Predictive and Proactive Aquarium Management Using Machine Learning: An Extension of the Smart AroTank
摘要
Keeping fish as pets has become increasingly popular, yet it presents several challenges in maintaining an optimal environment. Issues such as fluctuating water quality, proper feeding, and managing temperature and lighting can be demanding for aquarium owners. To address these challenges, a proposed solution is to implement a real-time monitoring system equipped with sensors. This system continuously tracks parameters like temperature and water pH levels, providing real-time updates and eliminating the need for manual checks. The system also features an aeration component to ensure adequate oxygen levels and supports water renewal operations to sustain water quality. Enhanced by IoT technology, the system allows users to monitor and control their aquarium remotely via a mobile application. This intelligent aquarium management system prioritizes the well-being of the fish by offering precise control over feeding schedules, thereby preventing health issues related to improper feeding. It also minimizes the manual effort required for aquarium maintenance, allowing owners to spend more time enjoying their pets. Overall, the AroTank 2.0 system effectively meets its functional requirements and enjoys high user acceptance. It successfully addresses user needs by providing valuable information, a well-designed interface, and a high level of user satisfaction.