L-Mile

User A with Small Model (QR code attached)
User B with Large Model (QR codes attached)

Inspiration

For each customer encountering the scenario regarding the product, it is quite inconvenient for them to get in touch with the delivery man or the manufacturer about the poor quality of its product. More specifically, they are unable to contact the delivery man via phones or text messages. Therefore, to resolve this problem, we need to make use of both QR code and the notification system to make sure each receiver is satisfied with the product they received.

What it does

To explain the purpose of the product, it can be generalized as follows: (1) to better understand the functions of QR code and the notification system (2) to guarantee the quality of the product does not worsen. (3) help people become familiar with the whole procedure over the the product processing
To summarize: It's used to avoid getting what you didn't order through any E-Com website and even if you do have that handled using our system.

How we built it

To better respond to our build-in process, our whole project consists of three parts: the manufacturer cooperation who manufactures the product like Amazon, eBay, Alibaba, Walmart, etc., the delivery man who sends the product to the address of the apartment of the receiver, and the receiver who accepts the product. The programming languages we basically use are HTML, CSS, and JavaScript. However, not all processes are as fluent as expected. Each part needs to handle its own error. For example, the manufacturer might accidentally post the image of the wrong product received by the delivery man. At the side of the delivery man, they could not realize that the products they sent to the receiver might be broken without knowing in advance. For the receiver, after receiving the product, they might destroy the product in a horrible way that cannot be imagined. For the receiver part, we built an image text extraction and comparison using Google cloud vision API. It uses the image url from the site you order from and it takes a picture of the product using your webcam when it arrives. Text within each image is extracted and compared to check if that's the right product. If there are any dissimilarities between the product then it notifies the vendor and raises concern on behalf of the user.

Challenges we ran into

The most challenging part of our project is the programming language itself and its logic. This is our group's first time to try the scripting programming language. Even though it is quite exhausting, it is definitely worthwhile or meaningful for us to gain lots of knowledge about the script programming language.

Accomplishments that we're proud of

The accomplishments we are proud of can be illustrated as follows: (1) the implementation of the notification system (2) handling error for each section in our project (3) The image extraction and comparison model which works magic. (4) a group with diverse background to complete a teamwork that is crucial for everyone

What we learned

We learned the introduction of scripting programming languages like JavaScript, HTML, and CSS, how QR codes can be applied to people's daily lives, and the implementation of embedded links. We also learned about state of the art Google Cloud vision API and its uses in our daily lives.