this contest 2 weeks before the submission deadline. We have zero knowledge in Neo4j. Learn from scratch, start implementing. Have to come out with a project in a short period with the tech we are not familiar with.

Accomplishments that we're proud of

Learn neo4j in a short duration. Manage to come up with a product using neo4j. Teamwork and cooperation.

What we learned

We learned that neo4j is a very robust and interactive tool that can easily help us identify multiple >connections between different sets of data that we would have otherwise overlooked. It is a more >profound way to look at data and how it is stored, how it can be processed, and how dynamic data can >truly be if given the right circumstances.

What's next for Disaster Prevention Web

Currently, we've only worked on a very small scale and for our local situation, but we believe that this system can be upscaled to include other natural disasters and help foster a >community that is alert to the signs of natural disasters. As well as better equip these people on the measures and actions they should take in order to get themselves to safety.

To accomplish this, we will need support from a lot of parties. A very good example is “MySejahtera App” in Malaysia which helps to control the covid19 case. We need this support to make things happen.

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