## Inspiration

One of our own member's worry about his puppy inspired us to create this project, so he could keep an eye on him.

## What it does

Our app essentially monitors your dog(s) and determines their mood/emotional state based on their sound and body language, and optionally notifies the owner about any changes in it. Specifically, if the dog becomes agitated for any reasons, manages to escape wherever they are supposed to be, or if they fall asleep or wake up.

## How we built it

We built the behavioral detection using OpenCV and TensorFlow with a publicly available neural network. The notification system utilizes the Twilio API to notify owners via SMS. The app's user interface was created using JavaScript, CSS, and HTML.

## Challenges we ran into

We found it difficult to identify the emotional state of the dog using only a camera feed. Designing and writing a clean and efficient UI that worked with both desktop and mobile platforms was also challenging.

## Accomplishments that we're proud of

Our largest achievement was determining whether the dog was agitated, sleeping, or had just escaped using computer vision. We are also very proud of our UI design.

## What we learned

We learned some more about utilizing computer vision and neural networks.

## What's next for PupTrack

KittyTrack, possibly
Improving the detection, so it is more useful for our team member
## Inspiration 💡

**Due to rising real estate prices, many students are failing to find proper housing, and many landlords are failing to find good tenants**. Students looking for houses often have to hire some agent to get a nice place with a decent landlord. The same goes for house owners who need to hire agents to get good tenants. *The irony is that the agent is totally motivated by sheer commission and not by the wellbeing of any of the above two.*

Lack of communication is another issue as most of the things are conveyed by a middle person. It often leads to miscommunication between the house owner and the tenant, as they interpret the same rent agreement differently.

Expensive and time-consuming background checks of potential tenants are also prevalent, as landowners try to use every tool at their disposal to know if the person is really capable of paying rent on time, etc. Considering that current rent laws give tenants considerable power, it's very reasonable for landlords to perform background checks!

Existing online platforms can help us know which apartments are vacant in a locality, but they don't help either party know if the other person is really good! Their ranking algorithms aren't trustable with tenants. The landlords are also reluctant to use these services as they need to manually review applications from thousands of unverified individuals or even bots!

We observed that we are still using these old-age non-scalable methods to match the home seeker and homeowners willing to rent their place in this digital world! And we wish to change it with **RentEasy!**

![Tech-Stack](https://ipfs.infura.io/ipfs/QmRco7zU8Vd9YFv5r9PYKmuvsxxL497AeHSnLiu8acAgCk)

## What it does 🤔

In this hackathon, we built a cross-platform mobile app that is trustable by both potential tenants and house owners.

The app implements a *rating system* where the students/tenants can give ratings for a house/landlord (ex: did not pay security deposit back for no reason), & the landlords can provide ratings for tenants (the house was not clean). In this way, clean tenants and honest landlords can meet each other.

This platform also helps the two stakeholders build an easily understandable contract that will establish better trust and mutual harmony. The contract is stored on an InterPlanetary File System (IPFS) and cannot be tampered by anyone.

![Tech-Stack](https://ipfs.infura.io/ipfs/QmezGvDFVXWHP413JFke1eWoxBnpTk9bK82Dbu7enQHLsc)

Our application also has an end-to-end encrypted chatting module powered by @ Company. The landlords can filter through all the requests and send requests to tenants. This chatting module powers our contract generator module, where the two parties can discuss a particular agreement clause and decide whether to include it or not in the final contract.

## How we built it ️⚙️

Our beautiful and elegant mobile application was built using a cross-platform framework flutter.

We integrated the Google Maps SDK to build a map where the users can explore all the listings and used geocoding API to encode the addresses to geopoints.

We wanted our clients a sleek experience and have minimal overhead, so we exported all network heavy and resource-intensive tasks to firebase cloud functions. Our application also has a dedicated **end to end encrypted** chatting module powered by the **@-Company** SDK. The contract generator module is built with best practices and which the users can use to make a contract after having thorough private discussions. Once both parties are satisfied, we create the contract in PDF format and use Infura API to upload it to IPFS via the official [Filecoin gateway](https://www.ipfs.io/ipfs)

![Tech-Stack](https://ipfs.infura.io/ipfs/QmaGa8Um7xgFJ8aa9wcEgSqAJZjggmVyUW6Jm5QxtcMX1B)

## Challenges we ran into 🧱

1. It was the first time we were trying to integrate the **@-company SDK** into our project. Although the SDK simplifies the end to end, we still had to explore a lot of resources and ask for assistance from representatives to get the final working build. It was very gruelling at first, but in the end, we all are really proud of having a dedicated end to end messaging module on our platform.
2. We used Firebase functions to build scalable serverless functions and used expressjs as a framework for convenience. Things were working fine locally, but our middleware functions like multer, urlencoder, and jsonencoder weren't working on the server. It took us more than 4 hours to know that "Firebase performs a lot of implicit parsing", and before these middleware functions get the data, Firebase already had removed them. As a result, we had to write the low-level encoding logic ourselves! After deploying these, the sense of satisfaction we got was immense, and now we appreciate millions of open source packages much more than ever.

