With more complete drone legislation coming, and an increasing number of industries using drones for more and more applications, adoption of this technology will continue to grow in the coming years. At the same time, the marketplace for drone operators is basically a regional and one-to-one market: while large quantities of drone imagery may be captured, lots of it is used only once or never at all. This means it can´t—or won´t—reach a potentially larger customer base if it is not offered through some sort of platform or marketplace that makes the data available outside the local region where seller and buyer are located.
The Soar platform intends to fill this gap, offering tools for both demand-driven and supply-driven drone content worldwide. Soar uses the cloud to host data, and transactions are realized through smart contracts based on blockchain technology and are paid using an Ethereum-based cryptocurrency.
Soar’s intent is to create a dynamic super-map of highly detailed drone imagery that covers the entire planet. This map can bring geospatial functionality to blockchain protocols that currently lack it. The map uses 2D heatmaps to show buyers and sellers of drone imagery where in the world there is a demand for mapping data, which in turn can form an incentive for users to map these areas and sell the resulting drone data through the platform.
The idea of a dynamic, world-covering high detail map of drone data is comparable to what satellite imagery providers are offering, but with a higher level of detail. The platform will hold multiple data types: still imagery, video content at different resolutions, areal maps with a birds-eye view and multi-spectral, lidar, and thermal imagery. Soar’s map uses a quadtree grid cell structure to present raster mapping data to the client.
Content updates from the client to the blockchain benefit from using the geohash geocoding standard for providing arbitrary spatial precision.
Before content is added to Soar’s map and can be sold to potential buyers, it needs to validated first. That’s why Soar create a participation model that guarantees quality assurance and content moderation. In this model, so-called content intermediaries will be able to host, moderate, and improve the quality of drone content destined for the platform.
These intermediaries are financially incentivized through a cryptocurrency called SkyMap tokens. After content is and uploaded by a drone operator and accepted by these sponsors, a smart contract is executed and a transaction is written to the blockchain. Next, the content is added to the Soar platform. After this, the content can be purchased and downloaded through another smart contract. Sponsors receive a portion of the revenue when their sponsored content is sold through the platform. This model makes it easier for users to interact with the blockchain application, taking away potential uptake barriers normally associated with blockchain applications.
A second market mechanism is Soar’s SkyBounty system, which offer incentives for local drone operators to capture drone data. In this system, a user shows interest in drone imagery for a certain area by placing a bounty—in tokens—in that area. The interest is marked on a 2D map, so local drone operators can see that an interest in their area exists, and upload content to claim the bounty.
The Soar project started in 2015 when alternative mapping technologies were developed for a tactical military project. In 2017, Soar’s technology was made available to commercial and civilian applications and has been adapted to become the platform for the Soar marketplace as well as the foundation for the global super-map that is the planned end-state. The initial launch of the Soar Stage 1 platform happened in June of this year, to be followed by the development of additional functionality to enable value creation opportunities for Soar users. In April 2019, Stage 2 of the Soar platform will release the super-map protocol accompanied by a global roll-out and roadshow in conjunction with key partners in June and July of next year.