sensors-logo

Journal Browser

Journal Browser

Innovative Restoration Technologies for the Spatial Scaling of Marine Restoration

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

Deadline for manuscript submissions: closed (28 February 2024) | Viewed by 998

Special Issue Editors


E-Mail Website
Guest Editor
1. Instituto de Cièncias del Mar (ICM-CSIC), Renewable Marine Resources ("Functioning and Vulnerability of Marine Ecosystems" Group), I E-08003 Barcelona, Spain
2. Stazione Zoologica Anton Dohrn, 80122 Naples, Italy
Interests: ecological monitoring; biological indicators; fisheries; cabled video-observatories; autonomous robotic platforms
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Agriculture and Forest Sciences (DAFNE), Via San Camillo de Lellis s.n.c., 01100 Viterbo, Italy
Interests: precision agriculture; machine learning; deep learning; precision forestry; condensed matter physics; spectroscopy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The United Nations (UN) has called for a decade of “Ecosystem Restoration”. In the marine realm, in-situ operations are often limited to the operating depths of SCUBA divers yet 99% of marine habitats exceed these depths. To address this issue, emerging robotic technologies should provide three fundamental lines of restoration action: (1) ecological surveying of areas pre-restoration to describe habitat heterogeneity and identify strategic sites, via high-resolution 3D image and acoustic-based tools; (2) in-situ manipulative actions including transferring/seeding organisms and placing colonization substrates to scale recovered surface to kilometre scale; and finally, (3) remote monitoring of ongoing operations and of post-restoration dynamics. Presently, the managing environment sector which is mostly interested by the robotic revolution, is agriculture. Most of the technological issues which limit the development of a largescale oceanic monitoring and restoration, are now solved in smart agriculture while actual challenges of that field are common to marine sciences. The impact due technological improvements such as AI-powered sensors, is deeply changing the field of smart agriculture and precision forestry, by increasing productivity, reducing waste, and improving sustainability. As such, the following Special Volume will contain information on marine in-situ intervention technologies by tele-operated and autonomous robotic platforms in relation to restoration of costal and deep-sea ecosystems. This will provide a platform for inter-sectoral dialogue between marine and precision agriculture scientists with the goal of transferring technological solutions to develop networks of marine platforms for in-situ intervention. Contributions on different aspects of marine and agriculture robotics technologies (e.g., AI routines for platforms navigation and autonomous intervention, arms and manipulation taxonomies, areas’ mapping and monitoring, strategic sensors and innovative combinations into operational payloads) are foreseen.

Dr. Jacopo Aguzzi
Dr. Luciano Ortenzi
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.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

11 pages, 3626 KiB  
Article
A High-Frequency and Real-Time Ground Remote Sensing System for Obtaining Water Quality Based on a Micro Hyper-Spectrometer
by Yunfei Li, Yanhu Fu, Ziyue Lang and Fuhong Cai
Sensors 2024, 24(6), 1833; https://doi.org/10.3390/s24061833 - 13 Mar 2024
Viewed by 632
Abstract
The safeguarding of scarce water resources is critically dependent on continuous water quality monitoring. Traditional methods like satellite imagery and automated underwater observation have limitations in cost-efficiency and frequency. Addressing these challenges, a ground-based remote sensing system for the high-frequency, real-time monitoring of [...] Read more.
The safeguarding of scarce water resources is critically dependent on continuous water quality monitoring. Traditional methods like satellite imagery and automated underwater observation have limitations in cost-efficiency and frequency. Addressing these challenges, a ground-based remote sensing system for the high-frequency, real-time monitoring of water parameters has been developed. This system is encased in a durable stainless-steel shell, suited for outdoor environments, and features a compact hyperspectral instrument with a 4 nm spectral resolution covering a 350–950 nm wavelength range. In addition, it also integrates solar power, Wi-Fi, and microcomputers, enabling the autonomous long-term monitoring of water quality. Positioned on a rotating platform near the shore, this setup allows the spectrometer to quickly capture the reflective spectrum of water within 3 s. To assess its effectiveness, an empirical method correlated the reflective spectrum with the actual chlorophyll a(Chla) concentration. Machine learning algorithms were also used to analyze the spectrum’s relationship with key water quality indicators like total phosphorus (TP), total nitrogen (TN), and chemical oxygen demand (COD). Results indicate that the band ratio algorithm accurately determines Chla concentration (R-squared = 0.95; RMSD = 0.06 mg/L). For TP, TN, and COD, support vector machine (SVM) and linear models were highly effective, yielding R-squared values of 0.93, 0.92, and 0.88, respectively. This innovative hyperspectral water quality monitoring system is both practical and reliable, offering a new solution for effective water quality assessment. Full article
Show Figures

Figure 1

Back to TopTop