AI Unmanned Surface Vehicle Water Pollution Sensing Systems
BEIA CONSULT INTERNATIONAL
Reference Teacher: External expert TBC
Teacher(s): External expert TBC
This course will delve into the application of advanced ICT technologies within the context of green skills in aquaculture, with a particular focus on intelligent predictive maintenance solutions. Students will explore how the integration of IoT, AI, and blockchain technologies can be leveraged to monitor and optimize the operations of aquaculture farms, contributing to sustainable practices. The course will address both the theoretical foundations and practical implementation of innovative platforms, such as the iPREMAS system developed in the Martera Project (Intelligent PREdictive Maintenance for Aquaculture Systems), aligning with green skills to enhance environmental stewardship and resource efficiency.
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Students will gain an understanding of the main principles that form the basis of intelligent predictive maintenance systems in aquaculture settings. They will explore how advanced Information and Communication Technology (ICT) tools, including the Internet of Things (IoT), Artificial Intelligence (AI), and blockchain technology, are integrated for real-time monitoring.
Students will develop the ability to apply theoretical frameworks to practical scenarios by testing and validating the iPREMAS platform. They will work with machine learning techniques, such as Time Series Forecasting, Anomaly Detection, Fault Classification, and Remaining Useful Life estimation, to empirically evaluate and address potential system failures in aquaculture systems. This hands-on experience will allow them to implement analytical models, and gain a better understanding of predictive maintenance strategies and optimizing operational reliability in aquaculture environments.
Through case studies and practical exercises, students will learn to evaluate the effectiveness of different predictive maintenance strategies. They will make informed judgments on the potential impacts of these strategies on the operational efficiency, cost reduction, and environmental sustainability of aquaculture farms.
Students will enhance their ability to effectively communicate technical concepts related to intelligent predictive maintenance and smart infrastructure. They will practice reporting their findings, visualizing data, and providing clear and actionable alerts and notifications in the context of aquaculture systems.
Students will develop independent learning skills by being encouraged to explore emerging trends and technological innovations in aquaculture, allowing them to stay updated on the latest developments and continuously enhance their expertise in predictive maintenance and smart infrastructure solutions.
Basic knowledge in the field of informatics and telecommunication
This course will be a theoretical but also practical course and will combine lecture, laboratory and field activities.
The students are assessed based on their performance during the entire course.
The course will address the following content:
– Artificial Intelligence (AI)
– Providing data visualization functionalities
– Water quality monitoring
– Aquaculture monitoring systems
Related to clean water and sanitation (SDG 6), life below water (SDG 14), and innovation and infrastructure (SDG 9)
By expressing interest via official e-mail of Beia at: office@beia.ro
Course Modules: The educational material and syllabus include:
The students will gain basic knowledge of aquaculture systems, develop technical skills for monitoring and maintaining optimal environmental conditions and learn about sustainable management, with a focus on responsible ecological practices.
The students will acquire the ability to effectively manage and address main challenges in aquaculture maintenance, such as disease management, environmental impact mitigation, feed sustainability, and water quality control.
The students will gain foundational knowledge of intelligent predictive maintenance, understand the role of data analytics in maintenance processes, and be able to apply these concepts in the context of aquaculture to optimize operations and prevent failures. They will develop skills in applying advanced technologies, like IoT and AI, for predictive maintenance and real-time monitoring, ensuring the sustainability and productivity of aquaculture operations.
Students will gain essential skills in incorporating technology into aquaculture, including the use of IoT devices and sensors to improve farm management, optimize operations, and promote sustainability through advanced data analysis and real-time monitoring.
The students will gain basic knowledge in designing and implementing an intelligent predictive maintenance monitoring system.
Students will have access to online course support, training materials and data collecting infrastructure.