LCLs are becoming popular because of the flexibility they provide to appeal to rapidly changing customer demands. The LCLs are shipped from port to port in the bigger cargos. Manually associating each LCL with the cargo can be time consuming. After the consignee places the order, it's hard to track where the LCLs are stored and when they get to the port.

What it does

We have created a system that solves the above mentioned problems by automating the process of associating the LCLs with Cargos as well as transmitting notifications as the LCLs register into the system and arrive the destination. Each LCL is equipped with a unique RFID tag. The RFID sensor is mounted inside the Cargo. When the tag is within the vicinity of a the RFID sensor, an LCL-Cargo association is made by sending an http request to a heroku server where the web app is running. As each LCL is associated with a cargo, a text message is sent to the consignee. The microprocessor mounted on the container is also equipped with a GPS module which is able to track the position of the container. When the container reaches the destination, another http request is sent to the server which fires up a notification to the users.

How we built it

We built a Rails app which allows us to create associations between consignees, who are our target users, and their cargo, as well as the cargo containers into which their cargo goes. After the app was constructed, we wrote Python code that would simulate the signals coming in from the sensors, and connected the app to the Tropo API by Cisco in order to send notifications to our users. The Tropo API had resources of code examples to follow. Merging it with functions allowed us to get the effects we needed.

Challenges we ran into

One of the major challenges we ran into was finding ways to interface between Python and Ruby. Although it is possible to run Ruby on Python, running the entire framework of Ruby on Rails was not necessary. We solved the problem by sending http requests. There were different versions of code for APIs and it was confusing to debug.

Accomplishments that we're proud of

We are proud of creating reliable notifications for the customers. We are also proud that we successfully made two programming languages play nicely with each other.

What we learned

API's can be difficult to learn and integrate, but not impossible. They also allow a cleaner way to accomplish a task.

What's next for lclEnterprises

The next step would be to create a physical prototype of the hardware. We would like to connect a the RFID sensor and GPS module on a Raspberry Pi and run the LCL_pyCode in the microprocessor.

In addition to that, we would like to expand the communications the company, the employees, and the customers need. So far we have notification features but many companies use phones and emails to also get feedback from their customers. For people who prefer to sign up and utilize phones over other mediums can also get the chance to submit paperwork. The Tropo API can continue this with its other features.

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