## Inspiration

In the exciting world of hackathons, where innovation meets determination, **participants like ourselves often ask "Has my idea been done before?"** While originality is the cornerstone of innovation, there's a broader horizon to explore - the evolution of an existing concept. Through our AI-driven platform, hackers can gain insights into the uniqueness of their ideas. By identifying gaps or exploring similar projects' functionalities, participants can aim to refine, iterate, or even revolutionize existing concepts, ensuring that their projects truly stand out.

For **judges, the evaluation process is daunting.** With a multitude of projects to review in a short time frame, ensuring an impartial and comprehensive assessment can become extremely challenging. The introduction of an AI tool doesn't aim to replace the human element but rather to enhance it. By swiftly and objectively analyzing projects based on certain quantifiable metrics, judges can allocate more time to delve into the intricacies, stories, and the passion driving each team

## What it does

This project is a smart tool designed for hackathons. The tool measures the similarity and originality of new ideas against similar projects if any exist, we use web scraping and OpenAI to gather data and draw conclusions.

**For hackers:**

* **Idea Validation:** Before diving deep into development, participants can ascertain the uniqueness of their concept, ensuring they're genuinely breaking new ground.
* **Inspiration:** By observing similar projects, hackers can draw inspiration, identifying ways to enhance or diversify their own innovations.

**For judges:**

* **Objective Assessment:** By inputting a project's Devpost URL, judges can swiftly gauge its novelty, benefiting from AI-generated metrics that benchmark it against historical data.
* **Informed Decisions:** With insights on a project's originality at their fingertips, judges can make more balanced and data-backed evaluations, appreciating true innovation.

## How we built it

**Frontend:** Developed using React JS, our interface is user-friendly, allowing for easy input of ideas or Devpost URLs.

**Web Scraper:** Upon input, our web scraper dives into the content, extracting essential information that aids in generating objective metrics.

**Keyword Extraction with ChatGPT:** OpenAI's ChatGPT is used to detect keywords from the Devpost project descriptions, which are used to capture project's essence.

**Project Similarity Search:** Using the extracted keywords, we query Devpost for similar projects. It provides us with a curated list based on project relevance.

**Comparison & Analysis:** Each incoming project is meticulously compared with the list of similar ones. This analysis is multi-faceted, examining the number of similar projects and the depth of their similarities.

**Result Compilation:** Post-analysis, we present users with an 'originality score' alongside explanations for the determined metrics, keeping transparency.

**Output Display:** All insights and metrics are neatly organized and presented on our frontend website for easy consumption.

## Challenges we ran into

**Metric Prioritization:** Given the timeline restricted nature of a hackathon, one of the first challenges was deciding which metrics to prioritize. Striking the balance between finding meaningful data points that were both thorough and feasible to attain were crucial.

**Algorithmic Efficiency:** We struggled with concerns over time complexity, especially with potential recursive scenarios. Optimizing our algorithms, prompt engineering, and simplifying architecture was the solution.

*Finding a good spot to sleep.*

## Accomplishments that we're proud of

We took immense pride in developing a solution directly tailored for an environment we're deeply immersed in. By crafting a tool for hackathons, while participating in one, we felt showcases our commitment to enhancing such events. Furthermore, not only did we conceptualize and execute the project, but we also established a robust framework and thoughtfully designed architecture from scratch.

Another general Accomplishment was our team's synergy. We made efforts to ensure alignment, and dedicated time to collectively invest in and champion the idea, ensuring everyone was on the same page and were equally excited and comfortable with the idea. This unified vision and collaboration were instrumental in bringing HackAnalyzer to life.

## What we learned

We delved into the intricacies of full-stack development, gathering hands-on experience with databases, backend and frontend development, as well as the integration of AI. Navigating through API calls and using web scraping were also some key takeaways. Prompt Engineering taught us to meticulously balance the trade-offs when leveraging AI, especially when juggling cost, time, and efficiency considerations.

## What's next for HackAnalyzer

We aim to amplify the metrics derived from the Devpost data while enhancing the search function's efficiency. Our secondary and long-term objective is to transition the application to a mobile platform. By enabling students to generate a QR code, judges can swiftly access HackAnalyzer data, ensuring a more streamlined and effective evaluation process.
# The Ultimate Water Heater

February 2018

## Authors

This is the TreeHacks 2018 project created by Amarinder Chahal and Matthew Chan.

## About

Drawing inspiration from a diverse set of real-world information, we designed a system with the goal of efficiently utilizing only electricity to heat and pre-heat water as a means to drastically save energy, eliminate the use of natural gases, enhance the standard of living, and preserve water as a vital natural resource.

Through the accruement of numerous API's and the help of countless wonderful people, we successfully created a functional prototype of a more optimal water heater, giving a low-cost, easy-to-install device that works in many different situations. We also empower the user to control their device and reap benefits from their otherwise annoying electricity bill. But most importantly, our water heater will prove essential to saving many regions of the world from unpredictable water and energy crises, pushing humanity to an inevitably greener future.

