Smart City Planning and Investing Support Tool

💎 Idea

Tell us about your idea here. Explain the problem and how you're going to solve it.

We identified the following personas

1. You are a real estate investor, and you have 50 million USD to invest
2. You are someone who has a nice 9-5 job with a yearly 120.000 USD income. You already have a debt free house. You have 150.000 USD in your savings account and you are eligible for a 250.000 USD loan anytime.
3. Representative of the government and are tasked with real estate development in your city.
4. Real estate consultant

Problem statement

• Citizen - can’t find data about air pollution, quality of soil.
• Real estate consultant - hard to create reports containing relevant data for customer.
• Investor - can’t see historical built-up index data easily.
• City planning officer - lack of a holistic view that contains green areas, public services.

Value Proposition

1. We all know the most important thing when we are considering real estate is location. Currently there is available data through easily accessible solutions, such as Google Maps. However these solutions often lack the possibility to get data about pollution, unused lands etc. With our solution you can get a much bigger picture when considering any type of real estate investment, even as a small investor.

2. The main benefits of the product:

   1. A compact, easily understandable and modern interface with minimal action required from the user, for maximum impact / effect. (intuitive) 

   2. Getting real-time data about relevant dimensions people consider when investing into real estate - or simply buying a home.

   3. Holistic tool to get the “generic idea” of your purchase / planning

3. Value in these benefits:

   1. The user can get valuable data and insights with a minimal learning curve on the product.

   2. The user can access socially and environmentally important data easily, such as the pollution rate of the area nearby, public transportation etc.

4. We think that the main problem of the buyer is the lack of easily accessible, relevant data. Most of the data we are providing with the product can not be easily accessed with an average end-user. 

Value summary

• Aggregated data

• Easy to use interface

• Easily accessible data for both average and professional end users

• Lot of various info pulled together at one place

• High impact with heavy visualization

• Holistic

• Enabling green investments

Key assumption(s)

1. Bill the 9-5 wants to buy a house for his family. His preferences are:

   1. Low air pollution

   2. Close green areas - preferably water as well

   3. City have not expanded his preferred direction lately (needs historical data)

2. Mary the blue collar investor wants to purchase X development purpose real-estates

   1. Residential preferences

      1. No industrial areas in the neighborhood

      2. Close green areas, preferably forest

   2. Industrial development

      1. Highways, railroad close

      2. In direction where the city expands

3. Kate the city planning officer wants to have a holistic view on the city. Her preferences:

   1. Where are the lowest quality soil (so the city can advance in that direction)

   2. Unused industrial areas

   3. Green area development

   4. Pollution

   5. Disaster management (floods)

4. Joe the real estate consultant received a call from an important client, where the client named his preferences related to pollution, crime stats, nearby green areas

   1. Based on client preferences (1, 2)

🛰️ EU space technologies

Highlight the data, information or signals you are using/intend to use in your idea. Include some information on how this brings value to your idea.

Data visualized on built up areas

• Sentinel-1 / Urban Planning

  • Locating urban areas and individual buildings

  • Highlight different buildings and topology orientations

  • Track urban expansion, estimate building type or locate buildings in high-risk areas (such as floods)

• Sentinel-2 / Land use/cover classification algorithms / Built-up Area Classification

  • Creating built-up index

• Sentinel-2 / Urban Planning / Urban classified

  • Differentiating between water, built up areas, barren areas and vegetated areas

Possible rooftops analysis

• Sentinel-2 / Urban Planning

  • Mark urban areas with rooftops

  • Mark high probability of vegetation areas in green

  • Mark rivers, pools and the sea in blue

Public transportation and roads

• Google Maps Public Transportation Layer

Public utilities

• Collecting data on power grids from country-specific services and visualize them

Green areas, rivers, lakes nearby

• Sentinel-2 / Remote sensing indices

  • NDVI

  • NDWI

Air pollution

• Sentinel-5P

🏦 Space for the Financial World

Which of the 3 challenges are you solving, and how does this contribute to solving the problems faced in finance, insurance and investments?

We are targeting the "Enabling green and sustainable investments" challenge with our idea. 

We believe that a tool like this is able to enhance the small / large scale investors decision making, also, easier to suggest green investments with better position pre-selection. Also, the investors from far away should not travel to the planned location in advance, as satellite data is able to provide them decorated information. 

For governmental-level planning it is easier to observe the effects of urbanization, thus can effect the decision making, as well as proofing the real estate development idea towards citizens.

It also has multiple extending options, like:

• Connect to country-level real estate websites to provide real-estate prices
• Connect to country-level crime statistic to provide social context
• Measure air pollution sources (wind, bad forestry, nearby industrial zones)

🤼 Team

Tell us who is in your team, what role they have (e.g. coder/designer), and a 1-2 sentence bio.

Out team contains 3 members:

• Member 1: Technical architecture, data analysis, coding
• Member 2: Business analysis, data analysis, security concerns, coding
• Member 3: Business analysis, data analysis, UI/UX, coding