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Wireless Sensor Networks for Environmental Monitoring
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Wireless Sensor Networks for Environmental Monitoring

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

Deadline for manuscript submissions: closed (10 December 2020) | Viewed by 29962

Special Issue Editors

Dr. Annie Lanzolla

E-Mail Website
Guest Editor
Department of Electrical and Information Engineering, Polytechnic University of Bari, 70125 Bari, Italy
Interests: environmental monitoring; sensor network; e-health; smart sensor; signal and image processing
Dr. Maurizio Spadavecchia

E-Mail Website
Guest Editor
Department of Electrical and Information Engineering, Politecnico di Bari, Bari, Italy
Interests: smart sensors; measurements on power systems; smart grid; wide area measurements; signal processing; distributed measurement system; energy harvesting
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Environmental monitoring is fundamental to understand our ecosystem, to prevent adverse effects on human health and environment, and as a tool to evaluate the effectiveness of regulations. Recent advances in technology, instrumentation, and procedures have pushed forward laboratory capabilities in testing and analyzing soil, water, gas, and biota specimens and have created new opportunities for real-time monitoring through, for example, distributed sensor networks or wireless sensor networks. These architectures are widely used in environmental monitoring because they offer many important benefits, such as real time access to data, covering wide areas, long term monitoring and system scalability.

This Special Issue aims to survey and discuss the state of the art, difficulties, innovations, and improvements on environmental data acquisition, monitoring, analysis, and risk assessment and management. The observed trends in the pollution of soil, air, and water, the global warming and the increased awareness of environmental themes urge scientists to work on effective methods to be able to detect and react to environmental parameter changes in a timely and authoritative manner. Some of these measurements are particularly challenging, due to the large range of spatial and time scales, the large amount of data to store and process, the high value of specimens, and the effort to reduce costs while maintaining accuracy.

You are welcome to submit an unpublished original research work related to the theme of “Wireless Sensor Networks for Environmental Monitoring” that is proposed to welcome Sensors’ 20th birthday.

Dr. Annie Lanzolla
Dr. Maurizio Spadavecchia
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

  • Analytical methods, sensors, and instruments for measuring environmental variables and pollution
  • Environmental noise and vibration pollution
  • Renewable energy sources monitoring
  • Remote sensing, airborne-based, and ground-based systems
  • Sensors, sensor networks and devices
  • Ambient intelligent and smart home
  • Environmental data and big data processing and dissemination, image processing
  • High performance computing for extreme events and climate changes
  • Expert systems and decision-making systems
  • Quality assurance and quality control of measurements

Published Papers (7 papers)

