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.
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.
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.
The Internet of Things (IoT) has emerged as an innovative framework, connecting physical devices into intricate networks that monitor and control various aspects of daily life. While traditional technologies such as big data analytics and cloud computing have driven the growth of IoT, the emergence of quantum technologies, spanning quantum computing, quantum communication, and quantum sensing, presents unprecedented opportunities to enhance IoT systems. This paper explores the realistic potential and challenges of integrating quantum technologies into IoT, emphasizing the need for a nuanced understanding of what quantum technologies can achieve to bridge the gap between promise and practical application. By fostering collaboration between disciplines, quantum technologies can shape the future of IoT, improving its security, efficiency, and precision.
The rapid expansion of the Internet of Things (IoT) has transformed the way physical devices communicate, process information, and provide intelligent services.With billions of interconnected devices generating enormous volumes of heterogeneous data, conventional computing architectures increasingly face limitations in computational efficiency, security, optimisation, and scalability.Quantum computing has emerged as a disruptive paradigm capable of solving computationally intensive problems exponentially faster than classical computers for selected problem classes.Integrating quantum computing with IoT offers unprecedented opportunities for intelligent decision-making, real-time optimisation, secure communication, and enhanced machine learning.Quantum-enhanced IoT (QIoT) combines quantum algorithms, quantum machine learning, quantum communication, and post-quantum cryptography to create highly efficient and secure smart systems.Applications span healthcare, industrial automation, smart cities,
The need for next-generation sensing systems that are ultra-highly sensitive, have short reaction times, and have lower power demands has swelled with the explosive development of the Internet of Things (IoT). Existing sensors are increasingly constrained by the nature of their performance, in terms of accuracy, sensitivity to noise, and level of security in large-scale IoT applications. Quantum sensors provide high accuracy to measurement on quantities previously thought to be unmeasurable, such as temperature, magnetic fields, gravitational effects, movement, and biochemical markers, using quantum phenomena such as superposition, entanglement, and tunneling. This chapter covers four major concepts: difficulties in hardware integration, difficulties in scalability, state-of-the-art information fusion structures, and specialized security issues in quantum-assisted quantum sensing in a networked setting. Regarding this research work, the quantum sensing technology will, as a rule, be an extremely useful enabler of the next generation of IoT systems, which must provide proper measurements, safety, and high levels of security.
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.