Smart City Gnosys

Smart city article details

Title	Investigation Of Quantum Machine Learning For Smart Eco System Focusing On Energy Optimization
ID_Doc	33489
Authors	Hussain S.M.; Malviya N.; Pareek P.
Year	2025
Published	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 597 LNICST
DOI	http://dx.doi.org/10.1007/978-3-031-77075-3_12
Abstract	This work explores the integration of Quantum Machine Learning (QML) with various applications in development of smart eco system, focusing on its potential to optimize various urban systems and address complex challenges. Mainly, we explored energy management and optimization techniques, considering Quantum Variational Algorithm (QVL). With this study we recognize that the integration of quantum machine learning approaches in smart city applications enhance the sustainability goals with comparison to the classical techniques. Further, we also investigated on how QML algorithms can revolutionize in various aspects in easing transportation, digital public services and policies, security enhancements, and urban planning, offering opportunities to enhance efficiency, sustainability, and resilience in urban environments. However, this study presents several challenges, including scalability limitations, data privacy concerns, and security vulnerabilities in smart cities. Application of QML holds immense promise for urban innovation and transformation. Discussed, various future directions for integrating QML in smart cities applications. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.
Author Keywords	Data Privacy; Energy Optimization; Optimization; Quantum Machine Learning; Quantum Variational Algorithm; Security; Smart Cities; Sustainability; Urban Development

Similar Articles

Id	Similarity	Authors	Title	Published
29809	0.897	Barletta V.S.; Caivano D.; De Vincentiis M.; Pal A.; Scalera M.	Hybrid Quantum Architecture For Smart City Security	Journal of Systems and Software, 217 (2024)
47791	0.894	Caivano D.; De Vincentiis M.; Pal A.; Ragone A.	Securing Smart Cities: Unraveling Quantum As A Service	QP4SE 2023 - Proceedings of the 2nd International Workshop on Quantum Programming for Software Engineering, Co-located with: ESEC/FSE 2023 (2023)
45936	0.883	Wang S.; Wang N.; Ji T.; Shi Y.; Wang C.	Research Progress Of Quantum Artificial Intelligence In Smart City	Intelligent and Converged Networks, 5, 2 (2024)
43983	0.878	Barletta, VS; Caivano, D; Lako, A; Pal, A	Quantum As A Service Architecture For Security In A Smart City	QUALITY OF INFORMATION AND COMMUNICATIONS TECHNOLOGY, QUATIC 2023, 1871 (2023)
60620	0.872	Acampora G.; Schiattarella R.; Vitiello A.	Using Quantum Fuzzy Inference Engines In Smart Cities	IEEE International Conference on Fuzzy Systems (2024)
43975	0.869	Yigitcanlar T.; Hossain S.T.; Shaamala A.; Ye X.	Quantum Ai Urbanism: Redefining The Future Of Artificial Intelligence In Cities	Journal of Urban Technology, 32, 3 (2025)
60137	0.865	Bashirpour Bonab A.; Fedele M.; Formisano V.; Rudko I.	Urban Quantum Leap: A Comprehensive Review And Analysis Of Quantum Technologies For Smart Cities	Cities, 140 (2023)
966	0.865	EL Azzaoui A.; Arif T.; Park H.; Chen H.; Camacho D.; Park J.H.	A Comprehensive Study On Quantum Computing Technologies In Smart City: Review And Future Directions	Human-centric Computing and Information Sciences, 14 (2024)
31598	0.864	Saraswathi T.; Ravikumar S.; Vaishnavi R.; Arun A.; Mahalakshmi S.; Dinesh M.G.; Prabhu D.	Innovating Urban Futures: Exploring Quantum Computing And Ai In Smart City Development	Leveraging Urban Computing for Sustainable Urban Development (2025)
53763	0.857	Pradhan M.	Survey Of Quantum Machine Learning In Iot Application Field	Proceedings of 5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024 (2024)