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21 pages, 7836 KiB  
Article
Wireless Sensor Networks for Noise Measurement and Acoustic Event Recognitions in Urban Environments
by Liyan Luo, Hongming Qin, Xiyu Song, Mei Wang, Hongbing Qiu and Zou Zhou
Sensors 2020, 20(7), 2093; https://doi.org/10.3390/s20072093 - 8 Apr 2020
Cited by 21 | Viewed by 4348
Abstract
Nowadays, urban noise emerges as a distinct threat to people’s physiological and psychological health. Previous works mainly focus on the measurement and mapping of the noise by using Wireless Acoustic Sensor Networks (WASNs) and further propose some methods that can effectively reduce the [...] Read more.
Nowadays, urban noise emerges as a distinct threat to people’s physiological and psychological health. Previous works mainly focus on the measurement and mapping of the noise by using Wireless Acoustic Sensor Networks (WASNs) and further propose some methods that can effectively reduce the noise pollution in urban environments. In addition, the research on the combination of environmental noise measurement and acoustic events recognition are rapidly progressing. In a real-life application, there still exists the challenges on the hardware design with enough computational capacity, the reduction of data amount with a reasonable method, the acoustic recognition with CNNs, and the deployment for the long-term outdoor monitoring. In this paper, we develop a novel system that utilizes the WASNs to monitor the urban noise and recognize acoustic events with a high performance. Specifically, the proposed system mainly includes the following three stages: (1) We used multiple sensor nodes that are equipped with various hardware devices and performed with assorted signal processing methods to capture noise levels and audio data; (2) the Convolutional Neural Networks (CNNs) take such captured data as inputs and classify them into different labels such as car horn, shout, crash, explosion; (3) we design a monitoring platform to visualize noise maps, acoustic event information, and noise statistics. Most importantly, we consider how to design effective sensor nodes in terms of cost, data transmission, and outdoor deployment. Experimental results demonstrate that the proposed system can measure the urban noise and recognize acoustic events with a high performance in real-life scenarios. Full article
(This article belongs to the Special Issue Wireless Sensor Networks for Environmental Monitoring)
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3 pages, 167 KiB  
Editorial
Wireless Sensor Networks for Environmental Monitoring
by Anna Lanzolla and Maurizio Spadavecchia
Sensors 2021, 21(4), 1172; https://doi.org/10.3390/s21041172 - 7 Feb 2021
Cited by 30 | Viewed by 5167
Abstract
In this editorial, an overview of the content of the Special Issue on “Wireless Sensor Networks for Environmental Monitoring” is provided [...] Full article
(This article belongs to the Special Issue Wireless Sensor Networks for Environmental Monitoring)
18 pages, 5036 KiB  
Article
A Nonparametric SVM-Based REM Recapitulation Assisted by Voluntary Sensing Participants under Smart Contracts on Blockchain
by Seung Bum Park and Won Cheol Lee
Sensors 2020, 20(12), 3574; https://doi.org/10.3390/s20123574 - 24 Jun 2020
Cited by 2 | Viewed by 2230
Abstract
This paper proposes a blockchain-based automated frequency coordination system (BAFCS) for secure and reliable spectrum sharing without causing any harmful interference to an existing system. For the exact assessment of whether the incumbent is interfered with by the spectrum sharer, the received signal [...] Read more.
This paper proposes a blockchain-based automated frequency coordination system (BAFCS) for secure and reliable spectrum sharing without causing any harmful interference to an existing system. For the exact assessment of whether the incumbent is interfered with by the spectrum sharer, the received signal strength (RSS) associated with the incumbent should be measured with sufficient accuracy at every location within the area of interest. However, since it requires brute force to carry out empirical measurements around an entire region, to lessen the burden, only the confined portion of the RSSs associated with the incumbent as a kind of primary user are observed and the omitted residuals are conventionally estimated by carrying out the well-known Kriging interpolation with regard to the geostatistical characteristics. This paper proposes a frequency coordination system capable of identifying whether a requested frequency band can be eligible for spectrum sharing while exchanging adequate information over blockchain network to confirm the usability. This paper proposes the Support Vector Machine (SVM)-based Kriging interpolation for recapitulating the radio environment map (REM) when only a fraction of the RSS measurements is acquired by the voluntary sensing participant (VSP). The nonparametric modeling approach for variograms proposed in this paper was determined to have a vital role in making a confident decision regarding spectrum sharing. The simulation result confirmed the effectiveness and the superiority of the proposed BAFCS with several affirmative features, such as enabling the consensus-based approval of spectrum sharing, the secure transaction of the information, and reliable assurance of no harmful interference. Full article
(This article belongs to the Special Issue Wireless Sensor Networks for Environmental Monitoring)
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25 pages, 3427 KiB  
Article
A Robot Hybrid Hierarchical Network for Sensing Environmental Variables of a Smart Grid
by Jiayang Liu, Gongping Wu, Fei Fan and Yuxin Li
Sensors 2020, 20(19), 5521; https://doi.org/10.3390/s20195521 - 26 Sep 2020
Cited by 4 | Viewed by 2208
Abstract
With the rapid development of the social economy, high-voltage transmission lines as power supply infrastructure are increasing, subsequently presenting a new challenge to the effective monitoring of transmission lines. The dynamic sensor network integrated with robots can effectively solve the elastic monitoring of [...] Read more.
With the rapid development of the social economy, high-voltage transmission lines as power supply infrastructure are increasing, subsequently presenting a new challenge to the effective monitoring of transmission lines. The dynamic sensor network integrated with robots can effectively solve the elastic monitoring of transmission lines, but the problems of real-time performance, energy consumption and economy of the network need to be solved. To solve this problem, a dynamic network deployment method based on the hybrid hierarchical network (HHN) is proposed to realize a low-cost, energy-saving and real-time dynamic sensing system for overhead high-voltage transmission lines. Through case analysis and simulation, combined with the vague set multi-attribute decision-making method (MADM) with scheme preference, the network deployment and optimization results under multi-parameter constraints are obtained. Full article
