Watch / Flyingcarpet: An Open Network for Building and Using Aerial Analytics Services

Flyingcarpet: An Open Network for Building and Using Aerial Analytics Services

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Flyingcarpet: An Open Network for Building and Using Aerial Analytics Services

Duration: 00:10:35

Speaker: Julien Bouteloup

Type: Talk

Expertise: Intermediate

Event: Devcon 4

Date: Oct 2018

The Flyingcarpet network connects analytics-hungry businesses with a pool of data scientists who compete to create machine learning/artificial intelligence analytics-extraction models from visual data, such as drone and satellite imagery. The competition incentivisation mechanism uses bounties and a Token-Curated Registry of Opportunities (TCRO) running on the Ethereum blockchain to collect and rank machine learning model creation opportunities. From insurance companies, to agri-companies, to governments, the Flyingcarpet network enables actionable insights through rich AI-powered analytics. For example, last year, Flyingcarpet built a machine learning model that enabled a drone to autonomously count the number of coconuts in a coconut plantation in Papua New Guinea—a task which cannot be performed using satellites. The aim was to increase estimation accuracy and reduce the costs of crop yield predictions for the farmer. From a 20 minute autonomous flight, we were able to effectively collect data from the entire plantation, provide an accurate coconut count and translate that into crop yield predictions to be used on blockchain prediction platforms such as Gnosis. This information could also be used by the farmer to optimise distribution of fertilisers, water and so on. Tech paper: Website:
About the speakers


Julien Bouteloup


Julien holds a Master’s degree in Electrical Engineering from the USA and a Master’s degree in Electrical Engineering from France where he specialised in Artificial Intelligence, decentralised systems and security back in 2009. He has built multiple tech businesses from energy trading, high frequency trading, decentralised identity to autonomous transportation systems and won multiple competitions worldwide. He was first introduced into Bitcoin in 2010 and then Ethereum in 2015. He is now involved full-time in decentralised applications, Blockchain, Ethereum, Game and Computability theory, AI, cryptographic and Machine learning algorithms. He is also the AI and Blockchain lead for British Blockchain Association and teaches at the Blockchainconnector in London (

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