Industrial Internet of Things (IIoT): Trends and Technologies
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 30 June 2024 | Viewed by 1028
Special Issue Editors
Interests: Industry 5.0; digital twin and metaverse; embodied AI; human-robot collaboration; robot learning; reinforcement learning; neural information processing; human-compatible AI
2. CNIT National Laboratory of Smart and Secure Networks (S2N), 16126 Genova, Italy
Interests: dynamic resource allocation in multiservice networks and in the Future Internet; mobile wireless and satellite networks; multimedia communications and services; flexible; programmable; energy-efficient networking
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The Industrial Internet of Things (IIoT) has emerged as a transformative force revolutionizing industries across the globe. It encompasses the integration of sensor technologies, machine learning, big data analytics, and connectivity to revolutionize industrial processes and enhance productivity. This transformation has not just enhanced industrial processes and productivity but is also paving the way for innovative business models. As the IIoT continues to evolve rapidly, it is crucial to delve into its latest trends, explore state-of-the-art technologies, and understand the emerging challenges and future possibilities.
In this Special Issue, we invite submissions focusing on the dynamic landscape of the Industrial Internet of Things (IIoT) and its evolving trends and technologies. We encourage researchers, academicians, and industry practitioners to contribute their valuable insights and research findings to this Special Issue, fostering the dissemination of knowledge and advancements in the realm of the Industrial Internet of Things (IIoT).
Scope:
This Special Issue seeks to explore various facets of IIoT, including but not limited to:
- IIoT applications in manufacturing, healthcare, energy, transportation, agriculture, and other industries;
- Edge computing and IIoT;
- Security and privacy challenges in IIoT;
- AI and machine learning in IIoT systems;
- Big data analytics for IIoT;
- Connectivity protocols and standards for IIoT: URLLC, TSN, OPC UA, etc.;
- Sensor technologies and their role in IIoT;
- Industry 4.0 and the convergence of IIoT with other technologies;
- Case studies and real-world implementations of IIoT solutions.
Dr. Zhihao Liu
Prof. Dr. Franco Davoli
Dr. Davide Borsatti
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. Future Internet is an international peer-reviewed open access monthly 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 1600 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
- Industrial Internet of Things (IIoT)
- edge computing
- cybersecurity in IIoT
- Artificial Intelligence (AI) in IIoT applications
- Industry 5.0 with IIoT
- big data analytics for IIoT
- sensor networks for IIoT
- IIoT-driven smart manufacturing
- IIoT standards and protocols
- wireless communication in industrial environments
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: GreenLab, an IoT-Based Small-Scale Smart Greenhouse
Authors: Cristian Volosciuc, Razvan Bogdan, Bianca Blajovan, Cristina Stângaciu and Marius Marcu
Affiliation: Department of Computers and Information Technology, Politehnica University Timisoara
Abstract: In an era of connectivity, the Internet of Things introduces smart solutions for smart and
sustainable agriculture, bringing alternatives to overcome the food crisis. Among these solutions,
smart greenhouses support crop and vegetable agriculture regardless of season and cultivated area
by carefully controlling and managing parameters like temperature, air and soil humidity, and light.
Smart technologies have proved to be successful tools for increasing agricultural production at both
the macro and micro levels, being an important step in streamlining small-scale agriculture. This
paper presents an experimental Internet of Things-based small-scale greenhouse prototype as a proof
of concept for the benefits of merging smart sensing, connectivity, IoT and mobile-based applications,
for growing cultures. Our proposed solution includes a photovoltaic panel and a buffer battery
for reducing energy consumption costs, while also assuring functionality during night and cloudy
weather and a mobile application for an easy data visualization and monitoring of the greenhouse.
Title: Multi-Agent Deep-Q Network Based Cache Replacement Policy for Content Delivery Networks
Authors: Janith K. Dassanayake, Minxiao Wang, Muhammad Z. Hameed, Ning Yang, and Ning Weng
Affiliation: Information Technology Faculty, Southern Illinois University
Abstract: In today's digital landscape, content delivery networks (CDNs) play a pivotal role in ensuring rapid and seamless access to online content across the globe. By strategically deploying a network of edge servers in close proximity to users, CDNs optimize the delivery of digital content. One key mechanism involves caching frequently requested content at these edge servers, not only alleviating the load on the source CDN server but also enhancing the overall user experience. However, the exponential growth in user demands has led to increased network congestion, subsequently reduces the cache hit ratio within CDNs. To address this reduction in cache hit ratio with CDNs, this paper presents an innovative approach for efficient cache replacement in a dynamic caching environment while maximizing the cache hit ratio via a cooperative cache replacement policy based on reinforcement learning. The cache replacement problem is initially modeled as a Markov decision process and it is extended to a multi-agent reinforcement learning problem. We propose a cooperative cache replacement algorithm based on multi-agent deep-Q network (MADQN), where the edge servers cooperatively learn efficiently to replace the cached content to maximize the cache hit ratio. The experimental results are presented to validate the performance of our proposed approach. Notably, our MADQN policy exhibits superior cache hit ratios and lower average delays compared to traditional caching policies.
