City-Alert

Inspiration

There is no system available with the govt administration department like Police and District Magistrates to send notification to every resident of the city or a particular area. They have to rely on news media and by that time its too late. Also resident cannot ask for immediate help or send news of immediate happenings to concerned departments.

What it does

There will be a centralized platform where the residents and the administration departments can register for sending instant notifications. A mobile app needs to installed which will provide interface for sending and receiving messages. Resident of the area will be automatically get connected to the concerned departments of the area they reside. The department team will also have a mobile as well as web interface through which they can see the messages from their area and can send notifications to everyone in the areas within their control.

How we built it

It’s a concept built on the area of Internet of Things(IOT) where the people are connected using the internet of their mobile. The underlying protocol used for communication is MQTT. Server side component will be a (cluster of)MQTT broker(Mosquito) and the client interface is MQTT client in android or IOS. MQTT works efficiently in low bandwidth and is reliable and scalable.

Challenges we ran into

Testing the application with low bandwidth. It is difficult to test the "reconnect in low bandwidth" and "fast communication delivery".

Accomplishments that we're proud of

Its a platform that can help the people to save their lives. A message can save life before it gets too late.

What we learned

A different view of applying IOT in real world. MQTT protocol is very valuable not given enough respect yet.

What's next for City-Alert

We are in process of developing the idea and will deliver a basic cut by 11th April.

Future enhancements will cover below features: Support high load of connecting millions of people. Can be done by clustering of MQTT broker. Will also add support of analyzing the sentiments in the messages by applying Natural Language Processing(NLP)