Egreen Quanta
Browse and strategize across all 5 official problem statements submitted by Egreen Quanta for Smart India Hackathon 2026.
Problem Statements (5)
Match My TeamQuantum-Inspired Intelligent Traffic Route Optimization in Transportation Systems Using Metaheuristic Optimization
Metropolitan traffic congestion in Indian cities causes massive fuel waste and carbon emissions, while classical Dijkstra/A* routing algorithms fail when thousands of vehicles simultaneously request dynamic re-routing around traffic jams. Build a Quantum-Inspired Intelligent Traffic Route Optimization Platform for Egreen Quanta that formulates urban network flow as a Quadratic Unconstrained Binary Optimization (QUBO) problem, solving multi-vehicle dynamic route assignment via Simulated Quantum Annealing (SQA) and QAOA heuristics in real time.
Quantum-Inspired Fuel Consumption Prediction and Green Fleet Optimization
Commercial shipping fleets and heavy inter-city freight logistics companies face severe carbon emissions and high fuel costs due to unoptimized voyage speeds, oceanic currents, and non-linear aerodynamic/hydrodynamic drag. Build a Quantum-Inspired Fuel Consumption Prediction and Green Fleet Optimization Platform for Egreen Quanta that uses Quantum Support Vector Regression (QSVR) and Quantum-Inspired Genetic Algorithms (QIGA) to predict vessel hydrodynamic fuel burn and calculate fuel-optimal weather-routing trajectories.
Hybrid Quantum Machine Learning Platform for Early Disease Detection
Early detection of complex diseases (multi-gene cancers, Alzheimer's, autoimmune disorders) from high-dimensional multi-omics datasets (genomics, transcriptomics, clinical biomarkers) suffers from the 'Curse of Dimensionality' where classical machine learning overfits on small clinical sample sizes. Build a Hybrid Quantum Machine Learning (HQML) Platform for Early Disease Detection for Egreen Quanta that utilizes Quantum Neural Networks (QNN) and Variational Quantum Classifiers (VQC) with parameterized quantum circuits (PQC) in PennyLane/Qiskit to classify disease biomarkers with superior generalization.
AI-Based Interactive Quantum Algorithm Learning Platform
Engineering students and developers struggle to learn quantum computing because abstract linear algebra concepts (superposition, entanglement, phase kickback, quantum Fourier transform) are taught theoretically without interactive visual intuition or real-time circuit execution. Build an AI-Based Interactive Quantum Algorithm Learning Platform for Egreen Quanta featuring a dynamic 3D Bloch Sphere visualizer, drag-and-drop quantum circuit builder with real-time statevector calculations, and an AI conversational quantum tutor.
Quantum-Inspired Cyber Threat Detection for Digital Signature Security
The impending advent of fault-tolerant quantum computers running Shor's algorithm threatens to shatter classical asymmetric public-key digital signatures (RSA, ECDSA) used across national banking, PKI certificates, and blockchain networks. Build a Quantum-Inspired Cyber Threat Detection and Post-Quantum Cryptographic (PQC) Migration Platform for Egreen Quanta that analyzes digital signature entropy anomalies, identifies quantum vulnerability risks across enterprise PKI infrastructure, and implements NIST-standardized Post-Quantum algorithms (CRYSTALS-Dilithium, Falcon, SPHINCS+).