Evidence map›Paper›PMID 41829526›Full record

ReviewSensors (Basel, Switzerland)2026

A Survey of Modern Data Acquisition and Analysis Systems for Environmental Risk Monitoring in Aquatic Ecosystems.

Nicola Perra, Daniele Giusto, Matteo Anedda

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Nicola PerraConsorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT), Unità di Ricerca di Cagliari (CNIT UdR Cagliari), Department of Electrical and Electronic Engineering, University of Cagliari, 09123 Cagliari, Italy.
Daniele GiustoConsorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT), Unità di Ricerca di Cagliari (CNIT UdR Cagliari), Department of Electrical and Electronic Engineering, University of Cagliari, 09123 Cagliari, Italy.ORCID 0000-0002-6450-4609
Matteo AneddaConsorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT), Unità di Ricerca di Cagliari (CNIT UdR Cagliari), Department of Electrical and Electronic Engineering, University of Cagliari, 09123 Cagliari, Italy.ORCID 0000-0003-1910-9551

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This survey is an integrated and complete summary of the strategies and technological systems of surveying environmental hazard in marine, freshwater, and brackish environments. Contrary to the previous articles where the separate parts of the monitoring chain are investigated or certain environments/enabling technologies are considered, the given work has a cross-domain approach that unites sensing modalities, data acquisition schemes, communication schemes, operational platforms, data analytics, energy management schemes, and regulatory compliance into one consistent framework. The survey systematically examines the entire sensing-to-cloud pipeline, which includes sensor technologies, data acquisition systems, telecommunication infrastructures, and a variety of monitoring platforms such as buoy-based systems, Unmanned Surface Vehicles (USVs), Autonomous Underwater Vehicles (AUVs), and Unmanned Aerial Vehicles (UAVs). In addition, it touches on the administration and examination of mass environmental data, including cloud-based systems and AI-based methods of automated feature identification, anomaly recognition and predictive modeling. The key points of the autonomy of the system, including power supply solutions and energy-conscious management, are also mentioned, as well as the relevant regulations on the environmental monitoring nationally, at the European level, and globally. This paper presents a systematic six-step design process of aquatic environmental monitoring systems: (1) risk categorization, (2) physical data acquisition systems, (3) monitoring platforms, (4) data management & analytics, (5) energy autonomy strategies, and (6) regulatory compliance. The systematic framework offers researchers and practitioners practical guidelines to follow when designing end-to-end systems, thus completing the gaps in the historically disjointed research strands and going beyond the traditional domain- and technology-based studies.

Indexed as

aquatic environmental monitoringartificial intelligence and machine learningautonomous monitoring platformsclimate change and aquatic ecosystemsdata acquisition and telemetryenvironmental risk assessmentin situ sensor networksinternet of Things (IoT) for environmental monitoringlow-power wide-area networks (LPWAN)water quality monitoring systems

Identifiers

PMID41829526
PMCPMC12986620

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.