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Sustainable Environmental Sensing Systems
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Sustainable Environmental Sensing Systems

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

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 16683

Special Issue Editors

Dr. Catia Prandi

E-Mail Website
Guest Editor
Dipartimento di Informatica-Scienza e Ingegneria, University of Bologna, 40126 Bologna, Italy
Interests: human–computer interactions; citizen science; pervasive computing and IoT for social good and sustainability in the urban environment
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Pietro Manzoni

E-Mail Website
Guest Editor
Department of Computer Engineering (DISCA), Universitat Politècnica de València, 46022 Valencia, Spain
Interests: mobile networks and systems; internet of things
Special Issues, Collections and Topics in MDPI journals
Dr. Ruidong Li

E-Mail Website
Guest Editor
National Institute of Information and Communications Technology (NICT), Tokyo, Japan
Interests: IoT; big data networking; intelligent internet edge; mobile networks

Special Issue Information

Dear Colleagues,

September 2020 will be the fifth anniversary of the launch of the United Nations 2030 Agenda, a plan for action that details the 17 Sustainable Development Goals (SDGs), where the environment underlies each of those goals—from eliminating hunger to reducing inequalities to building sustainable communities around the world.
Indeed, monitoring environmental-related conditions is fundamental to achieve the SDGs and mitigate climate change. In this context, different challenges need to be addressed, from designing and developing more sustainable, ecological, and efficient smart sensing objects that need to be energy-efficient and low-power, and able to communicate via wide-area networks, to turning to the general public for deploying such systems and crowdsourcing the collection of data using IoT and mobile sensing devices.
This Special Issue aims at presenting and showcasing the latest advances in sustainable environmental sensing systems to monitor different urban and rural conditions in order to improve people’s quality of life and reduce climate change, toward sustainable development. Sensing systems can range from dynamic (mobile) to purely static deployments.

The “Sustainable Environmental Sensing Systems” SI perfectly fits with the Sensors scope, due to the wide number and varieties of sensors exploited in such systems, sensors that need to be sustainable, to communicate in an efficient, low-consuming, and long-distance fashion, opening several challenges that still need to be investigated.

Dr. Catia Prandi
Prof. Dr. Pietro Manzoni
Dr. Ruidong Li
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

  • environmental monitoring
  • pervasive sensing
  • crowdsensing
  • citizen science
  • rural IoT
  • SDGs

Published Papers (5 papers)

