Cohen-Manrique et al. (2025) Emerging trends in IoT for aquatic systems: a systematic literature review

Identification

• Journal: Frontiers in Water
• Year: 2025
• Date: 2025-12-04
• Authors: Carlos S. Cohen-Manrique, Sérgio Camacho-León, J.L. Villa
• DOI: 10.3389/frwa.2025.1699240

Research Groups

• Vatio Laboratory, CBIyA Department, Corporación Universitaria del Caribe-CECAR, Sincelejo, Colombia
• Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, Mexico
• Engineering Department, Universidad Tecnológica de Bolívar-UTB, Cartagena, Colombia

Short Summary

This systematic literature review analyzes 458 articles published between 2015 and 2025 to identify emerging IoT-based strategies for surface and groundwater monitoring and management. It finds LoRa as the most adopted transmission technology and highlights the growing relevance of remote IoT, satellite-assisted sensing, and digital twins, proposing an integrated IoT architecture for aquatic systems.

Objective

• To identify and analyze emerging trends in IoT-based technological strategies for monitoring and managing surface and groundwater systems, highlighting their applications, strengths, and challenges.

Study Configuration

• Spatial Scale: Global (systematic review of literature), focusing on freshwater systems (surface and groundwater).
• Temporal Scale: Articles published between 2015 and 2025.

Methodology and Data

• Models used: Not applicable (systematic literature review). The review analyzes various IoT-based models, algorithms (e.g., Random Forest, Decision Trees, Q-learning, ANN, SVM, Kalman Filter), and architectures.
• Data sources: Scopus and Web of Science (WoS) databases, supplemented by IEEE, DBLP, and ACM. A total of 458 peer-reviewed articles were analyzed.

Main Results

• LoRa is the most widely adopted data transmission technology due to its long-range coverage, scalability, and low energy consumption.
• Emerging innovations include remote IoT, satellite-assisted sensing, and digital twins for real-time hydrological monitoring and simulation.
• Approximately 59% of reviewed studies incorporate machine learning techniques for real-time data visualization, predictive analytics, and scenario generation.
• Common sensors include DS18B20 and DHT22 for temperature, SEN0161 and Atlas Scientific for pH, SEN0189 and TSD-10 for turbidity, and gravity analog TDS and SEN0244 for total dissolved solids.
• A four-layer IoT architecture (perception, transmission, platform, application) is proposed for aquatic systems monitoring.
• The review highlights the need for more accessible, affordable, and interoperable IoT solutions, especially in resource-constrained regions, and identifies a significant gap in cybersecurity analysis.

Contributions

• Identification of the most relevant IoT technologies for effective water resource monitoring.
• Classification of key domains within AI and IoT as enabling tools for monitoring and sustainable management of surface water and groundwater systems.
• Analysis of prevailing global trends in the development of sensor networks, computational algorithms, and communication technologies tailored for aquatic environments.
• Proposal of a general reference framework for IoT-based monitoring architectures for aquatic systems.
• Highlighting the need for more accessible, affordable, and interoperable IoT solutions, particularly in developing regions, and addressing the cybersecurity gap.

Funding

• The authors declare that no financial support was received for the research and/or publication of this article.

Citation

@article{CohenManrique2025Emerging,
  author = {Cohen-Manrique, Carlos S. and Camacho-León, Sérgio and Villa, J.L.},
  title = {Emerging trends in IoT for aquatic systems: a systematic literature review},
  journal = {Frontiers in Water},
  year = {2025},
  doi = {10.3389/frwa.2025.1699240},
  url = {https://doi.org/10.3389/frwa.2025.1699240}
}