Participants – Only for on-campus Technology students of Banasthali

Tracks/Broad Challenge Announcement

1. Server Side Engineering: 
Title: Dynamic Content Delivery for Regional Indian Languages

Objective:
Develop a server-side platform to deliver localized content, such as news, quotes, and stickers, dynamically based on the user’s language preference and location.

Key Aspects to Consider:

Content Recommendation Algorithms: Tailor recommendations to regional preferences including city, state, and country.
Efficient Content Delivery Infrastructure: Implement a robust system for fast and reliable content delivery.
Real-Time User Tracking and Analytics: Track user interactions and analyze data to enhance content delivery.

Technology Stack:
Content Delivery Network (CDN): Integration with a 3rd party CDN (e.g., Google Cloud CDN, Cloudinary).
APIs: Development of APIs for content recommendation and delivery based on user location and past interactions.
Database Schema: Design a schema to tag content and manage storage locations.
Web Demo: Build a demo showcasing personalized content delivery.

Submission Guidelines for this Step:
Idea Submission: Submit a detailed proposal outlining the technologies and frameworks you plan to use for content delivery, recommendation, and user analytics.
References: Include references to existing tools, services, or frameworks that will support your solution.
Repository: Drive/Github Link of POC done for idea submission.

2. Mobile Engineering:
Objective:
Develop an innovative Android application with two main verticals: Engagement and Recommendations. The goal is to improve productivity and overall user experience through an engaging game and personalized recommendations.

Technology Stack:
AI and Machine Learning: Basic usage of AI models from services like MonsterAPI
NLP: Basic NLP functionalities using pre-built models from Hugging Face or similar
Data Analysis: Firebase, Google Analytics for tracking user interactions
Frontend: Android SDK, Kotlin, Java
Backend: Firebase

Verticals Overview:
Vertical 1: Engagement
Goal: Provide users with engaging tools to manage stress and take productive breaks.
Feature: Catch the Falling Sky Emoji Game
Gameplay: Simple and intuitive, using the entire canvas of the Android device.
Emoji Falling: Various emojis fall from the top of the screen.
Catching Mechanism: Users catch emojis by tapping or swiping to earn points.
Accessibility: Playable on top of other applications.
Score Tracking: Track scores to encourage competition.

Vertical 2: Recommendations
Goal: Provide intelligent, intent-based recommendations based on user interactions.
Features:
Intent-Based Recommendations:
Contextual Understanding: Analyze user inputs to understand needs.
Personalized Suggestions: Recommend relevant content, products, and actions.
Next-Step Guidance: Suggest the next logical step in user interactions.
Interaction Tracking and Feedback:
User Activity Monitoring: Track interactions to understand preferences.
Feedback Loop: Use feedback to improve the recommendation algorithm.

Submission Guidelines for this Step:
Idea Submission: Submit a detailed proposal outlining the technologies and frameworks you plan to use for both the Engagement and Recommendations verticals.
References: Include references to existing research, tools, or frameworks that will support your solution.
Repository: Drive/Github Link of POC done for idea submission.

3. AI-Vision Challenge:
Welcome to the 3D Premium Stickers Challenge! This competition is focused on developing a system that generates high-quality 3D cartoon stickers based on image input and thematic prompts. 

Objective:
Develop a system that converts images into high-quality 3D cartoon stickers based on thematic prompts. The system should handle two inputs: an image to be converted and a prompt to set the theme.

Key Aspects to Consider:
Image Conversion: Transform real images into cartoon-style 3D stickers.
Prompt-Based Customization: Use thematic prompts to define the style and context of the stickers.
High Quality: Ensure the generated stickers are of premium quality.

Technology Stack:
AI and Machine Learning: Techniques for image processing and cartoon-style generation.
Prompt Engineering: Techniques for using text prompts to guide image transformation.

Submission Guidelines for this Step:
Idea Submission: Submit a proposal detailing your approach for image conversion and prompt-based customization.
Technology Overview: Outline the technologies, frameworks, and libraries you plan to use, including any relevant references.
Repository: Drive/Github Link of POC done for idea submission.

4. AI-NLP Challenge:
Objective:
Your initial task is to conceptualize and design a model that can accurately classify text into one of three tense categories: past, present, and future.

Problem Statement:
In our rapidly advancing world, understanding and processing natural language is becoming increasingly important. A key aspect of this is determining the tense of a sentence, which plays a crucial role in applications such as text analysis, machine translation, and more.

Your Task:
Tense Categories:
Past Tense: Sentences that describe events that have already occurred.
Present Tense: Sentences that describe events happening currently or regularly.
Future Tense: Sentences that describe events that will occur in the future.

Example Inputs and Outputs:

Input: "The company launched a new product last month."
Output: Past
Input: "She is studying for her final exams."
Output: Present
Input: "They will travel to Japan next year."
Output: Future
Broad Challenge Requirements:

Conceptual Design: Begin by designing a model that can classify sentences into the correct tense categories.
Consideration: Think about the subtleties of language and various ways tenses can be expressed.

Submission Guidelines for this Step
Idea Submission: Submit a detailed idea that outlines the technologies and frameworks you plan to use for the challenge.
References: Include proper references to any existing research, tools, or frameworks that will support your solution. This will demonstrate your understanding of the tools and techniques necessary for successful implementation.
Repository: Drive/Github Link of POC done for idea submission.

5. Data Challenge:
Objective: Your task is to conceptualize and design a scalable data engineering solution using advanced technologies that can handle high volumes of data efficiently.

Technology Stack:
Cloud Services: AWS/GCP
Data Processing: Big Data ETL tools like EMR, Glue, or DataProc
Data Models: Data schema design
Code Library: PySpark, SQL
Machine Learning: NLP, TensorFlow, Random Forest, etc.

Design Flow: You will need to create and set up automatic data processing pipelines on a Big Data platform.

Input Data: Format: High Volume JSON/CSV files

Output: Format: partitioned, structured Parquet data optimized for analysis

Use Cases:
Sample Events Data: Provided in JSON format
Task: Build structured event data that can be analyzed efficiently using any SQL platform.
Advanced Technologies: Utilizing technologies like Kafka streaming for real-time data analysis is encouraged.

Submission Guidelines for this Step:

Idea Submission: Submit a detailed proposal outlining the technologies and frameworks you plan to use.
References: Include proper references to existing research, tools, or frameworks that will support your solution.
Repository: Drive/Github Link of POC done for idea submission.