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📄 Info

Challenge: Life on land

Location: Germany

🌍 Problem

Arctic communities (in Northern Canada) rely on seasonal transportation routes over many frozen lakes & rivers (“ice roads”) for personal and commercial needs, paved roads are rare.

- Only 1% of Canada’s road network covers its 3 northern territories (40% of its land mass).

Increasing temperatures due to climate change makes these transportation routes unreliable, resulting in increased risk to life (for unmonitored routes over frozen waterways eg. snowmobiles) and unnecessary additional delays (for cars/trucks using common trails that suddenly become unsafe) to supply of goods/services, and potential isolation of communities, (where expensive flights are only other option for residents). People cannot trust their traditional knowledge anymore due to climate change.

Higher costs/manpower are also required by public authorities to ensure safety every year due to the increasingly changing conditions

- Over 1.4 million square kilometres of land where only 0.3% of Canadian population resides

🛰️ Solution

We provide an AI-based polar navigation platform that provides optimal routing for land vehicles in arctic regions influenced by climate change.

We do so by providing a data platform that uses machine learning and satellite data for real-time ice trail safety predictions (using Copernicus) and navigation (using Galileo).

This is accessible as:

- A mobile phone app for individuals/drivers (primary target)

- And potentially as a data service that can be implemented in existing navigation solutions for companies (secondary target)

🧭 Demonstrator

Check out our demonstrator here.

Or, take a look at our GitHub page!

⛰️ Value proposition

Existing navigation solutions rely on permanent road infrastructure instead of locally-used packed snow & ice trails and therefore do not consider ice thickness as a potential risk or cause for deviation

We provide safe and reliable navigation over ice (routes depending on sea ice, frozen rivers and lakes) for people living in remote Arctic communities (eg. Canada/US, Greenland) and suppliers who transport much-needed goods/services to them.

Polar Bearings improves their daily lives and sustains their communities, impacted by climate change, by:

- Reducing the risk of loss of life from traveling over unsafe trails over semi-frozen water

- Decreasing the need to rely on expensive flights as the only other alternative transport option

- Insuring goods and services are delivered without unnecessary delays

Polar Bearings would also facilitate public authorities (secondary target customer) to monitor public ice trail conditions remotely in real-time to save costs of regular visual safety checks 

 Potential revenue models for our service:

- Monthly app subscription for individual users or logistics companies

- Customised solutions for public authorities / specialized agencies based on our dataset

- Possible B2B/licensing relationships with navigation software companies or snow vehicle manufacturers

🔮 Future

The roadmap for the further development of the product:

- User study (3mo)

- Finish value proposition (3mo)

- Safe prediction algorithm for ice thickness (3mo)

- Real-time location-based pathfinding (3mo)

- Integration into an app with offline route planning functionality (6mo)

- Marketing (3mo)

Features that could be interesting to be added in time:

- Integration with other data providers

- Connecting with local experience and observation data 

- Rescue service integration

💡 Summary

Approximately 120,000 residents in Canadian Arctic, 65,000 in settlements away from the capital, without paved roads and relying on vehicles using seasonal “ice roads” over frozen rivers/lakes

 Polar Bearings will preserve & protect Arctic communities by sustaining these remote communities through maintaining their accessibility as climate change threatens safe & affordable transportation routes to/from. Polar Bearings will also save residents costs of otherwise having to fly out and the public authorities costs of monitoring the safety for such large expansive areas with low population density

No other navigation solution on the market that considers ice thickness in calculating safe, optimal routes


Our AI-powered solution uses data from both Copernicus (temperature & ice thickness) and Galileo, and incorporates state-of-the-art machine learning algorithms: 

- A navigation pathfinding algorithm based on ice thickness (prototype demonstrated) 

- A Machine Learning algorithm to predict real-time ice thickness data (still working on) 

We are an international team with strong ML and product/UX design expertise, combined with solid business & management experience, committed to developing this idea further and bringing it to market

👩‍💻 Team

Jorrit van der Heide (Team Leader)MSc Industrial Design student (focused on transition design to sustainable futures)
Tom Metcalfe

ML Engineer leading data science initiatives (big data)

MSc Physics (Astrophysics)

Stephanie Schindler
ML Engineer with 5 yrs of Data Science and Consulting experience
Vaibhav Bhutoria
10 yrs work experience as a Senior IT consultant (Norwegian government)
Ian Wright

Teacher with 9 yrs research (ethnographic) experience, 1.5 yrs experience in UX research/design

Elaine Tan

20 yrs experience in Business & Management (space sector)

Global Exec MBA, BSc Environmental Sciences

📖 Presentation

For our full presentation, please take a look here or download it in PDF below.

🤗 Thanks for visiting our project