Decentreelized

Decentreelized connects donors with farmers to engage in environmental conservation 🌳🙌

Demo Video Source Code

Technologies

Ethereum

Solidity

IPFS

Adobe Premiere

Hardhat

Remix

Description

Decentreelized connects donors with farmers using Ethereum smart contracts. Many farmers have plots of land that they cannot use for crops, and they therefore cannot make any profit from the land. There are also many people who like to help preserve the environment or to improve small communities. Donors in return receive a unique NFTree for their conservation efforts. How is Decentreelized is different from other products that already help environment? Because it is completely decentralized. Our smart contracts only transfer 10% of the donated funds to the farmer each year, for 10 years. During this time, farmers must send pictures to prove that donated money is being used to help the environment and preserve green areas - this ensures they receive their payment each year. If the money is not being put to good use, the person who donated can ask for a refund of the remainder of their deposit at any time. NFTrees are resalable on secondary markets, benefitting both the donor and farmer for the increased incentive! Donors can also share the earnings from charged particles based NFT with the farmer.

How It's Made

This project uses a backend in Node.js. HardHat was used as a testnet and Hardhat Hackathon Boilerplate code to build our frontend and to deploy the smart contract & front end UI to connect donors with farmers who plan to take care of a tree over multiple years. The trees are mapped using What3Words and an NFT containing the tree's images and other info in IPFS and pinned by Fleek.co. The smart contract uses the ERC-721 pattern and the base smart contracts from OpenZeppelin. We also wrote a Vault to follow separation of duties pattern. UI also uses Google Maps Api to display and zoom data in a map. To store NFT metadata we used jsonbox to faciliate since it is very easy to use in a MVP. We added internalization using react-18next.

Team

luiz soariis Chakrit Thippachartyothin Aditya Aditya crays loh
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