Quantum Computing for Smart Cities: Algorithms, Architectures, and Applications for Urban Optimization
Abstract
Managing contemporary smart cities demands computational capabilities that far exceed what conventional processors can deliver. Traffic signal coordination across hundreds of intersections, real-time balancing of renewable energy grids, and cryptographically securing millions of IoT endpoints each constitute combinatorially hard problems that classical algorithms cannot resolve at urban scale within practical time budgets. This paper addresses these limitations by developing and evaluating a hybrid quantum-classical architecture designed for practical deployment in mid-sized smart cities. Three core technical modules are proposed and validated: a Quantum Approximate Optimization Algorithm (QAOA) module for adaptive traffic signal control, a quantum machine learning (QML) module for short-term renewable energy forecasting, and a multi-node Quantum Key Distribution (QKD) architecture for quantum-resilient IoT security. Simulation experiments conducted on IBM Qiskit using realistic urban datasets from Bangalore, India, demonstrate that QAOA-based signal optimization reduces average intersection wait times by 47–53% compared to fixed-timing baselines and executes 4–5× faster than genetic algorithm solvers on equivalent instances. The QML forecasting model achieves 8–12% lower RMSE than classical LSTM networks on solar generation prediction tasks. The QKD-ECC hybrid security framework sustains a 99.9% device authentication success rate while remaining quantum-safe under…
Read the paper
Related studies
- In silico toxicology protocols
- QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
- Quantum Informed Machine-Learning Potentials for Molecular Dynamics Simulations of CO2's Chemisorption and Diffusion in Mg-MOF-74
- In-silico strategies in nano-drug design: Bridging nanomaterials and pharmacological applications
- mRNA codon optimization with quantum computers
- The computational power of the human brain
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.