Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

Journal Browser

► Journal Browser

Advanced Applications of WSNs and the IoT

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Related Special Issue
Published Papers

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

Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 15145

Share This Special Issue

Special Issue Editors

Dr. Sebastià Galmés

E-Mail Website
Guest Editor

Department of Mathematics and Computer Science, University of Balearic Islands, 07122 Palma de Mallorca, Spain
Interests: wireless sensor networks; RF energy-harvesting; nanoscale communications; specifically biomedical applications of nanoscale communications
Special Issues, Collections and Topics in MDPI journals

Dr. Baris Atakan

E-Mail Website
Guest Editor

Department of Electrical and Electronics Engineering, Izmir Institute of Technology, 35430 Izmir, Turkey
Interests: bio-inspired communication and networking techniques for wireless networks; wireless sensor and actor networks; delay tolerant networks; cognitive radio networks; molecular communications and nanoscale electromagnetic communications; nanonetworks, specifically body-area nanonetworks for nanomedicine applications; mobile ad hoc nanonetworks and graphene-based nanonetworks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Around three decades ago, wireless sensor networks (WSNs) emerged as a new ICT paradigm connecting the physical and the digital world. In fact, some authors called this disruptive technology the “digital retina”. Many applications in a broad set of fields were envisioned, which have nowadays become a reality. More recently, the idea of a wireless sensor network has been extended to a wider, higher-level and more ambitious concept, namely the Internet of Things (IoT). WSNs and the IoT have since merged together, with some members of the research community viewing WSNs as part of the IoT, with others pointing to the fact that WSNs constitute the supporting technology for IoT. Although none of these views is wrong, a deeper consideration is needed that highlights the similarities and differences, and definitely the relationship, between both technologies:

Nodes in WSN are specialized devices that have limited sensing, actuating, computing, and communicating capabilities, as well as scarce energy resources. Conversely, nodes in IoT are objects (things) of daily life to which those capabilities have been embedded, thus making them “smart”.
Usually, nodes in WSN do not have an IP address, whereas every “thing” in IoT does. Precisely, this gives rise to the expression “Internet of Things”.

There are also differences regarding their implementation, such as the fact that nodes in WSNs are obviously wireless, as the name implies, whereas in the case of IoT, they can be wired or wireless; or, from the topological point of view, typically WSNs obey a star or tree–star topology, rooted at one or several gateways which do have Internet connectivity, while IoT devices form a mesh network, in the same way that conventional computers, laptops, and servers are interconnected through the Internet.

Apart from these differences, a relevant feature common to both technologies is the limited amount of energy available at each node, which prioritizes low energy consumption among other design factors. This explains that routing strategies, topology control methods, medium-access control mechanisms, and other techniques already designed for WSNs have been extended to IoT systems, a fact that underlines the view of WSNs as the supporting technology for IoT. However, from the explanation above, a complete WSN can be a single node of an IoT system.

Nowadays, the spectacular number of nodes predicted for WSNs, and especially for IoT systems, has attracted other technological fields, without which the implementation of the former would not be possible. In effect, the pairing of expressions such as big data, artificial intelligence, cloud computing, 5G (and beyond) communications, and energy-harvesting techniques with WSNs and the IoT is inevitable.

On the basis of these preliminary considerations, this Special Issue welcomes papers describing sophisticated applications of WSNs and the IoT, which stand out because of their large scale and/or involved technologies. Detailed descriptions are expected, which highlight all design aspects in an organized way. Any application field can be considered, either in the WSN or the IoT context. The relevance and sophistication of the application, the structure of the paper, and the quality of descriptions and illustrations are essential aspects in the evaluation of manuscripts.

Dr. Sebastià Galmés
Dr. Barış Atakan
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

wireless sensor networks
Internet of Things
wireless communications standards (BLE, ZigBee, LoRaWAN, SigFox, 5G/6G)
energy-harvesting
big data
artificial intelligence
cloud computing
security
smart environment
ambient intelligence

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 polices can be found here.

