The augmented growth of the Internet of things (IoT) has brought an enormous surge in data generation requiring highly efficient, secure and scalable computational architectures. While conventional cloud computing is a widely used solution, it struggles with various issues like bandwidth constraints, latency and security vulnerabilities. Edge computing alleviates some of these concerns by processing the data closer to its source but time and again it is limited by restricted computational power. Quantum Edge Cloud Computing (QECC) presents a groundbreaking approach by assimilating the power of quantum computing with edge and cloud infrastructure to improve IoT performance. This study caverns the synergy between quantum computing, cloud computing and edge computing, foregrounding how this synergy can strengthen the IoT ecosystems. It examines the advantage of quantum assisted edge-cloud frameworks, investigates the advancements in cyber security through cryptographic methods and discusses plausible real-world applications. Additionally, the paper also features existing technological challenges, traces future research directions and suggests strategies required to realize a truly secure, intelligent and adaptive computing framework for IoT.
The augmented growth of the Internet of things (IoT) has brought an enormous surge in data generation requiring highly efficient, secure and scalable computational architectures. While conventional cloud computing is a widely used solution, it struggles with various issues like bandwidth constraints, latency and security vulnerabilities. Edge computing alleviates some of these concerns by processing the data closer to its source but time and again it is limited by restricted computational power. Quantum Edge Cloud Computing (QECC) presents a groundbreaking approach by assimilating the power of quantum computing with edge and cloud infrastructure to improve IoT performance. This study caverns the synergy between quantum computing, cloud computing and edge computing, foregrounding how this synergy can strengthen the IoT ecosystems. It examines the advantage of quantum assisted edge-cloud frameworks, investigates the advancements in cyber security through cryptographic methods and discusses plausible real-world applications. Additionally, the paper also features existing technological challenges, traces future research directions and suggests strategies required to realize a truly secure, intelligent and adaptive computing framework for IoT.
The rapid expansion of the Internet of Things (IoT) has driven the need for advanced computational frameworks capable of handling the complex data processing and security challenges that modern IoT applications demand. However, traditional cloud computing frameworks face significant latency, scalability, and security issues. Quantum-Edge Cloud Computing (QECC) offers an innovative solution by integrating the computational power of quantum computing with the low-latency advantages of edge computing and the scalability of cloud computing resources. This study is grounded in an extensive literature review, performance improvements, and metrics data from Bangladesh, focusing on smart city infrastructure, healthcare monitoring, and the industrial IoT sector. The discussion covers vital elements, including integrating quantum cryptography to enhance data security, the critical role of edge computing in reducing response times, and cloud computing's ability to support large-scale IoT networks with its extensive resources. Through case studies such as the application of quantum sensors in autonomous vehicles, the practical impact of QECC is demonstrated. Additionally, the paper outlines future research opportunities, including developing quantum-resistant encryption techniques and optimizing quantum algorithms for edge computing. The convergence of these technologies in QECC has the potential to overcome the current limitations of IoT frameworks, setting a new standard for future IoT applications.
The Internet of Things (IoT) is expanding rapidly, which has created a need for sophisticated computational frameworks that can handle the data and security requirements inherent in modern IoT applications. However, traditional cloud computing frameworks have struggled with latency, scalability, and security vulnerabilities. Quantum-Edge Cloud Computing (QECC) is a new paradigm that effectively addresses these challenges by combining the computational power of quantum computing, the low-latency benefits of edge computing, and the scalable resources of cloud computing. This study has been conducted based on a published literature review, performance improvements, and metrics data from Bangladesh on smart city infrastructure, healthcare monitoring, and the industrial IoT sector. We have discussed the integration of quantum cryptography to enhance data integrity, the role of edge computing in reducing response times, and how cloud computing's resource abundance can support large IoT networks. We examine case studies, such as the use of quantum sensors in self-driving vehicles, to illustrate the real-world impact of QECC. Furthermore, the paper identifies future research directions, including developing quantum-resistant encryption and optimizing quantum algorithms for edge computing. The convergence of these technologies in QECC promises to overcome the existing limitations of IoT frameworks and set a new standard for the future of IoT applications.
