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Last updated: 28 August 2022 05:48 AM

Updated the glitches in the media upload

The problem we3-degames solves

  1. We built a decentralized card faction game where user takes his NFT trade card and plays the game with an elixir which is termed to be the NEAR crypto tokens. The loser's NFT will be transferred to the Winner's wallet. Based on the gameplay, the bid between two players is split and the bigger potion is transferred to the winner. The assets in the game are belonging to NEAR protocol. All the NFT's are displayed in the NFT gallery along with a special feature of data analytics.

  2. We observe the influence of Web3 on the society where it is difficult for common people to use the applications, lot of DApps are being shipped to the market in the recent days. But at the end of the day, seeing at the users on the Web3 platforms are very niche compared to Web2 platforms. We observed the reason behind this problem to be - "The data is not properly delivered to the customers". We believe that, Data is the new gold, and companies would benefit from having good solid data of users, so that they can up the game. We are analysing the decentralized public blockchain data and generating results like: Block header, Transaction rates. We would be giving it to a company as a data for their development.

Challenges we ran into

  1. Being new with Photon Unity Networking, we initially faced challenges on using it. Since card faction games, have no player movement and spawnings involved, we had to decode and understand how the photon functions would be used. Also, integrating Unity's NavMesh AI with PUN was a heavy task as both of them include a lot of code in detail. We got over that challenge by backtracking all the changes by going through the git commits. This enabled us to observe all the components and decode which one plays a crucial role and which component can be replaced.

  2. This is the first time we are implementing Near Protocol, studying and picking up RUST for the first time was a tad bit challenging.

  3. Finding the useful insights for the users through Covalent API was challenging. More Data-Mining techniques, like Big-Data have been used for further analysis.

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