Related Special Issue

Advanced Applications of WSNs and the IoT—2nd Edition in Sensors

Published Papers (11 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

24 pages, 918 KiB

Open AccessArticle

Quality of Service-Aware Multi-Objective Enhanced Differential Evolution Optimization for Time Slotted Channel Hopping Scheduling in Heterogeneous Internet of Things Sensor Networks

by Aida Vatankhah and Ramiro Liscano

Sensors 2024, 24(18), 5987; https://doi.org/10.3390/s24185987 - 15 Sep 2024

Viewed by 178

Abstract

The emergence of the Internet of Things (IoT) has attracted significant attention in industrial environments. These applications necessitate meeting stringent latency and reliability standards. To address this, the IEEE 802.15.4e standard introduces a novel Medium Access Control (MAC) protocol called Time Slotted Channel Hopping (TSCH). Designing a centralized scheduling system that simultaneously achieves the required Quality of Service (QoS) is challenging due to the multi-objective optimization nature of the problem. This paper introduces a novel optimization algorithm, QoS-aware Multi-objective enhanced Differential Evolution optimization (QMDE), designed to handle the QoS metrics, such as delay and packet loss, across multiple services in heterogeneous networks while also achieving the anticipated service throughput. Through co-simulation between TSCH-SIM and Matlab, R2023a we conducted multiple simulations across diverse sensor network topologies and industrial QoS scenarios. The evaluation results illustrate that an optimal schedule generated by QMDE can effectively fulfill the QoS requirements of closed-loop supervisory control and condition monitoring industrial services in sensor networks from 16 to 100 nodes. Through extensive simulations and comparative evaluations against the Traffic-Aware Scheduling Algorithm (TASA), this study reveals the superior performance of QMDE, achieving significant enhancements in both Packet Delivery Ratio (PDR) and delay metrics. Full article

(This article belongs to the Special Issue Advanced Applications of WSNs and the IoT)

► Show Figures

Figure 1

43 pages, 2070 KiB

Open AccessArticle

Rapid and Resilient LoRa Leap: A Novel Multi-Hop Architecture for Decentralised Earthquake Early Warning Systems

by Vinuja Ranasinghe, Nuwan Udara, Movindi Mathotaarachchi, Tharindu Thenuwara, Dileeka Dias, Raj Prasanna, Sampath Edirisinghe, Samiru Gayan, Caroline Holden, Amal Punchihewa, Max Stephens and Paul Drummond

Sensors 2024, 24(18), 5960; https://doi.org/10.3390/s24185960 - 13 Sep 2024

Viewed by 268

Abstract

We introduce a novel LoRa-based multi-hop communication architecture as an alternative to the public internet for earthquake early warning (EEW). We examine its effectiveness in generating a meaningful warning window for the New Zealand-based decentralised EEW sensor network implemented by the CRISiSLab operating with the adapted Propagation of Local Undamped Motion (PLUM)-based earthquake detection and node-level data processing. LoRa, popular for low-power, long-range applications, has the disadvantage of long transmission time for time-critical tasks like EEW. Our network overcomes this limitation by broadcasting EEWs via multiple short hops with a low spreading factor (SF). The network includes end nodes that generate warnings and relay nodes that broadcast them. Benchmarking with simulations against CRISiSLab’s EEW system performance with internet connectivity shows that an SF of 8 can disseminate warnings across a 30 km urban area within 2.4 s, respectively. This approach is also resilient, with the availability of multiple routes for a message to travel. Our LoRa-based system achieves a 1–6 s warning window, slightly behind the 1.5–6.75 s of the internet-based performance of CRISiSLab’s system. Nevertheless, our novel network is effective for timely mental preparation, simple protective actions, and automation. Experiments with Lilygo LoRa32 prototype devices are presented as a practical demonstration. Full article

(This article belongs to the Special Issue Advanced Applications of WSNs and the IoT)

20 pages, 1712 KiB

Open AccessArticle

Dynamic Cooperative Communications with Mutual Information Accumulation for Mobile Robots in Industrial Internet of Things

by Daoyuan Sun, Zefan Liu and Xinming Zhang

Sensors 2024, 24(13), 4362; https://doi.org/10.3390/s24134362 - 5 Jul 2024

Viewed by 470

Abstract

Mobile robots play an important role in the industrial Internet of Things (IIoT); they need effective mutual communication between the cloud and themselves when they move in a factory. By using the sensor nodes existing in the IIoT environment as relays, mobile robots and the cloud can communicate through multiple hops. However, the mobility and delay sensitivity of mobile robots bring new challenges. In this paper, we propose a dynamic cooperative transmission algorithm with mutual information accumulation to cope with these two challenges. By using rateless coding, nodes can reduce the delay caused by retransmission under poor channel conditions. With the help of mutual information accumulation, nodes can accumulate information faster and reduce delay. We propose a two-step dynamic algorithm, which can obtain the current routing path with low time complexity. The simulation results show that our algorithm is better than the existing heuristic algorithm in terms of delay. Full article

(This article belongs to the Special Issue Advanced Applications of WSNs and the IoT)