The Internet of Things (IoT) has rapidly transformed industries by enabling the interconnectivity of devices and the real-time exchange of data. However, as IoT networks continue to scale, the limitations of traditional edge and cloud computing architectures—such as latency, security concerns, and scalability challenges—become more pronounced. This article explores the emerging role of quantum computing in addressing these challenges and advancing the evolution of edge and cloud solutions for IoT systems. By leveraging the unique capabilities of quantum computing, including superposition, entanglement, and quantum parallelism, IoT systems can achieve enhanced data processing speeds, improved security, and more efficient resource management. This article discusses the potential benefits of integrating quantum computing with edge and cloud infrastructures, focusing on use cases in real-time analytics, secure communication, and advanced machine learning for IoT applications. Additionally, it examines the technical, ethical, and regulatory challenges that need to be addressed for the successful deployment of quantum-edge cloud solutions. Finally, the article highlights the importance of collaboration between academia, industry, and policymakers to drive the development of quantum-enabled IoT systems. The findings suggest that quantum computing will play a pivotal role in the next generation of IoT infrastructure, unlocking new possibilities for smarter, more responsive, and secure IoT ecosystems.
Quantum technology is revolutionizing the next generation of intelligent and secure sensing systems.This review explores how quantum sensors—leveraging principles of superposition, entanglement, and quantum tunneling—can be integrated with Internet of Things (IoT) and cloud computing infrastructures to achieve ultra-high precision, real-time analytics, and quantum-secure communication.It discusses the fundamental mechanisms of quantum sensing, sensor architectures, and hybrid quantum-classical data models.The paper also reviews Quantum-Enabled IoT (QIoT) frameworks, Quantum Cloud Computing (QCC) platforms such as IBM Quantum and AWS Braket, and highlights challenges including decoherence, scalability, and standardization.Finally, it presents the future direction of Quantum Industry 5.0, emphasizing sustainable, secure, and intelligent cyber-physical systems powered by quantum innovation.
This chapter explores the transformative integration of Quantum Computing (QC) with the Internet of Things (IoT), highlighting significant advancements in security, optimization, and intelligent decision-making for cyber-physical systems. It provides a detailed review of quantum-enhanced algorithms, architectures, and sensing technologies designed for IoT ecosystems. Addressing the limitations of traditional methods in large-scale computation, network optimization, data analytics, and security, the chapter emphasizes core quantum concepts, i.e., superposition, entanglement, and interference. Techniques, including quantum annealing and the QAOA, enable efficient resource allocation, scheduling, and routing in emerging infrastructures like 6G and UAV networks. The use of hybrid quantum–classical models is examined for fault detection, cryptographic key generation, and real-time analytics across edge-to-cloud environments. QML has been shown to enhance adaptive learning and pattern recognition on resource-limited devices. To counter emerging cyber threats, quantum-resilient security solutions, including post-quantum cryptography, quantum random number generation, and quantum key distribution, are discussed. The chapter also highlights quantum sensors that utilize tunnelling, spin dynamics, and interference for applications in biomedical diagnostics, environmental monitoring, infrastructure evaluation, and autonomous navigation. Emerging use cases, including quantum-powered digital marketing and quantum-secured smart locks, are introduced. The chapter concludes by underscoring the transformative role of scalable hybrid QC–IoT architectures, which are poised to advance edge intelligence, smart infrastructure, healthcare, and logistics, while opening new directions for research and real-world deployment.
Edge computing allows different technologies such as Internet of Things (IoT), vehicle-to-vehicle communications(V V), Industrial IOT (IIOT) to connect to the cloud computing to facilitate end users. The edge networks uses low bandwidth, and enhances the processing speed. With more number of IoT devices connected in the network the privacy of data stored at the edge server also under threat. Authentication is a major challenge which is be addressed to provide security and privacy to IoT devices connected in the network. The existing works uses cryptographic algorithms to solve the authentication problems, but with increase in growth of quantum computers and quantum computing, breaking the complex cryptographic algorithm is not an issue. Hence one should adopt the quantum approach to provide authentication in edge network. The proposed work uses quantum key and context information of IoT devices to store in the edge server using blockchain, which proves to be more secure. The performance analysis shows that it is better with respect to registration, encryption, decryption and authentication of IoT devices.