Some key features we have:

* 90% energy efficiency
* An average rate of roughly 10 kW/hr of energy consumption
* Analysis of real-time and predictive ISO data of California power grids for optimal energy expenditure
* Clean and easily understood UI for typical household users
* Incorporation of the Internet of Things for convenience of use and versatility of application
* Saving, on average, 5 gallons per shower, or over ****100 million gallons of water daily****, in CA alone. \*\*\*
* Cheap cost of installation and immediate returns on investment

## Inspiration

By observing the RhoAI data dump of 2015 Californian home appliance uses through the use of R scripts, it becomes clear that water-heating is not only inefficient but also performed in an outdated manner. Analyzing several prominent trends drew important conclusions: many water heaters become large consumers of gasses and yet are frequently neglected, most likely due to the trouble in attaining successful installations and repairs.

So we set our eyes on a safe, cheap, and easily accessed water heater with the goal of efficiency and environmental friendliness. In examining the inductive heating process replacing old stovetops with modern ones, we found the answer. It accounted for every flaw the data decried regarding water-heaters, and would eventually prove to be even better.

## How It Works

Our project essentially operates in several core parts running simulataneously:

* Arduino (101)
* Heating Mechanism
* Mobile Device Bluetooth User Interface
* Servers connecting to the IoT (and servicing via Alexa)
Repeat all processes simultaneously

The Arduino 101 is the controller of the system. It relays information to and from the heating system and the mobile device over Bluetooth. It responds to fluctuations in the system. It guides the power to the heating system. It receives inputs via the Internet of Things and Alexa to handle voice commands (through the "shower" application). It acts as the peripheral in the Bluetooth connection with the mobile device. Note that neither the Bluetooth connection nor the online servers and webhooks are necessary for the heating system to operate at full capacity.

The heating mechanism consists of a device capable of heating an internal metal through electromagnetic waves. It is controlled by the current (which, in turn, is manipulated by the Arduino) directed through the breadboard and a series of resistors and capacitors. Designing the heating device involed heavy use of applied mathematics and a deeper understanding of the physics behind inductor interference and eddy currents. The calculations were quite messy but mandatorily accurate for performance reasons--Wolfram Mathematica provided inhumane assistance here. ;)

The mobile device grants the average consumer a means of making the most out of our water heater and allows the user to make informed decisions at an abstract level, taking away from the complexity of energy analysis and power grid supply and demand. It acts as the central connection for Bluetooth to the Arduino 101. The device harbors a vast range of information condensed in an effective and aesthetically pleasing UI. It also analyzes the current and future projections of energy consumption via the data provided by California ISO to most optimally time the heating process at the swipe of a finger.

The Internet of Things provides even more versatility to the convenience of the application in Smart Homes and with other smart devices. The implementation of Alexa encourages the water heater as a front-leader in an evolutionary revolution for the modern age.

## Built With:

(In no particular order of importance...)

* RhoAI
* R
* Balsamiq
* C++ (Arduino 101)
* Node.js
* Tears
* HTML
* Alexa API
* Swift, Xcode
* BLE
* Buckets and Water
* Java
* RXTX (Serial Communication Library)
* Mathematica
* MatLab (assistance)
* Red Bull, Soylent
* Tetrix (for support)
* Home Depot
* Electronics Express
* Breadboard, resistors, capacitors, jumper cables
* Arduino Digital Temperature Sensor (DS18B20)
* Electric Tape, Duct Tape
* Funnel, for testing
* Excel
* Javascript
* jQuery
* Intense Sleep Deprivation
* The wonderful support of the people around us, and TreeHacks as a whole. Thank you all!

\*\*\* According to the Washington Post: <https://www.washingtonpost.com/news/energy-environment/wp/2015/03/04/your-shower-is-wasting-huge-amounts-of-energy-and-water-heres-what-to-do-about-it/?utm_term=.03b3f2a8b8a2>

Special thanks to our awesome friends Michelle and Darren for providing moral support in person!
## Inspiration

At work, conference calls usually involves multiple people on one side using the same microphone. It may be hard to know who's speaking and what their role is. Furthermore, some details of the meeting can be lost and it's tedious to note everything down.

## What it does

Our app distinguishes/recognizes speakers, shows who's speaking and automatically transcribe the meeting in real time. When the meeting ends, our app can also export the meeting minutes (log of who said what at what time).

**Features**:

* display who's currently speaking using speaker recognition
* transcribe what's being said by who like a chat application
* create and train a new speaker profile within 15 seconds
* stream transcription to services such as `Slack`
* export transcription to cloud storage such as `Google Sheets`

## How I built it

* Microsoft Speech Recognition API
* Microsoft Speech to Text API
* Google Cloud Speech to Text API
* Google Sheets API
* Slack API
* stdlib for integrating services for the backend such as Slack and SMS
* NodeJS with Express for the backend
* Vue for the frontend
* Python scripts for accessing Microsoft's APIs
* Love ❤️

## Challenges I ran into

Generating the audio file in the right format for Microsoft's API was tougher than expected; seems like Mac's proprietary microphone isn't able to format the audio in the way Microsoft wants it.

## Accomplishments that I'm proud of

* Learning how to use the APIs, Microsoft Azure, and sampling an audio input to a format the API needs.
* Finishing an app before the deadline.

## What I learned

Usage of many APIs, speech recording, and integration of multiple services.

## What's next for Who Said What?

A year long worldwide tour to show.