Inspiration-

When I was a kid, I used to mesmerized myself with the idea of how cities are planned? What are the key aspects of cities that, woven together in order to build this massive inclusive structure? And, what amount of connectivity, structures, economics, etc. needed in order to design a self sustain city? What if city starts learning themselves and design themselves? Keeping my childhood dream and fantasy alive, I started researching and reading in the grounds of Smart Cities- citizen engaging, self contained and self sustaining cities.

After an year long research, a graffiti enclosed cozy office space, 10–15 withered coffee mugs, enormous mind mapping sessions, brainstorming sessions with urban planners, countless handwritten pages, gazillion of sticky notes, 7 destroyed markers and 2 faded white boards helped in realizing a dream. A dream to curate and solve the problem of urban India- “Making Smart Cities” using "Smart Cities Wheel".

What it does-

Smart Cities Wheel is a patent underway 12 Key Performance Indicator based data analytic and visualization platform that helps to deploy & build Smart Cities using - "City planning & Management visualization too". Using the Artificial Intelligence algorithm, it helps to predict the future performance of the city and based on that what necessary "call to actions" needed to be taken in order to maintain the "Smartness" of the city. 12 Key Performance are -

  1. Economy
  2. Mobility
  3. Infrastructure
  4. Technology
  5. Awareness
  6. Quality of Life
  7. Smart City Agents(people)
  8. Smart Governance
  9. Healthcare
  10. Waste Management
  11. Energy
  12. Innovation

The entire city will be built based on these KPIs and it will be sustained for the future to see the indicative perimeters leading to the performance of each of these KPIs.

Using our Infrastructure KPI we built an Augmented Reality app that helps urban planner to design cities and its retrofits intuitively over a smartphone, by augmenting it over the smart phone.

Data Visualization platform (Limited to proof of concept) -

  # Importing mobility KPI schema in MongoDB  for visualization 
print var MobilitySchema = new Schema({
  road_infra: Integer,
  conc_to_nonconc: Float,
  num_taxi_comp: Integer,
  num_tot_taxis: Integer,
  taxis_per_capita: Float, 
  num_of_busses: Integer,
  tot_passen_bus: Integer,
  num_metro_lines: Integer,
  num_stations: Integer,
  per_with_metro_access: Float,
  tot_passen_metro: Integer,
  per_pop_metro_use: Float,
  num_airports: Integer,
  num_inter_flights: Integer,
  num_dom_flights: Integer,
  num_of_destinations_flights: Integer,
  avg_pollu_output_car: Float,
  tot_pollu_cars: Float,
  tot_pollu_trucks: Float,
  daily_metro_pollu: Float,
  flights_fuel_usage: Float,
  carbon_output_air: Float,
  per_homes_alternate: Float,
  per_commer_alternate: Float,
});

## Augmented Reality app with Infrastructure KPI Features-

  1. Download and install the app from the dropbox link below.
  2. Open it up and put the camera facing towards the floor plan for the Rajwada-heritage site of Indore, such that the map meets the end points of the camera. Watch the Rajwada augmented ! on your screen.
  3. Touch the shops, roads and other objects to read their dimensions.
  4. Move shops, road and other objects to plan the area.
  5. Click the "camera" icon to save the image of the planned area.
  6. Click the "wheeler" icon to have the floor plan for the area.

How we built it-

  1. We used Unity 3D as the tool do design the Augmented Reality app.
  2. We designed the retrofitting area that augments over it using google sketch pro under .fbx file extension.
  3. Using C# as the basic language we modeled the design using the sdk and thus designed the app.
  4. For data visualization tool(proof of concept) we are currently building with using MongoDb , Python 2.7.2 and D3.js
  5. We are collecting the data from open source govt. websites, offline collections etc.
  6. We then laid the visualization using HTML5, CSS3 and Jquery, especially D3.js to design the front end.

Challenges we ran into-

  1. Outdated or no data for certain perimeters of KPI
  2. Real time feeds for the Rajwada AR to plan it more intuitively.
  3. Data collection and penetration.
  4. Making the tool to design cities for itself.

Accomplishments that we're proud of-

Finalist in Digital India Hackathon 2016.

What we learned-

  1. Data precision and collection using collect resources.
  2. Mining the data intelligently in order to focus on city's smartness.
  3. Handling the tools like - Unity 3D.
  4. Augmented Reality & Mixed Reality
  5. Artificial Intelligence & Neural Nets.
  6. Most Important - Cities can be planned and managed using AI.

What's next for Smart Cities Wheel-

  1. Pitching our model to Indore SPV, under Smart Cities Indore work.
  2. Building the AR app for pan city.
  3. Adding panorama video and photograph feature with geo coordinates to the app in order to avoid google map images.
  4. Real time encroachment notifications.
    1. Data visualization tool - from proof of concept to actual pilot in Indore.
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