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

Lu, Hoang-Yang; Cheng, Chih‐Yung; Cheng, Shyi-Chyi; Cheng, Yu‐Hao; Lo, Wen‐Chen; Jiang, Weilin; Nan, Fan-Hua; Chang, Shun-Hsyung; Ubina, Naomi A.

doi:10.3390/s22114078

Cited by 26 publications

(21 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To ensure accurate data collection, the devices in the ponds were securely attached to floating devices [6] placed or anchored in the vicinity of the death zone. This strategic placement allowed us to capture crucial minimum values of each parameter, which is of utmost importance from the technical decisionmaking perspective.…”

Section: Tools and Materialsmentioning

confidence: 99%

Towards a Customizable and Cost-Effective Monitoring System for Vannamei Shrimp Cultivation

Aynuddin,

Triyatmo,

Rakhmanda

2023

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

The advancement of technology has revolutionized the operational practices in vannamei shrimp (L. vannamei) cultivation, shifting towards a science-based and data-driven approach. The success of shrimp cultivation heavily relies on making informed technical decisions throughout the process. To facilitate optimal decision-making, an integrated monitoring system encompassing feed-growth data, water quality data, and material inputs is imperative. This research aims to design a customizable system that optimizes available resources and offers easily modifiable and adaptable program scripts for users. The development process involved constructing a prototype device, script development, and system implementation testing. The prototype incorporated three sensors (temperature, pH, and dissolved oxygen) and utilized floats for flexible customization based on specific needs and available sensors or materials. Data analysis and visualization were achieved through various free options. Remarkably, the system only required 2-3 concise scripts to operate effectively. The experimental results demonstrated the system’s potential for broader application and future development. The proposed monitoring system provides a cost-effective solution, offering flexibility, reliability, and valuable data-driven insights to enhance decision-making in vannamei shrimp cultivation.

show abstract

Section: Tools and Materialsmentioning

confidence: 99%

Towards a Customizable and Cost-Effective Monitoring System for Vannamei Shrimp Cultivation

Aynuddin,

Triyatmo,

Rakhmanda

2023

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…57 An AI-integrated water-quality monitoring buoy was developed by Lu et al, which cost about $2015, including all the sensors and other hardware. 58 These sensors have some challenges to operate due to their presence in submerged conditions for extended periods and can become clogged, therefore needing to be cleaned more frequently. Furthermore, wireless sensors face constraints related to their finite battery life, and those employed in marine aquaculture are susceptible to corrosion.…”

Section: Sensorsmentioning

confidence: 99%

Emerging technologies revolutionising disease diagnosis and monitoring in aquatic animal health

Bohara,

Joshi,

Acharya

et al. 2023

Reviews in Aquaculture

View full text Add to dashboard Cite

In recent years, aquaculture has seen tremendous growth worldwide due to technological advancements, leading to research and development of various innovations. Aquaculture farmers prioritise early diagnosis for timely treatment to achieve better productive and economic performance. Aquatic animal health experts still employ traditional diagnostic methods using visual diagnosis, cell culture, media culture, histopathology and serology. However, the developments of technologies in aquamedicine, such as sequencing, biosensors and CRISPR, have enabled rapid disease detection within minutes. Furthermore, integrating sensors, drones, artificial intelligence and the internet in aquaculture farm monitoring has helped farmers take decisive actions to improve production. Advancements in diagnostic techniques have significantly enhanced the efficient detection of bacterial, viral, parasitic and fungal diseases in aquatic animals. Moreover, monitoring water quality, aquatic animal health and animal behaviour on farms has become exceptionally streamlined with cutting‐edge tools like drones, sensors and artificial intelligence. Summarising research and development in aquatic animal health and monitoring aids efficient technology adoption in aquaculture. With these advanced technologies' continued development and adoption in developed countries, the aquaculture industry is experiencing growth and increased efficiency, benefiting farmers and consumers in these regions. However, farmers and educators in developing countries lack information about these technologies. Training of agricultural educators and efficient dissemination of knowledge and technologies through advertising and publication in collaboration with companies is essential. This review delves into emerging technologies capable of replacing the conventional diagnostic and monitoring methods utilised in aquaculture. We also explore their strengths, limitations and potential future applications within aquaculture settings.

show abstract

“…Data-driven approaches augment on-farm decision-making capabilities, improve fish production, and reduce losses, benefiting farmers. The IoT and wireless technologies enable real-time data transmission and monitoring in digital farming [35,36]. The cloud-based IoT systems facilitate communication between software platforms, sensors, farmers, and aquaculture machinery in digital farming.…”

Section: Literature Reviewsmentioning

confidence: 99%

Digital Twin Architecture Evaluation for Intelligent Fish Farm Management Using Modified Analytic Hierarchy Process

et al. 2022

Self Cite

View full text Add to dashboard Cite

Precision aquaculture deploys multi-mode sensors on a fish farm to collect fish and environmental data and form a big collection of datasets to pre-train data-driven prediction models to fully understand the aquaculture environment and fish farm conditions. These prediction models empower fish farmers for intelligent decisions, thereby providing objective information to monitor and control factors of automatic aquaculture machines and maximize farm production. This paper analyzes the requirements of a digital transformation infrastructure consisting of five-layered digital twins using extensive literature reviews. Thus, the results help realize our goal of providing efficient management and remote monitoring of aquaculture farms. The system embeds cloud-based digital twins using machine learning and computer vision, together with sensors and artificial intelligence-based Internet of Things (AIoT) technologies, to monitor fish feeding behavior, disease, and growth. However, few discussions in the literature concerning the functionality of a cost-effective digital twin architecture for aquaculture transformation are available. Therefore, this study uses the modified analytical hierarchical analysis to define the user requirements and the strategies for deploying digital twins to achieve the goal of intelligent fish farm management. Based on the requirement analysis, the constructed prototype of the cloud-based digital twin system effectively improves the efficiency of traditional fish farm management.

show abstract

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

Cited by 26 publications

References 33 publications

Towards a Customizable and Cost-Effective Monitoring System for Vannamei Shrimp Cultivation

Towards a Customizable and Cost-Effective Monitoring System for Vannamei Shrimp Cultivation

Emerging technologies revolutionising disease diagnosis and monitoring in aquatic animal health

Digital Twin Architecture Evaluation for Intelligent Fish Farm Management Using Modified Analytic Hierarchy Process

Contact Info

Product

Resources

About