► Show Figures

Figure 1

22 pages, 956 KiB

Open AccessArticle

Adaptive Spatial Scheduling for Event Traffic in LoRaWAN Networks

by Vassilis Asteriou, Konstantinos Kantelis, Georgia A. Beletsioti, Anastasios Valkanis, Petros Nicopolitidis and Georgios Papadimitriou

Sensors 2024, 24(7), 2222; https://doi.org/10.3390/s24072222 - 30 Mar 2024

Viewed by 696

Abstract

Low-Power Wide-Area Networks constitute a leading, emerging Internet-of-Things technology, with important applications in environmental and industrial monitoring and disaster prevention and management. In such sensor networks, external detectable events can trigger synchronized alarm report transmissions. In LoRaWANs, and more generally in networks with a random access-based medium access algorithm, this can lead to a cascade of frame collisions, temporarily resulting in degraded performance and diminished system operational capacity, despite LoRaWANs’ physical layer interference and collision reduction techniques. In this paper, a novel scheduling algorithm is proposed that can increase system reliability in the case of such events. The new adaptive spatial scheduling algorithm is based on learning automata, as well as previous developments in scheduling over LoRaWANs, and it leverages network feedback information and traffic spatial correlation to increase network performance while maintaining high reliability. The proposed algorithm is investigated via an extensive simulation under a variety of network conditions and compared with a previously proposed scheduler for event-triggered traffic. The results show a decrease of up to 30% in average frame delay compared to the previous approach and an order of magnitude lower delay compared to the baseline algorithm. These findings highlight the importance of using spatial information in adaptive schemes for improving network performance, especially in location-sensitive applications. Full article

(This article belongs to the Special Issue Advanced Applications of WSNs and the IoT)

► Show Figures

Figure 1

16 pages, 1317 KiB

Open AccessArticle

An Application of Throughput Request Satisfaction Method for Maximizing Concurrent Throughput in WLAN for IoT Application System

by Bin Wu, Nobuo Funabiki, Sujan Chandra Roy, Md. Mahbubur Rahman, Dezheng Kong and Shihao Fang

Sensors 2024, 24(7), 2173; https://doi.org/10.3390/s24072173 - 28 Mar 2024

Cited by 1 | Viewed by 804

Abstract

With the wide applications of the Internet of Things (IoT) in smart home systems, IEEE 802.11n Wireless Local Area Networks (WLANs) have become a frequently chosen communication technology due to their adaptability and affordability. In a high-density network of devices such as the smart home scenerio, a host often meets interferences from other devices and unequal Received Signal Strength (RSS) from Access Points (APs). This results in throughput unfairness/insufficiency problems between hosts communicating concurrently in WLAN. Previously, we have studied the throughput request satisfaction method to address this problem. It calculates the target throughput from measured single and concurrent throughputs of hosts and controls the actual throughput at this target one by applying traffic shaping at the AP. However, the insufficiency problem of maximizing the throughput is not solved due to interferences from other hosts. In this paper, we present an extension of the throughput request satisfaction method to maximize the throughput of a high-priority host under concurrent communications. It recalculates the target throughput to increase the actual throughput as much as possible while the other hosts satisfy the least throughput. For evaluations, we conduct experiments using the test-bed system with Raspberry Pi as the AP devices in several topologies in indoor environments. The results confirm the effectiveness of our proposal. Full article

(This article belongs to the Special Issue Advanced Applications of WSNs and the IoT)

► Show Figures

Figure 1

16 pages, 777 KiB

Open AccessArticle

Low-Latency Wireless Network Extension for Industrial Internet of Things

by Michael Fletcher, Eric Paulz, Devin Ridge and Alan J. Michaels

Sensors 2024, 24(7), 2113; https://doi.org/10.3390/s24072113 - 26 Mar 2024

Cited by 1 | Viewed by 1184

Abstract

The timely delivery of critical messages in real-time environments is an increasing requirement for industrial Internet of Things (IIoT) networks. Similar to wired time-sensitive networking (TSN) techniques, which bifurcate traffic flows based on priority, the proposed wireless method aims to ensure that critical traffic arrives rapidly across multiple hops to enable numerous IIoT use cases. IIoT architectures are migrating toward wirelessly connected edges, creating a desire to extend TSN-like functionality to a wireless format. Existing protocols possess inherent challenges to achieving this prioritized low-latency communication, ranging from rigidly scheduled time division transmissions, scalability/jitter of carrier-sense multiple access (CSMA) protocols, and encryption-induced latency. This paper presents a hardware-validated low-latency technique built upon receiver-assigned code division multiple access (RA-CDMA) techniques to implement a secure wireless TSN-like extension suitable for the IIoT. Results from our hardware prototype, constructed on the IntelFPGA Arria 10 platform, show that (sub-)millisecond single-hop latencies can be achieved for each of the available message types, ranging from 12 bits up to 224 bits of payload. By achieving one-way transmission of under 1 ms, a reliable wireless TSN extension with comparable timelines to 802.1Q and/or 5G is achievable and proven in concept through our hardware prototype. Full article

