## Inspiration

Violence is running rampant in Canada, & even more so in many other places in the world. To address this insecurity, we devised the solution SafeWay, which guides us home safely.

## What it does

SafeWays is a webapp that allows you to browse your surroundings and also determines the safest and closest possible route you can take. This allows for easy and peaceful navigation even in unfamiliar places.

## How we built it

We used a front end stack of React with vanilla CSS that made api calls to the Google Maps API for the mapview & search function. There are two servers, one of which is a flask server that uses selenium to scrape the Ottawa Crime Map for data, & an express server that uses axios to query said server as well as Google Maps API & GeoNames to compile the raw data into useful data for the web application.

## Challenges we ran into

The Ottawa Crime Map had a lot of bloat, so it was hard to navigate in order to find out how to acquire the data we need. There was also discrepancy between location data, names in particular, between the Ottawa Crime Map's & Google Maps. Devising our own Map API was also a thrill.

## Accomplishments that we're proud of

Devising the web scraper to get data from the Ottawa Crime Map, which had so much bloat network IMO. Meshing together different Map APIs to create something new, example being getting all potential roads between two points. Last but not least, creating our mapview that we can call ours.

## What we learned

We learned how to scrape data from the monstrous government site, how to work with maps & their respective APIs, as well as struggle with CORS. We also learned that there is a lot of crime & we should try to stay safe out there.

## What's next for SafeWays

As availability of crime data varies in format across municipalities, we wish to devise a standard protocol to centralize these data, & whilst doing so improve its feature by having more frequent & detailed updates that are based on individual events, as these seem to be updated within set intervals. With that, we would also be able to implement Solace. Another step would be to implement a feature that actually highlights redzones or something of the like to sort of show the severity of crimes in areas.
## Inspiration

As young adults who are new to a large metropolitan area, we are constantly hearing people tell us to avoid the sketchy areas of the city. Quite frankly, we don't always know where those areas are. This is what inspired AwareWolf. We wanted to create an app that will let both locals and tourists determine whether surrounding areas are dangerous.

## What it does

AwareWolf is a web application that crowdsources user-inputted crime reports to alert users of dangers within the surrounding areas. When users notice a crime, they can input information about the crime and where it occurred. The report will populate a heat map. The points will get brighter as more users report the same crime. Crimes that can be reported include robberies, shootings, harassment incidents, and drug usage. Users can then use the map to potentially reroute themselves to avoid those dangerous areas.

## How we built it

We started a simple Python script that utilized Flask. Most of our scripting was done using JavaScript. For our map feature, we used the Google Maps API. The website is hosted through Microsoft Azure but is currently running as a local host. To complete that, we had to create a remote git repository. The website itself was designed with CSS and HTML to create a user-friendly UI.

## Challenges we ran into

None of us were very familiar with CSS or HTML. We had to learn how to create more advanced animation and design to present an aesthetically-pleasing and user-friendly UI. We were also not familiar with Microsoft Azure services. It was big learning curve to create the application and include the proper repositories with correct accesses. Another challenge was creating the map using the Google Maps API. We had to apply advanced JavaScript knowledge to create a function that would allow the points to still appear on the map even if the page was refreshed.

## Accomplishments that we're proud of

All of us have times when we are wary of our surroundings and aren't sure if we are safe. We are proud to have a finished product that can eliminate this feeling and potentially keep millions of people out of danger. Our team also realized that 36 hours really isn't that long. Debugging took up the majority of our time. We also challenged ourselves to create new functionality based on already-existing source code for the Google Maps API.

## What we learned

The majority of the team had little to no CSS and HTML knowledge, so we utilized Bootstrap. We also had to familiarize ourselves with the Google Maps API and how to integrate that into our HTML design. We furthered our knowledge of JavaScript by utilizing that scripting language for the bulk of application.

## What's next for AwareWolf

The next step would be to create a mobile app. We hope to further incorporate the Google Maps API so that users can create routes that will avoid the dangerous areas and then utilize those routes to avoid the dangerous areas.
**In times of disaster, there is an outpouring of desire to help from the public. We built a platform which connects people who want to help with people in need.**

## Inspiration

Natural disasters are an increasingly pertinent global issue which our team is quite concerned with. So when we encountered the IBM challenge relating to this topic, we took interest and further contemplated how we could create a phone application that would directly help with disaster relief.

## What it does

**Stronger Together** connects people in need of disaster relief with local community members willing to volunteer their time and/or resources. Such resources include but are not limited to shelter, water, medicine, clothing, and hygiene products. People in need may input their information and what they need, and volunteers may then use the app to find people in need of what they can provide. For example, someone whose home is affected by flooding due to Hurricane Florence in North Carolina can input their name, email, and phone number in a request to find shelter so that this need is discoverable by any volunteers able to offer shelter. Such a volunteer may then contact the person in need through call, text, or email to work out the logistics of getting to the volunteer’s home to receive shelter.

## How we built it

We used Android Studio to build the Android app. We deployed an Azure server to handle our backend(Python). We used Google Maps API on our app. We are currently working on using Twilio for communication and IBM watson API to prioritize help requests in a community.

## Challenges we ran into

Integrating the Google Maps API into our app proved to be a great challenge for us. We also realized that our original idea of including a blood donation as one of the resources would require some correspondence with an organization such as the Red Cross in order to ensure the donation would be legal. Thus, we decided to add a blood donation to our future aspirations for this project due to the time constraint of the hackathon.

## Accomplishments that we're proud of

We are happy with our design and with the simplicity of our app. We learned a great deal about writing the server side of an app and designing an Android app using Java (and Google Map’s API” during the past 24 hours. We had huge aspirations and eventually we created an app that can potentially save people’s lives.

## What we learned

We learned how to integrate Google Maps API into our app. We learn how to deploy a server with Microsoft Azure. We also learned how to use Figma to prototype designs.

## What's next for Stronger Together

We have high hopes for the future of this app. The goal is to add an AI based notification system which alerts people who live in a predicted disaster area. We aim to decrease the impact of the disaster by alerting volunteers and locals in advance. We also may include some more resources such as blood donations.