Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Citizen science is often used as an approach for participatory water quality monitoring; however, its application in aquaculture remains limited. This study evaluates the current state of citizen science in monitoring water quality, with a particular focus on its implications for aquaculture practices. A systematic literature review was conducted using the Scopus and Web of Science databases to explore (1) common approaches for setting up and running such projects, (2) frequently used data collection tools and techniques, and (3) key water quality parameters. An in-depth review of 51 publications shows that citizen science studies are geographically concentrated in North America and Europe, with fewer studies in other regions. Most citizen science projects follow contributory models with a top-down approach, where scientists design research and citizens contribute data. Among the monitored parameters, chemical indicators, such as pH, are the most commonly monitored due to their significance in aquatic ecosystems and the availability of affordable test kits. These kits are widely used due to their ease of use and accessibility. However, the adoption of Internet of Things (IoT) technology remains limited, despite its potential to improve real-time monitoring and data accuracy. IoT-based systems, such as sensor boxes, can enhance citizen science by enabling automated data collection and expanding monitoring capabilities. Strengthening the integration of real-time monitoring technologies and broadening the range of monitored parameters could enhance the role of citizen science in aquaculture, supporting more effective and sustainable water quality management.
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Source |
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http://dx.doi.org/10.1007/s00267-025-02261-8 | DOI Listing |