Inspiration
CargoConnect was born out of a need for efficiency and sustainability in cargo transportation. The existing problem of trucks carrying unused space, leading to increased costs and environmental impact, was the driving force behind our project. Our inspiration is to tackle this issue head-on by optimizing cargo usage and significantly reducing transportation costs for everyday users. It's a win-win situation, trucking companies get paid to ship goods instead of carrying empty space, and shipping companies get discounted rates and get their product wherever they need it to be faster. Plus, it saves gasoline used by 18-wheelers which has a huge positive impact on the environment.
What it does
CargoConnect serves as a groundbreaking platform where trucking companies list available cargo space, which users can easily discover and book. The platform goes a step further by utilizing machine learning to allow users to scan their packages and identify which empty cargo listings are the perfect fit for their needs. The cargo is also turned into a 3D scan and is put inside a virtual truck with the company's existing cargo, and our program sorts it inside the truck bed to give the trucking company the best possible layout to maximize leftover space. We've also incorporated blockchain technology to enhance security, and transparency, and promote eco-friendliness in the industry.
How we built it
CargoConnect is built using React for the user interface, supported by a smart-contract-backed marketplace. Firebase handles authentication and backend operations. The platform's 3D visualization capabilities are powered by a combination of Python, OpenCV, TensorFlow Lite, and Plotly. We trained our custom model using TensorFlow Lite on various packages, and using OpenCV we scaled their dimensions to a virtual box. We then added this box to a virtual truck space composed of other boxes and resorted them using our own algorithm to try to maximize the space. This is all packaged into a Flask Server, which is fetched by our React App.
Challenges we ran into
Throughout the development process, we encountered several challenges. One notable hurdle involved seamlessly integrating Python with our React app to facilitate image uploads and visualization. Simplifying a complex system into a user-friendly design presented another significant challenge. We had two sides we had to take care of the truckers, and the consumers. Linking the object detection to the 3D scan was another hassle, as turning a 2D image into a 3D object was so difficult. Additionally, building a robust backend to manage cargo listings and user bookings required a lot of effort, especially managing the 3D system.
Accomplishments that we're proud of
CargoConnect is a project we take immense pride in. Our achievements include implementing blockchain technology to monitor and reduce the environmental impact of cargo transportation. Honestly, at the start, we didn't know what the end result was going to be but we are really really proud of what we have created. All the components we brainstormed at the beginning were implemented and combined into a cohesive app using the best tech available.
What we learned
CargoConnect has provided us with a wealth of knowledge and experience. We've learned a lot about the intricacies of blockchain, image analysis, and 3D visualization. More importantly, we learned how to pair advanced concepts together and unite them using existing technology.
What's next for CargoConnect
Looking ahead, we plan on expanding CargoConnect and actually making it work for many types of packages. We aim to implement more machine learning techniques to further optimize cargo space utilization as that's one of our most innovative features. We plan to reach out to real companies and see what possible improvements they could have to help us. Just overall improving the app, and asking leaders in the industries what we could make better.
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