## Inspiration

During sweltering summer days, cars can be become very hot very fast. Many people accidentally leave their dogs, or even young children and infants, in their vehicles, while picking up groceries or shopping. Even though they expect to be gone for only 20 minutes or less, during this time, car temperatures can reach about 110 degrees within minutes. 39 children died of heat stroke in overheated cars in 2016, accumulating to hundred of child deaths since 1998. Thousands of pets die per year in these cars. We wanted to stop these tragic and preventable deaths.

## What it does

Hot Dog is an IoT application, using IBM Watson's Node-RED and the Raspberry Pi. Users place the hardware, comprised of the Raspberry Pi and a temperature sensor, near their windshield in the car. Hot Dog will keep track of the temperature within their vehicle while they are running errands. When the measured temperature is about to reach dangerously high-levels and it detects a presence in the car, the application will send a text message to the user, warning them that they are potentially putting their pet/child at risk of heat stroke. If the car does become extremely hot, the app will also call Animal Control or 911 automatically as a second resort. As another addition to the IoT capability, we have a twitter account linked that tweets from the pet's perspective calling for help on a large social scale. In addition, we have made a web application dashboard that displays the live temperature updates, grabs data from a weather api to display heat patterns, graphs the temperatures fetched through the Pi, and displays the tweets.

## How we built it

Our main platform runs on Node-RED, where we have the IoT device as the Raspberry Pi (or for demo purposes, an app that allows us to manually control the temperature). The IoT device connects to many outlet nodes, such as twitter, twilio, and http to send live data to each outlet. On the hardware side, we have the Pi connected to a temperature sensor to retrieve measures and send it to the server. Then, we have the web application created from HTML/CSS, Javascript, and Angular.js to display the live data, also using frameworks such as n3-charts and OpenWeatherMap to visualize the data and give a comprehensive insight into past and projected temperatures in and around the car. Most importantly, the web page displays the status of the car, whether it is dangerous, uncomfortable, or safe at the current moment in the car. We use Twilio to send messages to the user's phone if the car become too hot or to call the authorities in dire situations. We use Twitter to tweet live updates as well.

## Challenges we ran into

As first-time hardware hackers, we were completely new to using microprocessors and microcomputers. We went from trying to use the Raspberry Pi, to the Intel Edison, to the Arduino Uno, back to the Edison, and finally to choosing the Raspberry Pi. We were trying to figure out how to attach a temperature sensor and how to connect the device on Node-RED as an IoT device. After many installations and attempts, we finally managed to retrieve data from a Raspberry Pi. Additionally, we had to simulate the temperature, so we also used a separate IoT device to manually change the temperature. We had troubles learning how to use Node-RED and how to connect nodes and data payloads appropriately. The twitter feature had authorization issues as well. Every step felt like 3 steps back to begin with, but we finally had a product at the end.

## Accomplishments that we're proud of

We made an IoT application that works! We successfully connected the data from the Pi to multiple outlets/platforms including web, Android, and SMS tools. It was amazing to see how Node-RED could so easily send information live onto our phones and other laptops. Our idea actually solves a real-life problem that could potentially save many lives lost every year. All of us see on the news that some small child died of heat stroke while their parents were following their busy schedule and just simply forgot how hot the day was. Way too many helpless pets die from this very issue as well, and our app can work to lower the number of fatalities.

## What we learned

We expanded our horizons beyond simply software and integrated hardware into our hack. We learned of the crazy capabilities of the Raspberry Pi, how to interface the Pi with serial communication, and how to integrate peripheral senors onto the hardware. We learned about the power of Node-RED to connect everything together and more about how node modules work. As students from USC and Stanford and strangers at first, we learned how to emphasize everyone's talents yet also learn a lot about each part of the project.