## Accomplishments that we're proud of ✨

We are proud of finishing the project on time which seemed like a tough task as we started working on it quite late due to other commitments and were also able to add most of the features that we envisioned for the app during ideation. Moreover, we learned a lot about new web technologies and libraries that we could incorporate into our project to meet our unique needs. We also learned how to maintain great communication among all teammates. Each of us felt like a great addition to the team. From the backend, frontend, research, and design, we are proud of the great number of things we have built within 36 hours. And as always, working overnight was pretty fun! :)

---

## Design 🎨

We were heavily inspired by the revised version of **Iterative** design process, which not only includes visual design, but a full-fledged research cycle in which you must discover and define your problem before tackling your solution & then finally deploy it.

![Double-Diamond](https://ipfs.infura.io/ipfs/QmPDLVVpsJ9NvJZU2SdaKoidUZNSDJPhC2SQAB8Hh66ZDf)

This time went for the minimalist **Material UI** design. We utilized design tools like Figma, Photoshop & Illustrator to prototype our designs before doing any coding. Through this, we are able to get iterative feedback so that we spend less time re-writing code.

![Brand-identity](https://ipfs.infura.io/ipfs/QmUriwycp6S98HtsA2KpVexLz2CP3yUBmkbwtwkCszpq5P)

---

# Research 📚

Research is the key to empathizing with users: we found our specific user group early and that paves the way for our whole project. Here are few of the resources that were helpful to us —

* Legal Validity Of A Rent Agreement : <https://bit.ly/3vCcZfO>
* 2020-21 Top Ten Issues Affecting Real Estate : <https://bit.ly/2XF7YXc>
* Landlord and Tenant Causes of Action: "When Things go Wrong" : <https://bit.ly/3BemMtA>
* Landlord-Tenant Law : <https://bit.ly/3ptwmGR>
* Landlord-tenant disputes arbitrable when not covered by rent control : <https://bit.ly/2Zrpf7d>
* What Happens If One Party Fails To Honour Sale Agreement? : <https://bit.ly/3nr86ST>
* When Can a Buyer Terminate a Contract in Real Estate? : <https://bit.ly/3vDexWO>

**CREDITS**

* Design Resources : Freepik, Behance
* Icons : Icons8
* Font : Semibold / Montserrat / Roboto / Recoleta

---

# Takeways

## What we learned 🙌

**Sleep is very important!** 🤐 Well, jokes apart, this was an introduction to **Web3** & **Blockchain** technologies for some of us and introduction to mobile app developent to other. We managed to improve on our teamwork by actively discussing how we are planning to build it and how to make sure we make the best of our time. We learned a lot about atsign API and end-to-end encryption and how it works in the backend. We also practiced utilizing cloud functions to automate and ease the process of development.

## What's next for RentEasy 🚀

**We would like to make it a default standard of the housing market** and consider all the legal aspects too! It would be great to see rental application system more organized in the future. We are planning to implement more additional features such as landlord's view where he/she can go through the applicants and filter them through giving the landlord more options. Furthermore we are planning to launch it near university campuses since this is where people with least housing experience live. Since the framework we used can be used for any type of operating system, it gives us the flexibility to test and learn.

**Note** — **API credentials have been revoked. If you want to run the same on your local, use your own credentials.**
## Inspiration

Cute factor of dogs/cats, also to improve the health of many pets such as larger dogs that can easily become overweight.

## What it does

Reads accelerometer data on collar, converted into steps.

## How I built it

* Arduino Nano
* ADXL345 module
* SPP-C Bluetooth module
* Android Studio for app

## Challenges I ran into

Android studio uses a large amount of RAM space.
Interfacing with the accelerometer was challenging with finding the appropriate algorithm that has the least delay and lag.

## Accomplishments that I'm proud of

As a prototype, it is a great first development.

## What I learned

Some android studio java shortcuts/basics

## What's next for DoogyWalky

Data analysis with steps to convert to calories, and adding a second UI for graphing data weekly and hourly with a SQLite Database.