This research addresses the challenges in aquaculture, specifically in the cultivation of Tilapia in brackish water. The study focuses on enhancing the efficiency and accuracy of sorting and counting fish fry, a factor that significantly influences the profitability of cultivators. An automated sorting and counting system is proposed, capable of categorizing Tilapia fry based on their quantity, size, and gender. This system employs sensors and a microcontroller, such as Arduino, to process the gathered information and control the sorting mechanism. The sorted and counted fry are subsequently separated into different compartments for easy collection and further cultivation. The data collected by the system can be displayed on an LCD screen or stored for future analysis and planning. This research represents a significant advancement in aquaculture technology, potentially leading to increased profitability and sustainability in Tilapia farming. Further research and development are required to refine the system and ensure its effectiveness and reliability under various cultivation conditions.
                        
                        
                        
                        
                            
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