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Problem Statements

Title Description Stream Industry Required Skills
Quality inspection Leverage AI to automate quality control, creating a universal solution adaptable to diverse products, streamlining inspection processes, and improving overall quality assurance. Computer Vision Manufacturing Pytorch, OpenCV, YOLO, Numpy, UI/UX
Predictive Demand Forecasting (Ecommerce) Develop AI models for precise inventory predictions based on historical data, optimizing warehouse distribution to meet dynamic demand across different regions and time periods. Data Science Ecommerce Matplotlib, Scikit-learn, Pandas, NumPy, TensorFlow, Keras, UI/UX
Health report analyzer Challenge participants to develop AI solutions for text extraction with the capability to standardize diverse reports into a single format. The objective is to streamline data integration, ensuring uniformity and facilitating analysis across different report types. Computer Vision Healthcare Pytorch, OpenCV, YOLO, Numpy, UI/UX
Social Media Recommendation AI challenge focused on utilizing engagement data to build models for accurate post recommendations, aiming to improve user content discovery and satisfaction. Data Science Social media Matplotlib, Scikit-learn, Pandas, NumPy, TensorFlow, Keras, UI/UX
Best Photo Identifier Automate selecting the best photo from a video. For individuals, prioritize open eyes and ideal pose; for groups, consider expressions and overall composition. Computer Vision Entertainment Pytorch, OpenCV, YOLO, Numpy, UI/UX
Automated Detection of Cardiac Diseases using Artificial Intelligence in Resting 12-Lead ECG Recordings Diagnosing heart disease through manual interpretation of 12-lead electrocardiograms (ECGs) is time-consuming, prone to human error, and lacks consistency. This project addresses this challenge by developing an Artificial Intelligence (AI) system for automated and accurate detection of cardiac diseases in resting ECGs. Early Detection of Cardiac Anomalies: To significantly reduce the incidence of sudden cardiac arrest among young individuals by enabling early detection of symptoms that could lead to critical conditions if left unattended. Data Science Healthcare Matplotlib, Scikit-learn, Pandas, NumPy, TensorFlow, Keras, UI/UX

Judging Criteria

Criteria Weightage Criteria Weightage
Initial Ideation 5 Model Architecture Used and Accuracy of the Model 25
Dataset Creation 10 Scalability 5
Review Point after 1st Mentor Round 10 Mentor feedback implementation 5
Review Point after 2nd Mentor Round 10 Presentation 10
Innovation 10 Working Code and UI 10

Prerequisites

Software and Development Tools:
  1. Integrated Development Environment (IDE):
    • Visual Studio Code, PyCharm, or any preferred Python IDE
    • Jupyter Notebook is not allowed for Final Submission. You can use it for R&D and Prototyping.
  2. Programming Languages:
    • Ensure Python is installed, preferably the stable version.
  3. Version Control:
    • Git with a GitHub account for version control and repository submission.
  4. AI and Machine Learning Libraries:
    • Core libraries such as TensorFlow, PyTorch, Scikit-learn, OpenCV, Keras, and Pandas should be installed and tested.
    • Ensure compatibility with the operating system and the IDE being used.
  5. Data Processing and Visualization Tools:
    • Libraries like NumPy, Matplotlib, and Seaborn for data manipulation and visualization.
Software and Development Tools:
  1. Virtual Environment Management:
    • Conda (Anaconda or Miniconda) or Venv for managing dependencies.
  2. Web frameworks
    • Frameworks like Flask, Django, Node, PHP, etc. for UI and Final Deployment and Evaluation.
  3. Browser
    • Browsers like Chrome, Mozilla Firefox or any other browser.
  4. Presentation Software
    • PowerPoint, Google Slides, or similar software for preparing the final presentation.
  5. Zip Software
    • You must have a zip software to zip the folder for final submission
  6. Google Colab or Cloud Service (optional)
    • If you want to use GPU services of cloud or Google Colab that need to be installed
Hardware Requirements:
  1. Laptop: At least an i5 processor, 16GB RAM (32GB recommended), 50GB free storage, and preferably a dedicated GPU.
  2. Wifi Connectivity: The laptop must have a Wi-Fi connection.
  3. USB Pendrive: Essential for data transfer.
  4. Chargers and Power Banks: To keep devices powered throughout the event.
  5. Extension Board: Ensure enough power outlets for all devices.
Personal Belongings:
  1. Toiletries: Stay fresh and clean with travel-sized essentials.
  2. Extra Pair of Clothes: Stay comfortable and refreshed throughout the event.
  3. Blanket and Hoodie: Stay warm during breaks or overnight stays.
  4. Health and Safety Essentials: Prioritize your well-being with hand sanitiser, disinfectant wipes, and face masks.
  5. Reusable Water Bottle: Stay hydrated with a refillable water bottle.
  6. Personal Medications: Don't forget any prescription medications or necessary supplies.
  7. Positive Attitude: Bring your enthusiasm, creativity, and a positive mindset to the hackathon!