Haulswap

Haulswap revolutionizes the way commercial trucking works all over the country, creating a new system that mimics a 9-5 job. Through AI, we optimize transportation for maximum efficiency for workers.

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Inspiration

Members of our team know very close family friends who are truck drivers and are undergoing several difficulties regarding a balance in health, lifestyle, and pay. They work long hours with conditions and pay that doesn’t necessarily compensate their efforts or external costs. These issues sparked the initial thought of revolutionizing the trucking industry through AI modeling to make it a more suitable and sustainable industry for truck drivers.

What it does

Haulswap is a web application for drivers and firms that utilizes blockchain technology to establish a trust amongst all parties. Our technology uses AI modeling to employ optimal nodes throughout the US where truckers are able to drive to local nodes, deliver, and pick up packages, and firms are able to contract truckers and initiate smart contracts through bnb which adds transparency to the payment of truckers which works to ensure that they are properly compensated.

How we built it

We built our application utilizing bnb, web3, node.js, express.js, and ai/ml modeling to create our platform. The process of planning started through creating 4 sides of the project. The frontend, the backend, the node optimization, and the blockchain transactions. Our team divided and conquered each of these tasks and came together for discussion and brain storming when running into an error or a problem.

Challenges we ran into

We ran into several challenges and difficulties. The organization of the nodes for our AI model was one of our difficulties since we didn’t really know where to start. We overcame this challenge by creating a step by step model, learning more about graph theory, creating multiple test cases to train our model, and utilizing Monte Carlo tree search.

Accomplishments that we’re proud of

Two of our accomplishments entail implementing a Monte Carlo Tree Search for our AI model and its training along with the bnb technology to our web application. Both of these implementations took a lot of effort however we continued to persevere and created an end product that we are all very proud of.

What we learned

We learned more about graph theory and blockchain technology. More specifically, we learned about the creation and management of smart contracts. On top of all of this, we learned how to integrate both these technologies to the front-end user-interface.

What’s next for Haulswap

In the future, we plan on continuously refining all aspects of the website: front-end/back-end, UI, UX, Monte Carlo Tree Search Model, improving model validity, and optimizing our blockchain technology for all users. In addition, we need to find out a way to improve trucker wages as its very low compared to the rigorous labor and workload that they are given.

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