We help firefighters understand where the fire is and where it will spread. This is important because avoiding 8% of landscape fires would reduce global greenhouse gas emissions by 1%.
Current Status
We have just finalised our early prototype and have already sold it to Georgia (forest fire monitoring), Moldova (border guard) and to Estonia (Tallinn city police).
Problem or Opportunity
Every year 4-5 million landscape fires destroy 400-500 million hectares of land and cause 300 000 deaths. Landscape fires account for ca 10-15% of global greenhouse gas emissions. By helping fire fighters to act quickly we will help them to reduce fires by 7-8%. This in turn will reduce the global CO2 emission by 1%.
Fires grow with exponential rate: it is very important that firefighters would be able to act quickly and contain the fire before it reaches out of control. The abovementioned 1% reduction can be achieved by avoiding 1/10 of those “big” landscape fires.
Solution (product or service)
We mount machine vision modules on board of the drones and fly them connected to cellular networks. This allows us to detect the location of the fire without human input and display it on a map while the drone is still in the air.
Our drones can do precision landing into a drone nest and have an obstacle avoidance system: this makes it extremely easy to operate our drones.
Because our drones are connected to mobile networks the data collected is instantly shared with not only the drone operator, but with the command & control centre (can be hundreds of miles away).
Business model
We use B2B2G and offer both (1) the hardware without our software and (2) only software:
(1) Hardware: drone with automated fire front detection software.
(2) Software that enables firefighters to do post-flight fire front location detection with the drones they already have.
We also provide firefighters one unified data hub from which they can access the drone aerial data as well as satellite imagery, weather data and fire spread forecast models.
The SaaS fire front detection model is the easiest route to market as it does not require tenders to purchase drones.
