Quantum Cities: Trends and challenges

The development of quantum machine learning (QML) has received a lot of interest recently thanks to developments in both quantum computing (QC) and machine learning (ML). Researches indicates that quantum computing can significantly accelerate processing speeds and enhance data transfer capabilities, especially for smart city applications. However, due to the instability in quantum processing and the potential for computational errors, a hybrid approach of quantum and classical computing is currently required. This research focuses on addressing the challenges of integrating quantum technologies into sustainable urban environments. For this purpose, we propose utilizing Green AI and AIOT (Artificial Intelligence of Things) alongside quantum data transmission to optimize resource management and energy efficiency. Currently, a hybrid of quantum and classical computing is essential to ensure reliable operation, laying the groundwork for future smart cities. This paper presents a novel vision for urban-scale quantum computing, leveraging current or near-term technologies to address these challenges effectively .

کلیدواژه ها:

Quantum Computing ، AIOT ، Smast cities ، Machine learning ، QAI ، Artificial intelligence ، QML