(This article belongs to the Special Issue Advanced Applications of WSNs and the IoT)

► Show Figures

Figure 1

43 pages, 11786 KiB

Open AccessArticle

Semi-Supervised Clustering-Based DANA Algorithm for Data Gathering and Disease Detection in Healthcare Wireless Sensor Networks (WSN)

by Anurag Sinha, Turki Aljrees, Saroj Kumar Pandey, Ankit Kumar, Pallab Banerjee, Biresh Kumar, Kamred Udham Singh, Teekam Singh and Pooja Jha

Sensors 2024, 24(1), 18; https://doi.org/10.3390/s24010018 - 19 Dec 2023

Cited by 1 | Viewed by 1969

Abstract

Wireless sensor networks (WSNs) have emerged as a promising technology in healthcare, enabling continuous patient monitoring and early disease detection. This study introduces an innovative approach to WSN data collection tailored for disease detection through signal processing in healthcare scenarios. The proposed strategy leverages the DANA (data aggregation using neighborhood analysis) algorithm and a semi-supervised clustering-based model to enhance the precision and effectiveness of data collection in healthcare WSNs. The DANA algorithm optimizes energy consumption and prolongs sensor node lifetimes by dynamically adjusting communication routes based on the network’s real-time conditions. Additionally, the semi-supervised clustering model utilizes both labeled and unlabeled data to create a more robust and adaptable clustering technique. Through extensive simulations and practical deployments, our experimental assessments demonstrate the remarkable efficacy of the proposed method and model. We conducted a comparative analysis of data collection efficiency, energy utilization, and disease detection accuracy against conventional techniques, revealing significant improvements in data quality, energy efficiency, and rapid disease diagnosis. This combined approach of the DANA algorithm and the semi-supervised clustering-based model offers healthcare WSNs a compelling solution to enhance responsiveness and reliability in disease diagnosis through signal processing. This research contributes to the advancement of healthcare monitoring systems by offering a promising avenue for early diagnosis and improved patient care, ultimately transforming the landscape of healthcare through enhanced signal processing capabilities. Full article

(This article belongs to the Special Issue Advanced Applications of WSNs and the IoT)

► Show Figures

Figure 1

27 pages, 3962 KiB

Open AccessArticle

Automatic Passenger Counting on the Edge via Unsupervised Clustering

by Giorgio Delzanno, Luca Caputo, Daniele D’Agostino, Daniele Grosso, Abdul Hannan Mustajab, Luca Bixio and Matteo Rulli

Sensors 2023, 23(11), 5210; https://doi.org/10.3390/s23115210 - 30 May 2023

Cited by 1 | Viewed by 1705

Abstract

We present a device- and network-based solution for automatic passnger counting that operates on the edge in real time. The proposed solution consists of a low-cost WiFi scanner device equipped with custom algorithms for dealing with MAC address randomization. Our low-cost scanner is able to capture and analyze 802.11 probe requests emitted by passengers’ devices such as laptops, smartphones, and tablets. The device is configured with a Python data-processing pipeline that combines data coming from different types of sensors and processes them on the fly. For the analysis task, we have devised a lightweight version of the DBSCAN algorithm. Our software artifact is designed in a modular way in order to accommodate possible extensions of the pipeline, e.g., either additional filters or data sources. Furthermore, we exploit multi-threading and multi-processing for speeding up the entire computation. The proposed solution has been tested with different types of mobile devices, obtaining promising experimental results. In this paper, we present the key ingredients of our edge computing solution. Full article

(This article belongs to the Special Issue Advanced Applications of WSNs and the IoT)

► Show Figures

Figure 1

28 pages, 1828 KiB

Open AccessArticle

Development and Analysis of a Distributed Leak Detection and Localisation System for Crude Oil Pipelines

