
Apply HN: A clustering engine that identifies people congregation areas - giesir
Here at Wisebud we&#x27;re building a SaaS clustering engine that identifies people congregation areas and helps analyze how masses behave in real-time. Think Apache Storm but context aware and with support for complex computations. It is also fully decentralized and brokerless. The engine can ingest spatio-temporal data from mobile networks, mobile apps and IoT.
The clusters are contextualized to find user behavior patterns – what and when are people doing at any given location. Companies analyze their own user base, let it be app users, mobile network subscribers or IoT users. There will also be a free global view of the population for researchers, users, governments or anyone else who’s interested.
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Mz
I have a Certificate in GIS and wanted to go into urban planning, so I like
the basic idea here. But I am wondering what you envision as a use case. What
can be done with this? Who would use it? Why?

Thank you.

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giesir
From the business customer standpoint, any company that has a location-based
element in their daily activities may stream their data through the engine. It
in turn performs continuous clustering on the data and displays real-time
results on an interactive map. By using the map's features the company
analysts may, for example:

1) See the details (count with demographic info) of the flow of people
congregated within their selected polygon boundaries.

2) Set handlers that monitor any given area for unexpected behavior and
respond to changes automatically by invoking their predefined logic (ex. a
retailer gets notified of an unexpected increase of customers at a shop and
may want to take action by notifying suppliers or deciding to offer a sale at
good prices).

3) View snapshots of the map's history to identify trends of people masses.
For example, a large company would want to know if people congregation is
increasing within their area of interest over the years, months, days, or not.

4) We hope to push forward from the [3] use case and simulate future behavior
of masses by performing deep learning. This could enable predictive analytic
as a potential use case as well.

The beauty also comes from the point that such information, we believe, is
invaluable to governments, defense agencies and any researchers in general. In
return for reduced SaaS expenses, companies can donate anonymized data to the
public engine. This way we can collect data from multiple different angles
and, basically, approximate the behavior of the entire population. This public
map would be available for all to use, including the data generating users
themselves, if they wish. We hope to classify congregations to identify the
reasons of their formation. Users want to find what people are up to and what
is the most trending at the moment - maybe it's that free concert at Old Town
tonight. Governments want to see that the concert gathered 100 000 people and
growing - way more than was expected, maybe some additional forces should be
allocated for peace-keeping. Maybe some locations form constant traffic jams
or some regions of the city are just too densely populated - this could help
in urban planning for users just like yourself! Not to mention potential web
or mobile applications that could be built on top of this.

We see many use cases for the engine and understand that some may even emerge
completely unexpectedly as the project grows. That is why our main goal for
the moment is to build out the engine topology itself and then enhance it with
analytical features demanded by our clients/users/community.

If You would like to know more about this, do not hesitate to ask. Thank You
for the questions, btw!