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Research

18 pages, 4245 KiB  
Article
Rock Surface Strain In Situ Monitoring Affected by Temperature Changes at the Požáry Field Lab (Czechia)
by Ondřej Racek, Jan Balek, Marco Loche, Daniel Vích and Jan Blahůt
Sensors 2023, 23(4), 2237; https://0-doi-org.brum.beds.ac.uk/10.3390/s23042237 - 16 Feb 2023
Cited by 1 | Viewed by 1563
Abstract
The evaluation of strain in rock masses is crucial information for slope stability studies. For this purpose, a monitoring system for analyzing surface strain using resistivity strain gauges has been tested. Strain is a function of stress, and it is known that stress [...] Read more.
The evaluation of strain in rock masses is crucial information for slope stability studies. For this purpose, a monitoring system for analyzing surface strain using resistivity strain gauges has been tested. Strain is a function of stress, and it is known that stress affects the mechanical properties of geomaterials and can lead to the destabilization of rock slopes. However, stress is difficult to measure in situ. In industrial practice, resistivity strain gauges are used for strain measurement, allowing even small strain changes to be recorded. This setting of dataloggers is usually expensive and there is no accounting for the influence of exogenous factors. Here, the aim of applying resistivity strain gauges in different configurations to measure surface strain in natural conditions, and to determine how the results are affected by factors such as temperature and incoming solar radiation, has been pursued. Subsequently, these factors were mathematically estimated, and a data processing system was created to process the results of each configuration. Finally, the new strategy was evaluated to measure in situ strain by estimating the effect of temperature. The approach highlighted high theoretical accuracy, hence the ability to detect strain variations in field conditions. Therefore, by adjusting for the influence of temperature, it is potentially possible to measure the deformation trend more accurately, while maintaining a lower cost for the sensors. Full article
(This article belongs to the Special Issue Sustainable Environmental Sensing Systems)
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26 pages, 10317 KiB  
Article
Improvement of On-Site Sensor for Simultaneous Determination of Phosphate, Silicic Acid, Nitrate plus Nitrite in Seawater
by Mahmoud Fatehy Altahan, Mario Esposito and Eric P. Achterberg
Sensors 2022, 22(9), 3479; https://0-doi-org.brum.beds.ac.uk/10.3390/s22093479 - 03 May 2022
Cited by 10 | Viewed by 3069
Abstract
Accurate, on-site determinations of macronutrients (phosphate (PO43−), nitrate (NO3−), and silicic acid (H4SiO4)) in seawater in real time are essential to obtain information on their distribution, flux, and role in marine biogeochemical cycles. [...] Read more.
Accurate, on-site determinations of macronutrients (phosphate (PO43−), nitrate (NO3−), and silicic acid (H4SiO4)) in seawater in real time are essential to obtain information on their distribution, flux, and role in marine biogeochemical cycles. The development of robust sensors for long-term on-site analysis of macronutrients in seawater is a great challenge. Here, we present improvements of a commercial automated sensor for nutrients (including PO43−, H4SiO4, and NO2− plus NO3−), suitable for a variety of aquatic environments. The sensor uses the phosphomolybdate blue method for PO43−, the silicomolybdate blue method for H4SiO4 and the Griess reagent method for NO2−, modified with vanadium chloride as reducing agent for the determination of NO3−. Here, we report the optimization of analytical conditions, including reaction time for PO43− analysis, complexation time for H4SiO4 analysis, and analyte to reagent ratio for NO3− analysis. The instrument showed wide linear ranges, from 0.2 to 100 μM PO43−, between 0.2 and 100 μM H4SiO4, from 0.5 to 100 μM NO3−, and between 0.4 and 100 μM NO2−, with detection limits of 0.18 μM, 0.15 μM, 0.45 μM, and 0.35 μM for PO43−, H4SiO4, NO3−, and NO2−, respectively. The analyzer showed good precision with a relative standard deviation of 8.9% for PO43−, 4.8% for H4SiO4, and 7.4% for NO2− plus NO3− during routine analysis of certified reference materials (KANSO, Japan). The analyzer performed well in the field during a 46-day deployment on a pontoon in the Kiel Fjord (located in the southwestern Baltic Sea), with a water supply from a depth of 1 m. The system successfully collected 443, 440, and 409 on-site data points for PO43−, Σ(NO3− + NO2−), and H4SiO4, respectively. Time series data agreed well with data obtained from the analysis of discretely collected samples using standard reference laboratory procedures and showed clear correlations with key hydrographic parameters throughout the deployment period. Full article
(This article belongs to the Special Issue Sustainable Environmental Sensing Systems)
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13 pages, 1506 KiB  
Article
MOSQUITO EDGE: An Edge-Intelligent Real-Time Mosquito Threat Prediction Using an IoT-Enabled Hardware System
by Shyam Polineni, Om Shastri, Avi Bagchi, Govind Gnanakumar, Sujay Rasamsetti and Prabha Sundaravadivel
Sensors 2022, 22(2), 695; https://0-doi-org.brum.beds.ac.uk/10.3390/s22020695 - 17 Jan 2022
Cited by 7 | Viewed by 4335
Abstract
Species distribution models (SDMs) that use climate variables to make binary predictions are effective tools for niche prediction in current and future climate scenarios. In this study, a Hutchinson hypervolume is defined with temperature, humidity, air pressure, precipitation, and cloud cover climate vectors [...] Read more.