by Safuriyawu Ahmed, Frédéric Le Mouël, Nicolas Stouls and Gislain Lipeme Kouyi

Sensors 2023, 23(9), 4298; https://doi.org/10.3390/s23094298 - 26 Apr 2023

Cited by 2 | Viewed by 2255

Abstract

Crude oil leakages and spills (OLS) are some of the problems attributed to pipeline failures in the oil and gas industry’s midstream sector. Consequently, they are monitored via several leakage detection and localisation techniques (LDTs) comprising classical methods and, recently, Internet of Things (IoT)-based systems via wireless sensor networks (WSNs). Although the latter techniques are proven to be more efficient, they are susceptible to other types of failures such as high false alarms or single point of failure (SPOF) due to their centralised implementations. Therefore, in this work, we present a hybrid distributed leakage detection and localisation technique (HyDiLLEch), which combines multiple classical LDTs. The technique is implemented in two versions, a single-hop and a double-hop version. The evaluation of the results is based on the resilience to SPOFs, the accuracy of detection and localisation, and communication efficiency. The results obtained from the placement strategy and the distributed spatial data correlation include increased sensitivity to leakage detection and localisation and the elimination of the SPOF related to the centralised LDTs by increasing the number of node-detecting and localising (NDL) leakages to four and six in the single-hop and double-hop versions, respectively. In addition, the accuracy of leakages is improved from 0 to 32 m in nodes that were physically close to the leakage points while keeping the communication overhead minimal. Full article

(This article belongs to the Special Issue Advanced Applications of WSNs and the IoT)

► Show Figures

Figure 1

22 pages, 877 KiB

Open AccessArticle

Implicit Overhearing Node-Based Multi-Hop Communication Scheme in IoT LoRa Networks

by Dick Mugerwa, Youngju Nam, Hyunseok Choi, Yongje Shin and Euisin Lee

Sensors 2023, 23(8), 3874; https://doi.org/10.3390/s23083874 - 10 Apr 2023

Cited by 4 | Viewed by 2104

Abstract

Long range (LoRa) is a low-power wide-area technology because it is eminent for robust long-distance, low-bitrate, and low-power communications in the unlicensed sub-GHz spectrum used for the Internet of things (IoT) networks. Recently, several multi-hop LoRa networks have proposed schemes with explicit relay nodes to partially mitigate the path loss and longer transmission time bottlenecks of the conventional single-hop LoRa by focusing more on coverage expansion. However, they do not consider improving the packet delivery success ratio (PDSR) and the packet reduction ratio (PRR) by using the overhearing technique. Thus, this paper proposes an implicit overhearing node-based multi-hop communication (IOMC) scheme in IoT LoRa networks, which exploits implicit relay nodes for performing the overhearing to promote relay operation while satisfying the duty cycle regulation. In IOMC, implicit relay nodes are selected as overhearing nodes (OHs) among end devices with a low spreading factor (SF) in order to improve PDSR and PRR for distant end devices (EDs). A theoretical framework for designing and determining the OH nodes to execute the relay operations was developed with consideration of the LoRaWAN MAC protocol. Simulation results verify that IOMC significantly increases the probability of successful transmission, performs best in high node density, and is more resilient to poor RSSI than the existing schemes. Full article

(This article belongs to the Special Issue Advanced Applications of WSNs and the IoT)

► Show Figures

Figure 1

25 pages, 796 KiB

Open AccessArticle

Sensor Clustering Using a K-Means Algorithm in Combination with Optimized Unmanned Aerial Vehicle Trajectory in Wireless Sensor Networks

by Thanh-Nam Tran, Thanh-Long Nguyen, Vinh Truong Hoang and Miroslav Voznak

Sensors 2023, 23(4), 2345; https://doi.org/10.3390/s23042345 - 20 Feb 2023

Cited by 5 | Viewed by 2374

Abstract

We examine a general wireless sensor network (WSN) model which incorporates a large number of sensors distributed over a large and complex geographical area. The study proposes solutions for a flexible deployment, low cost and high reliability in a wireless sensor network. To achieve these aims, we propose the application of an unmanned aerial vehicle (UAV) as a flying relay to receive and forward signals that employ nonorthogonal multiple access (NOMA) for a high spectral sharing efficiency. To obtain an optimal number of subclusters and optimal UAV positioning, we apply a sensor clustering method based on K-means unsupervised machine learning in combination with the gap statistic method. The study proposes an algorithm to optimize the trajectory of the UAV, i.e., the centroid-to-next-nearest-centroid (CNNC) path. Because a subcluster containing multiple sensors produces cochannel interference which affects the signal decoding performance at the UAV, we propose a diagonal matrix as a phase-shift framework at the UAV to separate and decode the messages received from the sensors. The study examines the outage probability performance of an individual WSN and provides results based on Monte Carlo simulations and analyses. The investigated results verified the benefits of the K-means algorithm in deploying the WSN. Full article

(This article belongs to the Special Issue Advanced Applications of WSNs and the IoT)

► Show Figures

Journal Menu

Journal Browser

Advanced Applications of WSNs and the IoT

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Related Special Issue

Published Papers (11 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI