All That You Need to Know About Kriyeta 4.0 (National Level Hackathon) : Sponsored by IEEE Humanitarian Technologies and eInfochips 

About:

Kriyeta 4.0 is a nationwide stage that instills a culture of innovation and motivates youth to develop a problem-solving mindset in a competitive energy environment that facilitates rapid development. Create, innovate, learn, and discover in a time-constrained coding event that gives the nation's brightest minds a chance to showcase their skills and try their hand at solving problems often faced by the masses.

Other Details:

Date: April 18th - 20th, 2025 (48-Hour Hackathon)
Location: Acropolis Institute of Technology and Research - AITR, Indore
Platform: As this is a coding opportunity, you can use any platform for coding on your laptop within the premises, such as VSCode, Sublime, GitHub, etc.

Domains : 

• Sustainable Technologies
• Healthcare Innovation
• AI and Emerging Technologies
• Agriculture and Food Security

Problem Statement:

• Domain: Sustainable Technologies: Agentic AI Assistant for Sustainable Urban Mobility Planning
  • Problem Statement: Design an Agentic AI solution that helps city planners or citizens plan eco-friendly travel using real-world constraints like public transport availability, distance, cost, and CO2 emissions. Agents can compare options (e.g., bike vs cab), optimize based on user goals (fastest vs greenest), and simulate outcomes.
  • Expected Outcome: A travel planner tool: user inputs start/end → agents compare routes, emissions, cost, and recommend best green option
• Smart AI Assistant for Home Energy Optimization
  • Problem Statement: Build a smart assistant that takes simulated home energy consumption data (CSV/mock API) and uses AI to analyze usage patterns, detect wastage, and recommend personalized optimization strategies. It should generate a daily or weekly tip in natural language using LLMs.
  • Expected Outcome: AI-based dashboard + recommendation engine + mock data pipeline
• Domain : Healthcare Innovation: Agentic AI Framework for Hospital Workflow Automation
  • Problem Statement: Design a multi-agent AI system using Microsoft AutoGen to simulate an Agentic AI workforce for hospital workflows such as appointment scheduling, EMR data retrieval, and billing validation. Agents should be autonomous, communicate with each other, and collectively complete a task.
  • Expected Outcome: End-to-end working demo with 2–3 agents automating tasks like patient appointment + EMR fetch + billing info.
• Agentic AI-Based Personalized Health Coach for Preventive Care
  • Problem Statement: Design an Agentic AI system using Microsoft AutoGen to simulate a personalized health coach that helps users reduce risks of chronic conditions (e.g., diabetes, hypertension). The AI agents should work together to assess user risk, recommend personalized lifestyle changes, and provide motivational feedback over time.
  • Expected Outcome: A multi-agent health advisory platform: profile intake → risk analysis → AI-generated recommendations + follow-up agent.
• Domain : AI and Emerging Technologies: Multi-Agent Communication Framework
  • Problem Statement: Design a reusable framework using Microsoft AutoGen to simulate collaboration between multiple AI agents (e.g., planner, summarizer, validator) to solve complex tasks. The framework should be modular, allowing users to plug in new agent types and control the task flow via config.
  • Expected Outcome: A modular agent collaboration framework with 2-3 sample task flows (e.g., text summarization, Q&A pipeline)
• Agentic AI Framework for Smart Email Triage and Action Automation
  • Problem Statement: Create a reusable platform using Agentic AI where agents collaboratively classify incoming emails (mock or real), extract action items, assign them to categories (e.g., meetings, follow-ups, approvals), and generate suggested responses or summaries. Useful for overloaded professionals and internal use.
  • Expected Outcome: An end-to-end email triage assistant that tags, summarizes, and drafts replies via interacting agents
• Domain : Agriculture and Food Security: AI- Powered Pest Control System
  • Problem Statement: Develop an AI-driven pest detection system that analyzes real-time images from drones or mobile devices to identify harmful pests. The system should provide early warnings and suggest eco-friendly solutions to mitigate pest attacks.
  • Expected Outcome: Enhances pest detection, minimizes crop loss, and promotes eco-friendly pest management.
• Food Waste Management and Redistribution Platform
  • Problem Statement: Build a tech-enabled food waste management system that connects farmers, retailers, and NGOs to track, reduce, and redistribute surplus food to people in need. The system should include AI-powered demand forecasting to prevent food wastage.

Objective: Reduces food wastage, optimizes redistribution, and contributes to hunger alleviation.