Water Quality Prediction in Aquaculture (WQPA) Using Machine Learning and Internet of Things
摘要
The growing popularity of Internet of Things (IoT) technologies has created new opportunities for aquaculture monitoring and management. An Internet of Things (IoT)-based water monitoring system uses sensors to gather data in real time on water quality factors that are important to aquatic life, such temperature, pH, dissolved oxygen, and ammonia content. The gathered data is sent to a central server for analysis and interpretation over a wireless network. The WQPA uses data analytics and cloud computing to give aqua culturists actionable information so they may make proactive decisions and make exact modifications to minimize water pollution caused by various human activities. This improves the general well-being and growth of aquatic life, which boosts aquaculture operations’ sustainability and production. A scalable and affordable answer to the ever-changing problems in aquaculture management, the Internet of Things-based WQPA encourages economical resource use and ecological preservation. WQPA strives to achieve Sustainable Development Goals 8 and 14, which safeguard aquatic life in order to boost fish producers’ economic prosperity.