ArticleSensors (Basel, Switzerland)2022
A Low-Cost AI Buoy System for Monitoring Water Quality at Offshore Aquaculture Cages.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Development of a Cost-Effective Multiparametric Probe for Continuous Real-Time Monitoring of Aquatic Environments.Sensors (Basel, Switzerland) · 2025Article
- Design and development of a cost-effective buoy using 3D printing for coastal monitoring.HardwareX · 2025Article
- Exploring opportunities of Artificial Intelligence in aquaculture to meet increasing food demand.Food chemistry: X · 2024Review
- An Integrated Smart Pond Water Quality Monitoring and Fish Farming Recommendation Aquabot System.Sensors (Basel, Switzerland) · 2024Article
- Integer Arithmetic Algorithm for Fundamental Frequency Identification of Oceanic Currents.Sensors (Basel, Switzerland) · 2023Article
- Novel Deep-Water Tidal Meter for Offshore Aquaculture Infrastructures.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The ocean resources have been rapidly depleted in the recent decade, and the complementary role of aquaculture to food security has become more critical than ever before. Water quality is one of the key factors in determining the success of aquaculture and real-time water quality monitoring is an important process for aquaculture. This paper proposes a low-cost and easy-to-build artificial intelligence (AI) buoy system that autonomously measures the related water quality data and instantly forwards them via wireless channels to the shore server. Furthermore, the data provide aquaculture staff with real-time water quality information and also assists server-side AI programs in implementing machine learning techniques to further provide short-term water quality predictions. In particular, we aim to provide a low-cost design by combining simple electronic devices and server-side AI programs for the proposed buoy system to measure water velocity. As a result, the cost for the practical implementation is approximately USD 2015 only to facilitate the proposed AI buoy system to measure the real-time data of dissolved oxygen, salinity, water temperature, and velocity. In addition, the AI buoy system also offers short-term estimations of water temperature and velocity, with mean square errors of 0.021 °C and 0.92 cm/s, respectively. Furthermore, we replaced the use of expensive current meters with a flow sensor tube of only USD 100 to measure water velocity.
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Registered trials
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.