## What's next for Hot Dog

Ideally, this application will be incorporated into cars across the country or encourage car manufactures to make their own implementations to monitor car temperatures. To improve the accuracy of our hardware, we will add sound sensors to detect noises such as barking or crying along with the temperatures so that users will only get notifications and warnings when the hardware is sure that the owner is out and there is life at risk in the car. The hardware will eventually have LED lights displaying warnings to passerbys when some being is threatened. We aim to educate people about the dangers of leaving lives in hot vehicles as well and raise awareness. We are improving our Android interface and tried making a Android launcher widget as well, so we definitely want to make more mobile apps for Hot Dog to supplement the mobile accessibility and provide information easily on mobile home screens like it does on our existing apps.
## Inspiration

Students spend hours getting their resumes ready and then application portals ask them to rewrite it all on their terribly designed webform. Worst of all, autofill does not work! Making it a very tedious manual effort. So we designed a site that goes around this, and let's our users automatically apply to as many relevant job postings as possible. We initially planned our app to programmatically generate a Resume and Cover Letter based on the job description and the user's skill set.

## What it does

Instead of going to every single website to apply, you list all the jobs you want by entering their addresses or by selecting the jobs we think match you. Then, you simply enter your information **once** and our website will handle all those applications and get back to you with their statuses!

## How I built it

Our web app was built using React and on a Redux app hosted on Firebase. We used Firebase functions, database, storage and authentication. We used UI-Path (the automation application) to automatically fill out the forms based on the users preferences. We used a Windows server to run our UiPath application on the Google Cloud Platform, we also set up a flask server on the VM to be ready to take inputs.

## Challenges I ran into

The UI-Path application does not have the functionality to run tasks based on external inputs, and to dynamically generate applications, we had to do some complicated powershell scripting and save all our our input as files that the ui-path would open.

## Accomplishments that I'm proud of

Anyone can access the site and apply now! The whole site is connected to firebase and all users have their own storage and accounts immediately when logging into the platform.

## What I learned

It was our first times using redux and firebase and we covered almost all firebase functionality and implemented all of our website functions in redux so we ended up learning quite a bit. Shoutout to FreeCodeCamp!

## What's next for While(1);

Get our summer internships through this. If we use our own application enough times, then there's no limit to how many rejections you can get!
## Inspiration

As a team, we collectively brought in quite a few ideas, but this idea ranked higher than the others for its simple practicality. Especially living in an inconsistent place like Ontario, we know from first-hand experience that we sometimes make mistakes in bringing a jacket or not. We may not bring a jacket during the colder days, or bring one despite not needing it and having to hold it around for the rest of the day. We were interested in accessing a large source of information and using it for our purposes, like knowing if the weather will be too cold or not for a jacket/coat.

## What it does

The website will ask the user to enter their city name in the search bar, and upon clicking "enter", the weather stats of the current city will show up. Based on the temperature, the user will be told by the computer program if they'll require a winter coat, a regular jacket, or no outerwear depending on the weather conditions.

## How we built it

We prototyped on the front end taking into consideration of user interface and using web scraping, we were able to write the python code that will be able to access the weather stats on any city in the world, and access other important information like rain/cloudy/sunny.

## Challenges we ran into

We ran into some difficulties using an API originally, and debugging was quite the hassle until we discovered another way of accessing weather data for our intended purposes. As a team, this taught us to be able to be ready to shift gears and work on finding new adaptive solutions than meddling around for too long with logical error and implementation.

As well, we had a difficult time linking the python code to the front-end code, which is something we wish to have foreseen beforehand, and will be well aware of next time.

## Accomplishments that we're proud of

While the project is quite simple, and we did not count for some of the challenges that persisted, we did learn a lot about our own interests in code side projects, new technical terms like web scraping and APIs, and what to look out for in the future! It was also a breath of fresh air to step into coding where we could truly develop our own passion and knowledge outside the classroom, where normally some sorts of restrictions are placed.

## What we learned

As mentioned, we did learn about web scraping, APIs, and some python libraries we've never known before. This project required a lot of teamwork to diligently work on multiple aspects of the project at once, which allowed us to create a product that otherwise would have not been possible without a 1 personal team in our case.

## What's next Do you need a jacket?

For now, we're thinking of maybe developing it to include more features on weather stats and finding a way to connect both the front end and python code so we can simultaneously work on both aspects as equal parts. As well, we would like to specially include a feature to output a "sorry, this city does not exist" message if the user types in the wrong spelling of a city name.