(This article belongs to the Special Issue Wireless Sensor Networks for Environmental Monitoring)
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31 pages, 25227 KiB  
Article
A DIY Low-Cost Wireless Wind Data Acquisition System Used to Study an Arid Coastal Foredune
by Antonio C. Domínguez-Brito, Jorge Cabrera-Gámez, Manuel Viera-Pérez, Eduardo Rodríguez-Barrera and Luis Hernández-Calvento
Sensors 2020, 20(4), 1064; https://doi.org/10.3390/s20041064 - 15 Feb 2020
Cited by 11 | Viewed by 5316
Abstract
Environmental studies on coastal dune systems are faced with a considerable cost barrier due to the cost of the instrumentation and sensory equipment required for data collection. These systems play an important role in coastal areas as a protection against erosion and as [...] Read more.
Environmental studies on coastal dune systems are faced with a considerable cost barrier due to the cost of the instrumentation and sensory equipment required for data collection. These systems play an important role in coastal areas as a protection against erosion and as providers of stability to coastal sedimentary deposits. The DIY (Do-It-Yourself) approach to data acquisition can reduce the cost of these environmental studies. In this paper, a low-cost DIY wireless wind data acquisition system is presented which reduces the cost barrier inherent to these types of studies. The system is deployed for the analysis of the foredune of Maspalomas, an arid dune field situated on the south coast of Gran Canaria (Canary Islands, Spain), for the specific purpose of studying the dynamics of a dune type (tongue dunes), which is typical of this environment. The results obtained can be of interest for the study of these coastal environments at both the local level, for the management of this particular dune field, and at the general level for other similar dune fields around the world. Full article
(This article belongs to the Special Issue Wireless Sensor Networks for Environmental Monitoring)
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20 pages, 5966 KiB  
Article
EDTD-SC: An IoT Sensor Deployment Strategy for Smart Cities
by Ibtihal Alablani and Mohammed Alenazi
Sensors 2020, 20(24), 7191; https://doi.org/10.3390/s20247191 - 15 Dec 2020
Cited by 38 | Viewed by 4985
Abstract
A smart city is a geographical area that uses modern technologies to facilitate the lives of its residents. Wireless sensor networks (WSNs) are important components of smart cities. Deploying IoT sensors in WSNs is a challenging aspect of network design. Sensor deployment is [...] Read more.
A smart city is a geographical area that uses modern technologies to facilitate the lives of its residents. Wireless sensor networks (WSNs) are important components of smart cities. Deploying IoT sensors in WSNs is a challenging aspect of network design. Sensor deployment is performed to achieve objectives like increasing coverage, strengthening connectivity, improving robustness, or increasing the lifetime of a given WSN. Therefore, a sensor deployment method must be carefully designed to achieve such objective functions without exceeding the available budget. This study introduces a novel deployment algorithm, called the Evaluated Delaunay Triangulation-based Deployment for Smart Cities (EDTD-SC), which targets not only sensor distribution, but also sink placement. Our algorithm utilizes Delaunay triangulation and k-means clustering to find optimal locations to improve coverage while maintaining connectivity and robustness with obstacles existence in sensing area. The EDTD-SC has been applied to real-world areas and cities, such as Midtown Manhattan in New York in the United States of America. The results show that the EDTD-SC outperforms random and regular deployments in terms of area coverage and end-to-end-delay by 29.6% and 29.7%, respectively. Further, it exhibits significant performance in terms of resilience to attacks. Full article
(This article belongs to the Special Issue Wireless Sensor Networks for Environmental Monitoring)
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23 pages, 8588 KiB  
Article
Fast Detection of Olive Trees Affected by Xylella Fastidiosa from UAVs Using Multispectral Imaging
by Attilio Di Nisio, Francesco Adamo, Giuseppe Acciani and Filippo Attivissimo
Sensors 2020, 20(17), 4915; https://doi.org/10.3390/s20174915 - 31 Aug 2020
Cited by 45 | Viewed by 4966
Abstract
Xylella fastidiosa (Xf) is a well-known bacterial plant pathogen mainly transmitted by vector insects and is associated with serious diseases affecting a wide variety of plants, both wild and cultivated; it is known that over 350 plant species are prone to [...] Read more.
Xylella fastidiosa (Xf) is a well-known bacterial plant pathogen mainly transmitted by vector insects and is associated with serious diseases affecting a wide variety of plants, both wild and cultivated; it is known that over 350 plant species are prone to Xf attack. In olive trees, it causes olive quick decline syndrome (OQDS), which is currently a serious threat to the survival of hundreds of thousands of olive trees in the south of Italy and in other countries in the European Union. Controls and countermeasures are in place to limit the further spreading of the bacterium, but it is a tough war to fight mainly due to the invasiveness of the actions that can be taken against it. The most effective weapons against the spread of Xf infection in olive trees are the detection of its presence as early as possible and attacks to the development of its vector insects. In this paper, image processing of high-resolution visible and multispectral images acquired by a purposely equipped multirotor unmanned aerial vehicle (UAV) is proposed for fast detection of Xf symptoms in olive trees. Acquired images were processed using a new segmentation algorithm to recognize trees which were subsequently classified using linear discriminant analysis. Preliminary experimental results obtained by flying over olive groves in selected sites in the south of Italy are presented, demonstrating a mean Sørensen–Dice similarity coefficient of about 70% for segmentation, and 98% sensitivity and 93% precision for the classification of affected trees. The high similarity coefficient indicated that the segmentation algorithm was successful at isolating the regions of interest containing trees, while the high sensitivity and precision showed that OQDS can be detected with a low relative number of both false positives and false negatives. Full article
(This article belongs to the Special Issue Wireless Sensor Networks for Environmental Monitoring)
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