## Inspiration

After hearing IF talk about this problem, we identified many possible areas to improve their process of cargo transport. Trucks were often taken while the driver left the truck for short periods of time, or stolen from a parking lot over the weekend. The area we chose to focus in was quick notification if the truck was potentially being stolen.

## What it does

Our solution is two parts:
The truck will not be able to start without a keyfob. If it is, it will send a text message saying a potential theft is in progress.
The second part uses R to do statistical analysis.We can figure out the locations of where the cargo truck is- and if it should be there or not. If it ventures out too far from its normal path, a notification will be sent of the truck's position.'
As well, we are looking at driving times. If the driver has just finished a shift (ie driving for ~8h), if their truck starts moving again, it is more likely to be suspicious activity. As well, the truck driving during odd times at night (when nobody would be taking deliveries).

## How we built it

UI was made using HTML/CSS and Google maps was used for visualization. Flask was used to run our python scripts. The main algorithm is in R which is then wrapped with python.

## Challenges we ran into

The data had many issues and anomalies which made processing it difficult, and threw off our algorithim.
In fact, we took a significant amount of time just cleaning up the data and removing null points so it was usable.
We did not have any information on what path the truck was supposed to take, so it was hard to identify a stolen truck vs one that was not.

## Accomplishments that we are proud of

Being able to identify the truck that was stolen
Getting the whole thing running.
Cleaning up the data and plotting the trucks' movement in real time.
Working so well in a team, everything flowed together almost seamlessly.

## What we learned

Algorithm design and the importance of data quality.

## What's next for Securesy

We can enhance the algorithm, build a working prototype for the keyfob. As well, testing this out on real trucks would provide invaluable data and experience to see what needs to be changed.
## Inspiration

Twitch for Pokemon

## What it does

Play chess collaboratively with other players. Together, teams will decide on one move to play against the opponent. This game format is both instructive for beginners and fun for more experienced players.

## What's next for hivemind

Hivemind can be extended to host a wide variety of games. Other features would include playing against AIs, creating private rooms, and more customization.
## Inspiration

We wanted to build a sustainable project which gave us the idea to plant crops on a farmland in a way that would give the farmer the maximum profit. The program also accounts for crop rotation which means that the land gets time to replenish its nutrients and increase the quality of the soil.

## What it does

It does many things, It first checks what crops can be grown in that area or land depending on the weather of the area, the soil, the nutrients in the soil, the amount of precipitation, and much more information that we have got from the APIs that we have used in the project. It then forms a plan which accounts for the crop rotation process. This helps the land regain its lost nutrients while increasing the profits that the farmer is getting from his or her land. This means that without stopping the process of harvesting we are regaining the lost nutrients. It also gives the farmer daily updates on the weather in that area so that he can be prepared for severe weather.

## How we built it

For most of the backend of the program, we used Python.
For the front end of the website, we used HTML. To format the website we used CSS. we have also used Javascript for formates and to connect Python to HTML.
We used the API of Twilio in order to send daily messages to the user in order to help the user be ready for severe weather conditions.

## Challenges we ran into

The biggest challenge that we faced during the making of this project was the connection of the Python code with the HTML code. so that the website can display crop rotation patterns after executing the Python back end script.

## Accomplishments that we're proud of

While making this each of us in the group has accomplished a lot of things. This project as a whole was a great learning experience for all of us. We got to know a lot of things about the different APIs that we have used throughout the project. We also accomplished making predictions on which crops can be grown in an area depending on the weather of the area in the past years and what would be the best crop rotation patterns. On the whole, it was cool to see how the project went from data collection to processing to finally presentation.

## What we learned

We have learned a lot of things in the course of this hackathon. We learned team management and time management, Moreover, we got hands on experience in Machine Learning. We got to implement Linear Regression, Random decision trees, SVM models. Finally, using APIs became second nature to us because of the number of them we had to use to pull data.

## What's next for ECO-HARVEST

For now, the data we have is only limited to the United States, in the future we plan to increase it to the whole world and also increase our accuracy in predicting which crops can be grown in the area. Using the crops that we can grow in the area we want to give better crop rotation models so that the soil will gain its lost nutrients faster. We also plan to give better and more informative daily messages to the user in the future.