AIMC Topic: Aquaculture

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A Two-Mode Underwater Smart Sensor Object for Precision Aquaculture Based on AIoT Technology.

Sensors (Basel, Switzerland)
Monitoring the status of culture fish is an essential task for precision aquaculture using a smart underwater imaging device as a non-intrusive way of sensing to monitor freely swimming fish even in turbid or low-ambient-light waters. This paper deve...

A System for Autonomous Seaweed Farm Inspection with an Underwater Robot.

Sensors (Basel, Switzerland)
This paper outlines challenges and opportunities in operating underwater robots (so-called AUVs) on a seaweed farm. The need is driven by an emerging aquaculture industry on the Swedish west coast where large-scale seaweed farms are being developed. ...

A Low-Cost AI Buoy System for Monitoring Water Quality at Offshore Aquaculture Cages.

Sensors (Basel, Switzerland)
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 aquacultu...

LSTM-TCN: dissolved oxygen prediction in aquaculture, based on combined model of long short-term memory network and temporal convolutional network.

Environmental science and pollution research international
Dissolved oxygen (DO) is an important water quality monitoring parameter of great significance in aquaculture. Accurate prediction of dissolved oxygen can help farmers to take necessary measures in advance to ensure the healthy growth of cultured spe...

Reproductive characteristics of the giant gurami sago strain ( Lacepède, 1801): basic knowledge for a future hatchery development strategy.

F1000Research
The giant gourami sago strain ( Lacepède) has been approved in 2018 as a candidate for freshwater aquaculture in Indonesia. However, information on the species' reproduction is minimal. This study analyzed the reproductive characteristics of the go...

Vision-based egg quality prediction in Pacific bluefin tuna (Thunnus orientalis) by deep neural network.

Scientific reports
Closed-cycle aquaculture using hatchery produced seed stocks is vital to the sustainability of endangered species such as Pacific bluefin tuna (Thunnus orientalis) because this aquaculture system does not depend on aquaculture seeds collected from th...

Analysis of Behavior Trajectory Based on Deep Learning in Ammonia Environment for Fish.

Sensors (Basel, Switzerland)
Ammonia can be produced by the respiration and excretion of fish during the farming process, which can affect the life of fish. In this paper, to research the behavior of fish under different ammonia concentration and make the corresponding judgment ...

Inhibition to crucial enzymes in the lethal effects of the dinoflagellate Karenia mikimotoi on the rotifer Brachionus plicatilis.

Marine environmental research
Blooms of the dinoflagellate Karenia mikimotoi have cause great financial losses to the marine aquaculture industry. However, the toxicity mechanism of this species is still not fully known. In this study, we evaluated the short-term effects of K. mi...

Predicting fish kills and toxic blooms in an intensive mariculture site in the Philippines using a machine learning model.

The Science of the total environment
Harmful algal blooms (HABs) that produce toxins and those that lead to fish kills are global problems that appear to be increasing in frequency and expanding in area. One way to help mitigate their impacts on people's health and livelihoods is to dev...