Q3 - 2017
First proof of concept successfully completed
Q1 - 2018
Q2 - 2018
Winners of Cogx London!
Q3 - 2018
Q3 - 2018
Technology and industry partners announced
Q3 - 2018
Testnet alpha launch
Q4 - 2018
Testnet beta launch
An Open Network for the World's Geospatial Analytics
The Flyingcarpet network provides organizations and smart contracts with geospaital truth. Data scientists compete to create machine learning models from satellite imagery. Models are tradable via NFT ownership tokens.
Aerial Data as a Source of Truth
Models are created for new geospatial use cases via a decentralized competition of data scientists. Competition funding is incentivised via model ownership NFTs that encapsulate all future model revenue. As smart contract oracles, these models enable game-changing decentralized applications, such as parametric insurance where pre- and post-state satellite analytics can trigger automated claims.
From DAOs, to insurance companies, to agri-companies, to governments, the Flyingcarpet network enables actionable insights through rich AI-powered analytics.
Namaliu, a farmer in Papua New Guinea, has a problem. He wastes countless days walking up and down his coconut plantation with a clipboard and pen, manually counting his yield and inspecting his trees. The machine learning model instead processes visual data of Namaliu's plantation, extracting insights and analytics about its projected harvest.
Now, not only can he track theft and monitor yield much more effectively, he can also sell the analytics to third parties, such as government bodies or commodity traders.
Infrastructure projects are incredibly costly, typically involve multiple stakeholders, and can be dangerous for the feet on the ground. A machine learning model can process the visual data relating to the bridge and extract insights and analytics about its condition.
Any abnormalities or weak sections are identified and rectified before they become costly - or deadly - problems. Flyingcarpet models can analyse a huge range of infrastructure, including rooftops, roads and power lines.
Setting Insurance on Fire
Insurance claims often take years to settle, payments are based on generic historical data, and brokers typically take a hefty 25% commission. With Flyingcarpet, a machine learning model determines the physical state of insured locations by processing raw satellite imagery gathered both before and after natural disasters occur.
By building on top of the decentralized Ethereum blockchain, insurers and customers operate within a commission-less protocol, enabling participants to capture all network value.
Raw imagery is sourced primarily from satellites. However, plane and drone data is also used for specific use cases.
Unleash the collaborative power of decentralised data scientists. Machine learning competitions incentivise participants to create cutting-edge models that extract analytics and insights for specific use cases.
Ownership NFT tokens are minted for successful models. With no middleman fees, ownership NFT tokens capture all model value for network participants.
Q3 - 2017 - First Proof of Concept Successfully Completed
An analytics-extraction algorithm running on drone imagery counted the number of coconuts in a plantation, equipping the farmer with relevant analytics and opening up significant supplemental income channels for the farmer.
Q1 - 2018 - Team Growth
From a drone developer to a performance marketer our list of contributors grows to 11 and counting.
Q2 - 2018 - Winners of CogX London!
Best in Category for Blockchain solutions for IoT.
Q3 - 2018 - Whitepaper Published
Read the latest Flyingcarpet paper here.
Q3 - 2018 - Partners Announced
From industry to technology partners, we'll be announcing our key strategic alliances created to boost the network in its early days.
Q3 - 2018 - Testnet Alpha Launch
Testnet launched to showcase addition and staking of geospatial analytics opportunities.
Q4 - 2018 - Testnet Beta Launch
This iteration of the testnet will include the dataset annotation portal and initial machine learning model integrations.
'19 - Mainnet
Fully operational geospatial services network.
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Get In Touch
If you love complex decentralised mathematical algorithms, get in touch - firstname.lastname@example.org
Have a network of data-collecting drones, satellites, or planes? Get in touch with us! - email@example.com
If your business, DAO or project requires a specific physical world oracle or geospaital analytics-extraction service, reach out to us - firstname.lastname@example.org
We are building something amazing, and we need amazing people to help us - email@example.com