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Intelligent IoT and Wireless Communications
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Intelligent IoT and Wireless Communications

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

Deadline for manuscript submissions: closed (21 April 2023) | Viewed by 10009

Special Issue Editors

Dr. Bin Xie

E-Mail Website
Guest Editor
InfoBeyond Technology LLC, 320 Whittington PKWY, Louisville, KY STE 117, USA
Interests: wireless communications; sensor networks; cybersecurity; AI & reasoning; optimization; mobile computing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Angelos Stefanidis

E-Mail Website
Guest Editor
Xi'an Jiaotong-Liverpool University, Taicang Campus, Suzho 215123, China
Interests: AI; explainable AI; AI for digital health; social computing; digital addiction
Dr. Yi Gu

E-Mail Website
Guest Editor
Department of Computer Science, Middle Tennessee State University, Murfreesboro, TN 37132, USA
Interests: wireless sensor networks; parallel and distributed computing; workflow scheduling; cloud/green computing; cybersecurity
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ning Wang

E-Mail Website
Guest Editor
School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China
Interests: resource allocation and security designs of wireless networks; signal processing for wireless communications; AI-enabled wireless communications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid growth of IoT across various industries promotes AI adoption in many aspects towards the intelligence of anything, computing, and communications. This enables intelligence of all connected devices and systems capable of learning, reasoning, planning, problem-solving, maintenance, self-awareness, smart event perception, decision-making and response under given contexts. For instance, IoT through 6G communications makes big data streaming and learning in the cyberspaces possible to offer intelligence for systems, which fosters new applications such as smart manufacturing, smart energy, remote controls, and smart healthcare.

The focus of this Special Issue is to highlight theoretical advances and innovative R&Ds in the areas of intelligent IoTs and AI-based network communications. The topics of interest include, but are not limited to:

  • Artificial Intelligence and Machine Learning
  • IoT System, Architecture, Protocols, and Intelligence
  • Industrial Control Systems (ICS) and Industrial Internet of Things (IIoT)
  • 6G and intelligent wireless communications
  • Sensors, remote systems, and cyber communications
  • AI-based computer vision, image processing, and object detection
  • AI Algorithms and applications
  • Edge and could computing
  • AI-based IoT and 6G network management
  • Deep learning and reasoning

Dr. Bin Xie
Prof. Dr. Angelos Stefanidis
Dr. Yi Gu
Prof. Dr. Ning Wang
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

  • Artificial Intelligence
  • IoT
  • 6G
  • Wireless Communications

Published Papers (2 papers)

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Research

18 pages, 3870 KiB  
Article
High-Precision AI-Enabled Flood Prediction Integrating Local Sensor Data and 3rd Party Weather Forecast
by Qinghua Wang and Walid Abdelrahman
Sensors 2023, 23(6), 3065; https://doi.org/10.3390/s23063065 - 13 Mar 2023
Cited by 4 | Viewed by 2551
Abstract
Flooding risk is a threat to many sea-level cities and residential areas in the world. In the city Kristianstad in southern Sweden, a large number of sensors of different types have been deployed to monitor rain and other weather conditions, water levels at [...] Read more.
Flooding risk is a threat to many sea-level cities and residential areas in the world. In the city Kristianstad in southern Sweden, a large number of sensors of different types have been deployed to monitor rain and other weather conditions, water levels at sea and lakes, ground water levels, and water flows in the city’s storm-water and sewage systems. All the sensors are enabled by battery and wireless communication, and allow real-time data to be transferred and visualized on a cloud-based Internet of Things (IoT) portal. To better enable the system with capacity of foreseeing upcoming flooding threats and to allow early response from decision-makers, it is desired to build a real-time flood forecast system by utilizing the massive sensor data collected at the IoT portal and data from 3rd party weather forecast service. In this article, we have developed a smart flood forecast system using machine learning and artificial neural networks. The developed forecast system has successfully integrated data from multiple sources and can make accurate flood forecast at distributed locations for the coming days. After being successfully implemented as software product and integrated with the city’s IoT portal, our developed flood forecast system has significantly extended the basic monitoring functions of the city’s IoT infrastructure. This article presents the context of this work, the challenges that have been encountered during our development, our solutions and performance evaluation results. To the best of our knowledge, this is the first large-scale IoT-based real-time flood forecast system that has been enabled by artificial intelligence (AI) and deployed in real world. Full article
(This article belongs to the Special Issue Intelligent IoT and Wireless Communications)
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22 pages, 2726 KiB  
Article
LP-MAB: Improving the Energy Efficiency of LoRaWAN Using a Reinforcement-Learning-Based Adaptive Configuration Algorithm
by Benyamin Teymuri, Reza Serati, Nikolaos Athanasios Anagnostopoulos and Mehdi Rasti
Sensors 2023, 23(4), 2363; https://doi.org/10.3390/s23042363 - 20 Feb 2023
Cited by 8 | Viewed by 2482
Abstract
In the Internet of Things (IoT), Low-Power Wide-Area Networks (LPWANs) are designed to provide low energy consumption while maintaining a long communications’ range for End Devices (EDs). LoRa is a communication protocol that can cover a wide range with low energy consumption. To [...] Read more.
In the Internet of Things (IoT), Low-Power Wide-Area Networks (LPWANs) are designed to provide low energy consumption while maintaining a long communications’ range for End Devices (EDs). LoRa is a communication protocol that can cover a wide range with low energy consumption. To evaluate the efficiency of the LoRa Wide-Area Network (LoRaWAN), three criteria can be considered, namely, the Packet Delivery Rate (PDR), Energy Consumption (EC), and coverage area. A set of transmission parameters have to be configured to establish a communication link. These parameters can affect the data rate, noise resistance, receiver sensitivity, and EC. The Adaptive Data Rate (ADR) algorithm is a mechanism to configure the transmission parameters of EDs aiming to improve the PDR. Therefore, we introduce a new algorithm using the Multi-Armed Bandit (MAB) technique, to configure the EDs’ transmission parameters in a centralized manner on the Network Server (NS) side, while improving the EC, too. The performance of the proposed algorithm, the Low-Power Multi-Armed Bandit (LP-MAB), is evaluated through simulation results and is compared with other approaches in different scenarios. The simulation results indicate that the LP-MAB’s EC outperforms other algorithms while maintaining a relatively high PDR in various circumstances. Full article
(This article belongs to the Special Issue Intelligent IoT and Wireless Communications)
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