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Sensor-Enabled IoT, Edge Computing and Artificial Intelligence: Emerging Intelligent Applications

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

Deadline for manuscript submissions: 30 July 2024 | Viewed by 348

Special Issue Editors


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Guest Editor
Fondazione Bruno Kessler, 38123 Trento, Italy
Interests: edge intelligence; edge computing; IoT; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue of Sensors is dedicated to the dynamic intersection of IoT, edge computing, and artificial intelligence (AI), and their collective impact on the evolution of intelligent applications. In an era marked by unprecedented technological advancements, this Special Issue serves as a platform to showcase cutting-edge research, breakthroughs, and innovative solutions that leverage the synergies among these three transformative domains.

The integration of IoT, edge computing, and artificial intelligence has ushered in a new era of possibilities, empowering the development of intelligent applications that span various domains, including agriculture, healthcare, smart cities, manufacturing, transportation, and beyond. This Special Issue brings together a collection of original research articles, reviews, and case studies, offering a comprehensive exploration of the theoretical foundations, practical implementations, and real-world applications that arise from the convergence of these technologies.

Contributions within this Special Issue delve into the intricacies of harnessing data generated by IoT devices at the edge, exploring novel edge computing architectures and methodologies. The fusion of artificial intelligence techniques, such as machine learning and deep learning, with edge computing capabilities opens avenues for real-time decision making, autonomous systems, and enhanced user experiences.

Topics relevant to this Special Issue include, but are not limited to, the following:

  1. Edge-based intelligent data analytics for IoT applications;
  2. Edge-driven machine learning algorithms for efficient processing;
  3. Security and privacy considerations in the integration of IoT, edge, and AI;
  4. Case studies showcasing successful deployments of intelligent applications across industries;
  5. Interoperability challenges and solutions in the interconnected landscape of IoT, Edge, and AI.

We invite researchers, academics, and practitioners to explore this Special Issue, providing insights into the transformative potential of combining IoT, edge computing, and artificial intelligence. By fostering collaboration and knowledge exchange, we aim to propel the field forward, enabling the emergence of intelligent applications that not only address current challenges but also pave the way for future innovations. Together, let us unravel the possibilities at the nexus of IoT, edge computing, and artificial intelligence, shaping the future of intelligent systems and applications.

Dr. Miguel Pincheira
Dr. Mattia Antonini
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

  • IoT
  • edge computing
  • artificial intelligence

Published Papers (1 paper)

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Research

25 pages, 1951 KiB  
Article
IR.WoT: An Architecture and Vision for a Unified Web of Things Search Engine
by Cristyan Manta-Caro and Juan M. Fernández-Luna
Sensors 2024, 24(11), 3302; https://doi.org/10.3390/s24113302 - 22 May 2024
Viewed by 108
Abstract
The revolution of the Internet of Things (IoT) and the Web of Things (WoT) has brought new opportunities and challenges for the information retrieval (IR) field. The exponential number of interconnected physical objects and real-time data acquisition requires new approaches and architectures for [...] Read more.
The revolution of the Internet of Things (IoT) and the Web of Things (WoT) has brought new opportunities and challenges for the information retrieval (IR) field. The exponential number of interconnected physical objects and real-time data acquisition requires new approaches and architectures for IR systems. Research and prototypes can be crucial in designing and developing new systems and refining architectures for IR in the WoT. This paper proposes a unified and holistic approach for IR in the WoT, called IR.WoT. The proposed system contemplates the critical indexing, scoring, and presentation stages applied to some smart cities’ use cases and scenarios. Overall, this paper describes the research, architecture, and vision for advancing the field of IR in the WoT and addresses some of the remaining challenges and opportunities in this exciting area. The article also describes the design considerations, cloud implementation, and experimentation based on a simulated collection of synthetic XML documents with technical efficiency measures. The experimentation results show promising outcomes, whereas further studies are required to improve IR.WoT effectiveness, considering the WoT dynamic characteristics and, more importantly, the heterogeneity and divergence of WoT modeling proposals in the IR domain. Full article
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