## Inspiration

Enabling Accessible Transportation for Those with Disabilities
AccessRide is a cutting-edge website created to transform the transportation experience for those with impairments. We want to offer a welcoming, trustworthy, and accommodating ride-hailing service that is suited to the particular requirements of people with mobility disabilities since we are aware of the special obstacles they encounter.

## What it does

Our goal is to close the accessibility gap in the transportation industry and guarantee that everyone has access to safe and practical travel alternatives. We link passengers with disabilities to skilled, sympathetic drivers who have been educated to offer specialised assistance and fulfill their particular needs using the AccessRide app.
Accessibility:-
The app focuses on ensuring accessibility for passengers with disabilities by offering vehicles equipped with wheelchair ramps or lifts, spacious interiors, and other necessary accessibility features.
Specialized Drivers:-
The app recruits drivers who are trained to provide assistance and support to passengers with disabilities. These drivers are knowledgeable about accessibility requirements and are
committed to delivering a comfortable experience.
Customized Preferences:-
Passengers can specify their particular needs and preferences within the app, such as requiring a wheelchair-accessible vehicle, additional time for boarding and alighting, or any specific assistance required during the ride.
Real-time Tracking:-
Passengers can track the location of their assigned vehicle in real-time, providing peace of mind and ensuring they are prepared for pick-up.
Safety Measures:-
The app prioritizes passenger safety by conducting driver background checks, ensuring proper vehicle maintenance, and implementing safety protocols to enhance the overall travel experience.
Seamless Payment:-
The app offers convenient and secure payment options, allowing passengers to complete their transactions electronically, reducing the need for physical cash handling

## How we built it

We built it using django, postgreSQL and Jupyter Notebook for driver selection

## Challenges we ran into

Ultimately, the business impact of AccessRide stems from its ability to provide a valuable and inclusive service to people with disabilities. By prioritizing their needs and ensuring a comfortable and reliable transportation experience, the app can drive customer loyalty, attract new users, and make a positive social impact while growing as a successful business.
To maintain quality service, AccessRide includes a feedback and rating system. This allows passengers to provide feedback on their experience and rate drivers based on their level of assistance, vehicle accessibility, and overall service quality. It was a challenging part in this event.

## Accomplishments that we're proud of

We are proud that we completed our project. We look forward to develop more projects.

## What we learned

We learned about the concepts of django and postgreSQL. We also learnt many algorithms in machine learning and implemented it as well.

## What's next for Accessride-Comfortable ride for all abilities

In conclusion, AccessRide is an innovative and groundbreaking project that aims to transform the transportation experience for people with disabilities. By focusing on accessibility, specialized driver training, and a machine learning algorithm, the app sets itself apart from traditional ride-hailing services. It creates a unique platform that addresses the specific needs of passengers with disabilities and ensures a comfortable, reliable, and inclusive transportation experience.

## Your Comfort, Our Priority "Ride with Ease, Ride with Comfort“
## Inspiration

One of our teammate’s grandfathers suffers from diabetic retinopathy, which causes severe vision loss.
Looking on a broader scale, over 2.2 billion people suffer from near or distant vision impairment worldwide. After examining the issue closer, it can be confirmed that the issue disproportionately affects people over the age of 50 years old. We wanted to create a solution that would help them navigate the complex world independently.

## What it does

### Object Identification:

Utilizes advanced computer vision to identify and describe objects in the user's surroundings, providing real-time audio feedback.

### Facial Recognition:

It employs machine learning for facial recognition, enabling users to recognize and remember familiar faces, and fostering a deeper connection with their environment.

### Interactive Question Answering:

Acts as an on-demand information resource, allowing users to ask questions and receive accurate answers, covering a wide range of topics.

### Voice Commands:

Features a user-friendly voice command system accessible to all, facilitating seamless interaction with the AI assistant: Sierra.

## How we built it

* Python
* OpenCV
* GCP & Firebase
* Google Maps API, Google Pyttsx3, Google’s VERTEX AI Toolkit (removed later due to inefficiency)

## Challenges we ran into

* Slow response times with Google Products, resulting in some replacements of services (e.g. Pyttsx3 was replaced by a faster, offline nlp model from Vosk)
* Due to the hardware capabilities of our low-end laptops, there is some amount of lag and slowness in the software with average response times of 7-8 seconds.
* Due to strict security measures and product design, we faced a lack of flexibility in working with the Maps API. After working together with each other and viewing some tutorials, we learned how to integrate Google Maps into the dashboard

## Accomplishments that we're proud of

We are proud that by the end of the hacking period, we had a working prototype and software. Both of these factors were able to integrate properly. The AI assistant, Sierra, can accurately recognize faces as well as detect settings in the real world. Although there were challenges along the way, the immense effort we put in paid off.

## What we learned

* How to work with a variety of Google Cloud-based tools and how to overcome potential challenges they pose to beginner users.
* How to connect a smartphone to a laptop with a remote connection to create more opportunities for practical designs and demonstrations.
How to connect a smartphone to a laptop with a remote connection to create more opportunities for practical designs and demonstrations.
How to create docker containers to deploy google cloud-based flask applications to host our dashboard.
How to develop Firebase Cloud Functions to implement cron jobs. We tried to developed a cron job that would send alerts to the user.

## What's next for Saight

### Optimizing the Response Time

Currently, the hardware limitations of our computers create a large delay in the assistant's response times. By improving the efficiency of the models used, we can improve the user experience in fast-paced environments.

### Testing Various Materials for the Mount

The physical prototype of the mount was mainly a proof-of-concept for the idea. In the future, we can conduct research and testing on various materials to find out which ones are most preferred by users. Factors such as density, cost and durability will all play a role in this decision.
## Inspiration

We were inspired to create such a project since we are all big fans of 2D content, yet have no way of actually animating 2D movies. Hence, the idea for StoryMation was born!

## What it does

Given a text prompt, our platform converts it into a fully-featured 2D animation, complete with music, lots of action, and amazing-looking sprites! And the best part? This isn't achieved by calling some image generation API to generate a video for our movie; instead, we call on such APIs to create lots of 2D sprites per scene, and then leverage the power of LLMs (CoHere) to move those sprites around in a fluid and dynamic matter!

## How we built it

On the frontend we used React and Tailwind, whereas on the backend we used Node JS and Express. However, for the actual movie generation, we used a massive, complex pipeline of AI-APIs. We first use Cohere to split the provided story plot into a set of scenes. We then use another Cohere API call to generate a list of characters, and a lot of their attributes, such as their type, description (for image gen), and most importantly, Actions. Each "Action" consists of a transformation (translation/rotation) in some way, and by interpolating between different "Actions" for each character, we can integrate them seamlessly into a 2D animation.

This framework for moving, rotating and scaling ALL sprites using LLMs like Cohere is what makes this project truly stand out. Had we used an Image Generation API like SDXL to simply generate a set of frames for our "video", we would have ended up with a janky stop-motion video. However, we used Cohere in a creative way, to decide where and when each character should move, scale, rotate, etc. thus ending up with a very smooth and human-like final 2D animation.

## Challenges we ran into

Since our project is very heavily reliant on BETA parts of Cohere for many parts of its pipeline, getting Cohere to fit everything into the strict JSON prompts we had provided, despite the fine-tuning, was often quite difficult.

## Accomplishments that we're proud of

In the end, we were able to accomplish what we wanted!