Applied Artificial Intelligence and Advanced Sensing for Real-World Water Quality Monitoring
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".
Deadline for manuscript submissions: 20 May 2026 | Viewed by 38
Special Issue Editors
Interests: sewer processes; wastewater treatment; zero liquid discharge; reclaimed water techniques; urban runoff pollutants transfer; biological reactor control in wastewater treatment plants
Special Issues, Collections and Topics in MDPI journals
Interests: embedded electronics; machine learning; image processing; security and defense; indirect monitoring
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Water quality analysis and management currently face challenges in detecting emerging contaminants, pathogens, and eutrophication phenomena such as cyanobacterial blooms early. Rapid and accurate identification of these risks is essential to safeguard aquatic ecosystems and public health. In this context, integrating new sensing technologies and machine learning techniques offers unique opportunities to develop more efficient, accurate, and sustainable monitoring systems.
This Special Issue will focus on research that combines traditional analytical approaches with technological innovations, including advanced sensors, portable analytical systems, indirect characterisation techniques, and machine-learning-based predictive models. Special emphasis will be given to studies that use artificial intelligence to estimate and predict parameters related to the presence of pathogens, organic pollutants, phytoplankton and cyanobacteria, and other factors that deteriorate water quality.
Likewise, the submission of papers that develop real-time detection and prediction methodologies, big data applications in water quality management, integration of remote sensing with in situ data, and proposals for autonomous systems capable of improving monitoring and decision-making in urban, agricultural, and natural contexts is encouraged. This Special Issue aims to serve as a platform for interdisciplinary exchange of innovative solutions that advance smarter, more resilient water management tools.
Dr. Juan Tomás García-Bermejo
Guest Editor
Dr. Daniel Carreres Prieto
Guest Editor Assistant
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 250 words) can be sent to the Editorial Office for assessment.
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. Water 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
- water quality
- pathogens
- cyanobacteria
- machine learning
- indirect characterization
- prediction
- detection
- environmental monitoring
- sensors
- big data
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