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Smart Cities Wheel - SCW is a pending patent 12 Key Performance Indicator based data
visualization tool that will not only help deploy and build smart cities, but it will also sustain
them for future generations.
Value Proposition-
1) Data driven decision making in Govt. policy is an existing procedures, but data along
with performance driven decision making is what we are trying to establish.
2) A real time track of entire metrics of the city on the palm of your hand.
3) Augmented Reality & Virtual Reality based smart infrastructure planning and
visualization app.
4) Trimonthly audits/calibration of cities based on 12 KPIs, to build proper feedback loop.
5) Building intelligent and dynamic smart cities.
Target Market-
 53% of the world lives in cities. It will be more than 70% by 2025
 Speaking of India 32% of the population lives in urban cities
 There are about 29 Megacities (population more than 10 million)
 Around US$ 1.2 Trillion worth of budget is allocated for cities of the world from
projects, tenders to executions
 SCW is targeting this market potential
 Market needs a performance driven Smart city creator and sustain-abler
 Every year 2.5 million architects and urban planners are graduated from University
 Around 650,000 urban planners are working on Smart Cities project today
 Globally, Smart Cities market will become US $ 750 Billion by 2025
 For India, the market of Smart Cities is over US $ 5 Billion
Competitive Landscape-
 Intellectual Property- We had applied for IP for our Smart Cities Wheel and it is still
under process
 Competitive strengths-
 First to Market
 Data visualization and that too performance driven
 Dynamic city planning
 AR/VR based Smart infra development technologies
 AI based data crunching and predictive algorithms for city’s smartness
 Trimonthly and real time audit/calibrations for cities
 No direct competitor
 Barrier to entry – Non seriousness of Indian Govt. ,collection of precision data,
lack of funds & preference over brand name instead of a Startup
Plan for Execution-
 Current Status of the Business – Proof of Concept
Notes-
 Funding for 12-18 months into operations
 Seeking for executing 3 Smart Cities
 CAC = Customer Acquisition Cost & CRC = Customer Retention Cost
Unit Economics (per smart city)-
 Data Visualization cost/SPVs(Special Purpose Vehicle) (based on premium services
chosen)– USD 50 – USD 120
 In App purchases for per urban planner, architect/ smart city – USD 10 – USD 200
 Cost of data visualization tool licence (onetime fee) – USD 50
 AR/VR smart interface for planning, city notifs, etc. – USD 1000
 Total - USD 1240(took avg for point 1 & 2 above)
 City from scratch(Same model with price doubled) = USD 2480
 AI based prediction smart city bot update = USD 1000
 Total Gross revenue /Smart City = USD 4720
Risk & Challenges- Mitigation-
- Inefficiencyindataextrapolation - Efficientdatascience team
- LessTransperancyincertainpublic
sector.
- AI flaw - EfficientNLPwill be used
- Will try PPPmodels.
- Apocalypse - Buttonso that citiesstill be made
Smart Cities Wheel

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Smart Cities Wheel

  • 1. Smart Cities Wheel - SCW is a pending patent 12 Key Performance Indicator based data visualization tool that will not only help deploy and build smart cities, but it will also sustain them for future generations. Value Proposition- 1) Data driven decision making in Govt. policy is an existing procedures, but data along with performance driven decision making is what we are trying to establish. 2) A real time track of entire metrics of the city on the palm of your hand. 3) Augmented Reality & Virtual Reality based smart infrastructure planning and visualization app. 4) Trimonthly audits/calibration of cities based on 12 KPIs, to build proper feedback loop. 5) Building intelligent and dynamic smart cities. Target Market-  53% of the world lives in cities. It will be more than 70% by 2025  Speaking of India 32% of the population lives in urban cities  There are about 29 Megacities (population more than 10 million)  Around US$ 1.2 Trillion worth of budget is allocated for cities of the world from projects, tenders to executions
  • 2.  SCW is targeting this market potential  Market needs a performance driven Smart city creator and sustain-abler  Every year 2.5 million architects and urban planners are graduated from University  Around 650,000 urban planners are working on Smart Cities project today  Globally, Smart Cities market will become US $ 750 Billion by 2025  For India, the market of Smart Cities is over US $ 5 Billion Competitive Landscape-  Intellectual Property- We had applied for IP for our Smart Cities Wheel and it is still under process  Competitive strengths-  First to Market  Data visualization and that too performance driven  Dynamic city planning  AR/VR based Smart infra development technologies
  • 3.  AI based data crunching and predictive algorithms for city’s smartness  Trimonthly and real time audit/calibrations for cities  No direct competitor  Barrier to entry – Non seriousness of Indian Govt. ,collection of precision data, lack of funds & preference over brand name instead of a Startup Plan for Execution-  Current Status of the Business – Proof of Concept Notes-  Funding for 12-18 months into operations  Seeking for executing 3 Smart Cities  CAC = Customer Acquisition Cost & CRC = Customer Retention Cost
  • 4. Unit Economics (per smart city)-  Data Visualization cost/SPVs(Special Purpose Vehicle) (based on premium services chosen)– USD 50 – USD 120  In App purchases for per urban planner, architect/ smart city – USD 10 – USD 200  Cost of data visualization tool licence (onetime fee) – USD 50  AR/VR smart interface for planning, city notifs, etc. – USD 1000  Total - USD 1240(took avg for point 1 & 2 above)  City from scratch(Same model with price doubled) = USD 2480  AI based prediction smart city bot update = USD 1000  Total Gross revenue /Smart City = USD 4720
  • 5. Risk & Challenges- Mitigation- - Inefficiencyindataextrapolation - Efficientdatascience team - LessTransperancyincertainpublic sector. - AI flaw - EfficientNLPwill be used - Will try PPPmodels. - Apocalypse - Buttonso that citiesstill be made