{"title": "Amazonomy - Community-led Science", "website": "https://shorturl.at/gCvn9", "createdAt": 1723216574092, "userGithub": "Amazonomy - Community-led Science", "credentials": {"twitter": {"type": ["VerifiableCredential"], "proof": {"jws": "eyJhbGciOiJFZERTQSIsImNyaXQiOlsiYjY0Il0sImI2NCI6ZmFsc2V9..nY_SPUCXBwCa8ohZ2VHrD2mHyJlF4mKNkouexx4MIP37W4X6_JHTU7qKZlrF1KvVVL52P3qsgZhk2ehvMqkTBg", "type": "Ed25519Signature2018", "created": "2024-08-09T15:22:07.075Z", "proofPurpose": "assertionMethod", "verificationMethod": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC#z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC"}, "issuer": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC", "@context": ["https://www.w3.org/2018/credentials/v1"], "issuanceDate": "2024-08-09T15:22:07.075Z", "expirationDate": "2024-11-07T15:22:07.075Z", "credentialSubject": {"id": "did:pkh:eip155:1:0x2807f448DD35805A3C76a63b21537515F3c5a7Ad", "hash": "v0.0.0:UvxcGC/49WpcVw8ljABy7beu33W4VvyRRetqaYtzlF4=", "@context": [{"hash": "https://schema.org/Text", "provider": "https://schema.org/Text"}], "provider": "ClearTextTwitter#Amazonomymrv"}}}, "description": "Our project aims to establish a fishery management system for communities in the Negro River Basin of the Amazon, while integrating cutting-edge Technologies and traditional knowledge. These communities rely heavily on fishing as their primary source of protein and income. \n\nTraditionally, these communities use a method called \"standby fishing.\" This involves two canoes, each with four people, waiting at predetermined spots with a large net. When a school of fish enters the place, the fishermen close the net, trapping the fish. The catch is then divided between community consumption and sale for extra income.\n\nHowever, climate change has led to extreme droughts in Amazon rivers, disrupting fish schools' usual movements and migrations. As a result, communities are spending weeks in their canoes, waiting for fish that no longer come to the traditional spots. This situation is threatening their main sources of protein and income.\n\nOur proposed system will deploy Hidromoths to track fish school movements through the communities' fishing spots in the Sustainable Development Reserve of Rio Negro. The communities will take pictures of the catch and using machine learning, we will identify fish species and sizes. \n\nThe Hidromoths will monitor fish school movements and sizes, providing communities with crucial information on where fish schools are located, their preferred spots, and their movement patterns throughout the day. This will save communities countless hours and financial resources.\n\nAfter catching the fish, communities will photograph their catch. Our machine learning model will then measure the fish size and identify its species. This data will be shared with both traditional and scientific communities, allowing for detailed analysis and comparison of species abundance, size, and proportions throughout the seasons. This information is critical for developing fishery management plans in the Amazon and understanding the impact of extreme climate events on fishing capacity.\n\nThis system will benefit 16 communities in the reserve, impacting 900 families (around 5,000 people) across 103,000 hectares. By improving fishery management, we aim to enhance food security, support local economies, and inform conservation policies.\n", "projectTwitter": "Amazonomymrv"}
Amazonomy - Community-led Science
Our project aims to establish a fishery management system for communities in the Negro River Basin of the Amazon, while integrating cutting-edge Technologies and traditional knowledge. These communities rely heavily on fishing as their primary source of protein and income. 

Traditionally, these communities use a method called "standby fishing." This involves two canoes, each with four people, waiting at predetermined spots with a large net. When a school of fish enters the place, the fishermen close the net, trapping the fish. The catch is then divided between community consumption and sale for extra income.

However, climate change has led to extreme droughts in Amazon rivers, disrupting fish schools' usual movements and migrations. As a result, communities are spending weeks in their canoes, waiting for fish that no longer come to the traditional spots. This situation is threatening their main sources of protein and income.

Our proposed system will deploy Hidromoths to track fish school movements through the communities' fishing spots in the Sustainable Development Reserve of Rio Negro. The communities will take pictures of the catch and using machine learning, we will identify fish species and sizes. 

The Hidromoths will monitor fish school movements and sizes, providing communities with crucial information on where fish schools are located, their preferred spots, and their movement patterns throughout the day. This will save communities countless hours and financial resources.

After catching the fish, communities will photograph their catch. Our machine learning model will then measure the fish size and identify its species. This data will be shared with both traditional and scientific communities, allowing for detailed analysis and comparison of species abundance, size, and proportions throughout the seasons. This information is critical for developing fishery management plans in the Amazon and understanding the impact of extreme climate events on fishing capacity.

This system will benefit 16 communities in the reserve, impacting 900 families (around 5,000 people) across 103,000 hectares. By improving fishery management, we aim to enhance food security, support local economies, and inform conservation policies.

Amazonomy - Community-led Science