NioHack2026
Problem Statements
- AI for Healthcare and Human Well-being (Develop intelligent solutions that leverage AI, computer vision, IoT, wearable devices, or multimodal data to improve disease diagnosis, patient monitoring, rehabilitation, mental health, accessibility, and personalized healthcare).
- Smart Cities, Transportation, and Sustainable Infrastructure (Design AI- and IoT-enabled systems to improve transportation, road safety, smart infrastructure, environmental monitoring, energy efficiency, disaster management, and sustainable urban living).
- Cybersecurity, Digital Forensics, and Privacy (Build innovative solutions for secure digital ecosystems using AI, ethical hacking, privacy-preserving technologies, blockchain, federated learning, digital forensics, and cyber threat intelligence).
- Intelligent Robotics, Automation, and Smart Manufacturing (Create autonomous robots, drones, industrial automation systems, digital twins, predictive maintenance, intelligent inspection, and AI-powered manufacturing solutions for Industry 4.0).
- Smart Communication, IoT, and Edge Computing (Develop next-generation communication and embedded systems using IoT, Edge AI, TinyML, LoRa, 5G/6G, RF technologies, wireless sensing, and low-power intelligent devices).
- Emerging Computing and Intelligent Information Systems (Design innovative applications using Generative AI, Explainable AI (XAI), Quantum Computing, Retrieval-Augmented Generation (RAG), knowledge systems, and advanced data analytics for solving real-world problems).
- Technology for Social Impact and Digital Transformation (Build scalable and inclusive technology solutions that address challenges in education, governance, agriculture, public safety, environmental sustainability, accessibility, and community development through AI and digital innovation).
- AI Agent for Marketing (Build an autonomous multi-agent system that ingests multi-platform ad data, analyzes conversion bottlenecks, and executes continuous campaign optimizations. The goal is to maximize Return on Ad Spend (ROAS) and drastically reduce Customer Acquisition Cost (CAC) without human intervention).
- AI Agent for Finance (Challenge: Finance teams lose hours to routine data entry, manual document verification, and reconciling mismatched transactions across fragmented systems. | Objective: Build an autonomous, multi-agent AI system that reads financial documents, autonomously maps transactions to General Ledger (GL) codes, reconciles statements, and flags anomalies for human).
- Open Innovation (Any other relevant solution towards any domain).