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008			251103b ||||| |||| 00| 0 eng d
043			_aURS
245			_aArtificial Intelligence for Aquaculture System _b/ Flores, Aron Carl M.... [et al.].
260			_cMarch 2024
300			_a100 leaves : _c28 cm.
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
502			_aThesis _bBachelor of Science in Computer Engineering _cUniversity of Rizal System-Morong _d2024
520			_aThe study aimed to design an Artificial Intelligence for Aquaculture System and to assess its acceptability in terms of Functional Suitability, Performance Efficiency, Usability, Reliability, Safety, and Maintainability. The study was conducted at the University of Rizal System Cardona Campus during the School Year 2023 - 2024. The objective of the research was to develop an efficient monitoring system for the fish that was automated with the use of Artificial Intelligence which can ensure and protect the aquaculture and the aquatic life living in the ponds, rivers and etc. The researchers guarantee that with the use of AI, future generations would have more access to protect the aquatic life, without actually being there, which is by developing machines and systems that actually helps the planet, and not harm it. The researchers successfully identified important community issues by having a collaborative mindset through the process of brain-storming and thinking of techniques that could actually help the community. They eagerly sought advice from their research instructor, where they proposed their own findings with a sense of commitment to solve the issues they discovered by their study. In addition to examining the pH level of the water and the water temperature for the aquatic life, the researchers also measured the water level since water is limited to their area of study. After carefully making the goal and design methodology of their study, the researchers conducted a through search for articles both local and international and foreign to support their study. By means of their investigations, they sought to find significant literatures from a selection of sources to have a comprehensive and more knowledgeable information. With the different viewpoints from both local and international aquaculture, the researchers sought a deep analysis in global trends while recognizing the subtleties found in local sources. The required pond to test the actual device on was borrowed by the researchers from the University of Rizal System – Cardona, where the University has the pond/s needed to evaluate the device and the system itself. Building from their success in creating the device as soon as possible, the researchers managed to modify the frame of the device according to the pond so that it would be beneficial to the pond that it was stationed on. The developed device’s usability ranged from 4.7 to 4.77, according to the study, indicating a high degree of effortless use of the device. Additionally, a weighted mean of 4.74 was used to assess the device’s maintainability, indicating its exceptional stability and performance in regards of the ease of modifying and repairing of the device. A state-of-the-art Artificial Intelligence for Aquaculture System was thoroughly evaluated in terms of its functional suitability, reliability, usability, maintainability, and safety. The study offers important insights into the overall efficacy and efficiency of the system by analyzing its performance across a number of metrics, such as functionality, interoperability, and user experience. By monitoring the aquaculture and innovating with artificial intelligence, the findings advanced the knowledge of the researchers on how this technology can transform the monitoring of aquaculture. The study concluded that the system's usability and maintainability matched expectations. Furthermore, the content emphasizes how important it is to put into practice efficient and alternative monitoring techniques for aquaculture, like remote monitoring in order to sustainably make the aquaculture safe and monitored without endangering the natural resources.
700			_aFlores, Aron Carl M. _eauthor
700			_aBetito, Denis V. _eauthor
700			_aCebanico, Ian B. _eauthor
700			_aLigas, Paul Arthur A. _eauthor
700			_aAlfonso, Paul Arvy V. _edegree supervisor
856			_3Online Request for Student Unpublished Works _uhttps://forms.gle/7LqvGGkaDrUQqz429
856			_uhttps://drive.google.com/file/d/130at1qm2Y8RSFElr9RmIDZPUJnZ5WqSa/view?usp=drive_link
942			_2lcc _cT
999			_c88567 _d88564