sensors-logo

Journal Browser

Journal Browser

Quantum IoT (QIoT): Revolutionizing Connectivity, Innovation, Challenges, and Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: 1 December 2025 | Viewed by 1480

Special Issue Editors


E-Mail Website
Guest Editor
Crown Institute of Higher Education (CIHE), Sydney 1001, Australia
Interests: IoT; indoor localization; machine learning; wireless sensor networks
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Crown Institute of Higher Education (CIHE), Sydney, Australia
Interests: IoT; cybersecurity; cloud computing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Victoria University Business School, Victoria University, Melbourne 3000, Australia
Interests: IoT; business intelligence; decision support systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Quantum IoT (QIoT) represents a groundbreaking integration of Quantum Computing and the Internet of Things, poised to revolutionize connectivity and drive technological innovation. By leveraging quantum technologies, QIoT can significantly enhance the efficiency, security, and scalability of IoT systems through quantum-enhanced algorithms, quantum cryptography, and advanced quantum sensors.

Despite its vast potential, the implementation of QIoT faces challenges such as high research costs, infrastructure requirements, and the need for seamless integration with classical systems. This Special Issue explores the multifaceted dimensions of QIoT, presenting cutting-edge research and practical applications that highlight the transformative impact of quantum technologies on IoT.

Through this collection, we aim to provide insights into the current advancements, future directions, and innovative solutions within the realm of QIoT, fostering a deeper understanding and inspiring further research in this emerging field.

This Special Issue will cover a broad spectrum of topics, including but not limited to the following:

  • Quantum AI for IoT optimization;
  • Machine learning integration in quantum IoT systems;
  • Quantum IoT and fog computing: enhancing edge intelligence;
  • Cloud-based quantum IoT solutions;
  • Quantum computing in IoT;
  • Quantum-enhanced IoT architectures;
  • Quantum cryptography for IoT security;
  • Quantum sensors in IoT;
  • Quantum machine learning for IoT data analysis;
  • Quantum key distribution (QKD) in IoT networks;
  • Quantum algorithms for real-time IoT analytics;
  • Edge computing with quantum processors;
  • Secure data transmission in quantum IoT;
  • Quantum IoT in healthcare applications;
  • Quantum IoT for smart cities;
  • Interoperability between classical and quantum IoT systems;
  • Ethical and regulatory considerations in quantum IoT;
  • Quantum IoT network protocols.

Dr. Javad Rezazadeh
Dr. John Ayoade
Dr. Omid Ameri Sianaki
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • quantum IoT
  • QIoT
  • quantum IoT and fog computing

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

21 pages, 4782 KiB  
Article
A New Method Based on Locally Optimal Step Length in Accelerated Gradient Descent for Quantum State Tomography
by Mohammad Dolatabadi, Vincenzo Loia and Pierluigi Siano
Sensors 2024, 24(17), 5464; https://doi.org/10.3390/s24175464 - 23 Aug 2024
Viewed by 791
Abstract
Quantum state tomography (QST) is one of the key steps in determining the state of the quantum system, which is essential for understanding and controlling it. With statistical data from measurements and Positive Operator-Valued Measures (POVMs), the goal of QST is to find [...] Read more.
Quantum state tomography (QST) is one of the key steps in determining the state of the quantum system, which is essential for understanding and controlling it. With statistical data from measurements and Positive Operator-Valued Measures (POVMs), the goal of QST is to find a density operator that best fits the measurement data. Several optimization-based methods have been proposed for QST, and one of the most successful approaches is based on Accelerated Gradient Descent (AGD) with fixed step length. While AGD with fixed step size is easy to implement, it is computationally inefficient when the computational time required to calculate the gradient is high. In this paper, we propose a new optimal method for step-length adaptation, which results in a much faster version of AGD for QST. Numerical results confirm that the proposed method is much more time-efficient than other similar methods due to the optimized step size. Full article
Show Figures

Figure 1

Back to TopTop