Species distribution models (SDMs) that use climate variables to make binary predictions are effective tools for niche prediction in current and future climate scenarios. In this study, a Hutchinson hypervolume is defined with temperature, humidity, air pressure, precipitation, and cloud cover climate vectors collected from the National Oceanic and Atmospheric Administration (NOAA) that were matched to mosquito presence and absence points extracted from NASA’s citizen science platform called GLOBE Observer and the National Ecological Observatory Network. An 86% accurate Random Forest model that operates on binary classification was created to predict mosquito threat. Given a location and date input, the model produces a threat level based on the number of decision trees that vote for a presence label. The feature importance chart and regression show a positive, linear correlation between humidity and mosquito threat and between temperature and mosquito threat below a threshold of 28 °C. In accordance with the statistical analysis and ecological wisdom, high threat clusters in warm, humid regions and low threat clusters in cold, dry regions were found. With the model running on the cloud and within ArcGIS Dashboard, accurate and granular real-time threat level predictions can be made at any latitude and longitude. A device leveraging Global Positioning System (GPS) smartphone technology and the Internet of Things (IoT) to collect and analyze data on the edge was developed. The data from the edge device along with its respective date and location collected are automatically inputted into the aforementioned Random Forest model to provide users with a real-time threat level prediction. This inexpensive hardware can be used in developing countries that are threatened by vector-borne diseases or in remote areas without cloud connectivity. Such devices can be linked with citizen science mosquito data platforms to build training datasets for machine learning based SDMs. Full article
(This article belongs to the Special Issue Sustainable Environmental Sensing Systems)
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29 pages, 16494 KiB  
Article
A Fishery Water Quality Monitoring and Prediction Evaluation System for Floating UAV Based on Time Series
by Lei Cheng, Xiyue Tan, Dong Yao, Wenxia Xu, Huaiyu Wu and Yang Chen
Sensors 2021, 21(13), 4451; https://0-doi-org.brum.beds.ac.uk/10.3390/s21134451 - 29 Jun 2021
Cited by 17 | Viewed by 3052
Abstract
In recent years, fishery has developed rapidly. For the vital interests of the majority of fishermen, this paper makes full use of Internet of Things and air–water amphibious UAV technology to provide an integrated system that can meet the requirements of fishery water [...] Read more.
In recent years, fishery has developed rapidly. For the vital interests of the majority of fishermen, this paper makes full use of Internet of Things and air–water amphibious UAV technology to provide an integrated system that can meet the requirements of fishery water quality monitoring and prediction evaluation. To monitor target water quality in real time, the water quality monitoring of the system is mainly completed by a six-rotor floating UAV that carries water quality sensors. The GPRS module is then used to realize remote data transmission. The prediction of water quality transmission data is mainly realized by the algorithm of time series comprehensive analysis. The evaluation rules are determined according to the water quality evaluation standards to evaluate the predicted water quality data. Finally, the feasibility of the system is proved through experiments. The results show that the system can effectively evaluate fishery water quality under different weather conditions. The prediction accuracy of the pH, dissolved oxygen content, and ammonia nitrogen content of fishery water quality can reach 99%, 98%, and 99% on sunny days, and reach 92%, 98%, and 91% on rainy days. Full article
(This article belongs to the Special Issue Sustainable Environmental Sensing Systems)
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18 pages, 5574 KiB  
Article
Towards a Sustainable City for Cyclists: Promoting Safety through a Mobile Sensing Application
by Pablo Boronat, Miguel Pérez-Francisco, Carlos T. Calafate and Juan-Carlos Cano
Sensors 2021, 21(6), 2116; https://0-doi-org.brum.beds.ac.uk/10.3390/s21062116 - 17 Mar 2021
Cited by 6 | Viewed by 2288
Abstract
Riding a bicycle is a great manner to contribute to the preservation of our ecosystem. Cycling helps to reduce air pollution and traffic congestion, and so, it is one of the simplest ways to lower the environmental footprint of people. However, the cohabitation [...] Read more.
Riding a bicycle is a great manner to contribute to the preservation of our ecosystem. Cycling helps to reduce air pollution and traffic congestion, and so, it is one of the simplest ways to lower the environmental footprint of people. However, the cohabitation of cars and vulnerable road users, such as bikes, scooters, or pedestrians, is prone to cause accidents with serious consequences. In this context, technological solutions are sought that enable the generation of alerts to prevent these accidents, thereby promoting a safer city for these road users, and a cleaner environment. Alert systems based on smartphones can alleviate these situations since nearly all people carry such a device while traveling. In this work, we test the suitability of a smartphone based alert system, determining the most adequate communications architecture. Two protocols have been designed to send position and alert messages to/from a centralized server over 4G cellular networks. One of the protocols is implemented using a REST architecture on top of the HTTP protocol, and the other one is implemented over the UDP protocol. We show that the proposed alarm system is feasible regarding communication response time, and we conclude that the application should be implemented over the UDP protocol, as response times are about three times better than for the REST implementation. We tested the applications in real deployments, finding that drivers are warned of the presence of bicycles when closer than 150 m, having enough time to pay attention to the situation and drive more carefully to avoid a collision. Full article
(This article belongs to the Special Issue Sustainable Environmental Sensing Systems)
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