DFD SIGNED
Deep Forestry Drones - revolutionising forestry mapping and analysis with artificial intelligence
Total Cost €
0EC-Contrib. €
0Partnership
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0DFD project word cloud
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Project "DFD" data sheet
The following table provides information about the project.
| Coordinator |
DEEP FORESTRY AB
Organization address contact info |
| Coordinator Country | Sweden [SE] |
| Total cost | 71˙429 € |
| EC max contribution | 50˙000 € (70%) |
| Programme |
1. H2020-EU.3. (PRIORITY 'Societal challenges) 2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs) 3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies) |
| Code Call | H2020-SMEInst-2018-2020-1 |
| Funding Scheme | SME-1 |
| Starting year | 2020 |
| Duration (year-month-day) | from 2020-01-01 to 2020-06-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | DEEP FORESTRY AB | SE (LANNA) | coordinator | 50˙000.00 |
Map
Project objective
Forestry mapping is key for the economy, yet most of the mapping work is manual today, allowing assessments of only 5-10% of trees. The results of improper forestry mapping range from the inability to react to crisis events such as wildfires or diseases, lower productivity and inaccurate valuations. To solve this problem, many companies have launched mobile phone-based platforms and above canopy LiDAR or photogrammetry, but these products often come with several drawbacks, e.g. they do not provide an accurate understanding of the most desirable forestry characteristics such as wood value (quality) class, species type, volume estimation and bad wood estimates. They are also unable to provide a detailed map of the terrain (boggy areas, small streams, boulders, dead-wood, fallen trees, etc.). These drawbacks cause the existing solutions to become difficult to use and time-consuming, while providing very little added advantage over traditional methods. In turn, this forces companies to create less value and leads to smaller ROI.
Deep Forestry AB built the first agile, light-weight, autonomous drone to fly below the canopy of commercial forests, that is, in-between the trees. Flying below the canopy provides our customers with analytical tools which were previously unavailable: precision analytics, robust classification algorithms, and optimized harvesting routes. They will help companies to cut their costs and increase revenue while mitigating risks and eliminating human error. Our new (Drone AI) technology will provide more data to the front-end of the forestry value chain than has ever been thought possible.
The key objective of our project is to transform an initial business plan into a robust strategy for international commercialization. With this goal in mind, our Phase 1 project will focus on a more precise market evaluation, assessing technical requirements for further scaling and optimizing our go-to-market strategy.
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The information about "DFD" are provided by the European Opendata Portal: CORDIS opendata.