Wireless Sensor Networks in the IoT

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: 15 October 2024 | Viewed by 3302

Special Issue Editors


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Guest Editor
Department of Electrical and Electronics Engineering, University of West Attica, 12244 Athens, Greece
Interests: algorithm design; approximation algorithms; algorithmic mechanism design; game theory, optimization algorithms for wireless sensor networks
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Special Issue Information

Dear Colleagues,

Wireless sensor networks (WSNs), based on the combined use of their sensor nodes, are not only able to monitor and collect information related to the ambient conditions that exist in areas of interest, but are also able to process and, finally, transmit the corresponding data to the final user. Going one step further, the Internet of Things (IoT) facilitates the interconnection between all types of intelligent devices and the exchange of data among them over the Internet.

Therefore, WSNs are one key supporting technology for the IoT, whereas both WSNs and the IoT have a practically endless range of applications, which is why they are considered to be among the most important scientific areas today. On the other hand, there are certain weaknesses and problems that impede the successful operation of WSNs and the IoT while various emerging technologies pose novel challenges. For all the aforementioned reasons, the integration of WSNs into the IoT is at the epicenter of the research being conducted by the scientific community.

The aim of this Special Issue is to host research articles related to experimentations, implementations, applications, new research proposals, and case studies regarding WSNs and the IoT. Hosted articles have to be original and neither published nor under review in any other conference or journal. Potential topics include, but are not limited to, the following:

  • WSNs/IoT with 5G/6G communication networks;
  • Energy sustainability in WSNs/IoT;
  • Energy harvesting methods;
  • Energy transfer methods;
  • Energy-efficient routing protocols;
  • WSNs/IoT architecture design;
  • Data analytics in WSNs/IoT;
  • Computational intelligence for WSNs/IoT;
  • Artificial intelligence for WSNs/IoT;
  • Cloud computing for IoT/WSNs;
  • Edge computing for IoT/WSNs;
  • Fog computing for IoT/WSNs;
  • Wireless body area networks;
  • Sensing technologies and systems for wearables and implants;
  • WSNs/IoT in Industry 4.0;
  • Optimization algorithms.

Prof. Dr. Dionisis Kandris
Dr. Eleftherios Anastasiadis
Guest Editors

Manuscript Submission Information

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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

  • WSNs
  • IoT
  • 5G/6G communication networks
  • artificial intelligence
  • cloud computing
  • edge computing
  • fog computing
  • wireless body area networks
  • Industry 4.0

Published Papers (2 papers)

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17 pages, 459 KiB  
Article
Latent Autoregressive Student-t Prior Process Models to Assess Impact of Interventions in Time Series
by Patrick Toman, Nalini Ravishanker, Nathan Lally and Sanguthevar Rajasekaran
Future Internet 2024, 16(1), 8; https://doi.org/10.3390/fi16010008 - 28 Dec 2023
Viewed by 1338
Abstract
With the advent of the “Internet of Things” (IoT), insurers are increasingly leveraging remote sensor technology in the development of novel insurance products and risk management programs. For example, Hartford Steam Boiler’s (HSB) IoT freeze loss program uses IoT temperature sensors to monitor [...] Read more.
With the advent of the “Internet of Things” (IoT), insurers are increasingly leveraging remote sensor technology in the development of novel insurance products and risk management programs. For example, Hartford Steam Boiler’s (HSB) IoT freeze loss program uses IoT temperature sensors to monitor indoor temperatures in locations at high risk of water-pipe burst (freeze loss) with the goal of reducing insurances losses via real-time monitoring of the temperature data streams. In the event these monitoring systems detect a potentially risky temperature environment, an alert is sent to the end-insured (business manager, tenant, maintenance staff, etc.), prompting them to take remedial action by raising temperatures. In the event that an alert is sent and freeze loss occurs, the firm is not liable for any damages incurred by the event. For the program to be effective, there must be a reliable method of verifying if customers took appropriate corrective action after receiving an alert. Due to the program’s scale, direct follow up via text or phone calls is not possible for every alert event. In addition, direct feedback from customers is not necessarily reliable. In this paper, we propose the use of a non-linear, auto-regressive time series model, coupled with the time series intervention analysis method known as causal impact, to directly evaluate whether or not a customer took action directly from IoT temperature streams. Our method offers several distinct advantages over other methods as it is (a) readily scalable with continued program growth, (b) entirely automated, and (c) inherently less biased than human labelers or direct customer response. We demonstrate the efficacy of our method using a sample of actual freeze alert events from the freeze loss program. Full article
(This article belongs to the Special Issue Wireless Sensor Networks in the IoT)
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17 pages, 5324 KiB  
Article
Design Considerations and Performance Evaluation of Gossip Routing in LoRa-Based Linear Networks
by Rao Muzamal Liaqat, Philip Branch and Jason But
Future Internet 2023, 15(11), 366; https://doi.org/10.3390/fi15110366 - 11 Nov 2023
Viewed by 1446
Abstract
Linear networks (sometimes called chain-type networks) occur frequently in Internet of Things (IoT) applications, where sensors or actuators are deployed along pipelines, roads, railways, mines, and international borders. LoRa, short for Long Range, is an increasingly important technology for the IoT with great [...] Read more.
Linear networks (sometimes called chain-type networks) occur frequently in Internet of Things (IoT) applications, where sensors or actuators are deployed along pipelines, roads, railways, mines, and international borders. LoRa, short for Long Range, is an increasingly important technology for the IoT with great potential for linear networking. Despite its potential, limited research has explored LoRa’s implementation in such networks. In this paper, we addressed two important issues related to LoRa linear networks. The first is contention, when multiple nodes attempt to access a shared channel. Although originally designed to deal with interference, LoRa’s technique of synchronisation with a transmission node permits a novel approach to contention, which we explored. The second issue revolves around routing, where linear networks permit simpler strategies, in contrast to the common routing complexities of mesh networks. We present gossip routing as a very lightweight approach to routing. All our evaluations were carried out using real equipment by developing real networks. We constructed networks of up to three hops in length and up to three nodes in width. We carried out experiments looking at contention and routing. We demonstrate using the novel approach that we could achieve up to 98% throughput. We compared its performance considering collocated scenarios that achieved 84% and 89% throughputby using relay widths of two and three at each hop, respectively. Lastly, we demonstrate the effectiveness of gossip routing by using various transmission probabilities. We noticed high performance up to 98% throughputat Tprob = 0.90 and Tprob = 0.80 by employing two and three active relay nodes, respectively. The experimental result showed that, at Tprob = 0.40, it achieved an average performance of 62.8% and 73.77% by using two and three active relay nodes, respectively. We concluded that LoRa is an excellent technology for Internet of Things applications where sensors and actuators are deployed in an approximately linear fashion. Full article
(This article belongs to the Special Issue Wireless Sensor Networks in the IoT)
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