Abstract:
Shrimp farming plays a crucial role in the global aquaculture industry. Shrimp aquaculture, involves the cultivation of shrimps in artificial ponds, tanks or other controlled environments. Shrimp farming is a significant source of income and employment for many countries, particularly in Southeast Asia. Shrimp farmers faces various diseases along with other challenges that can significantly impact the production and profitability of shrimp farming. The most devastating shrimp diseases results in production loss for the farmers, distributors and consumers. Frequent monitoring of shrimp health allows for early detection of any potential disease outbreaks, enabling prompt actions to mitigate risks. The existing researches on shrimp diseases, disease management and artificial intelligence-based disease classification are proposed in the literature review. We are proposing an artificial intelligence-based disease detection system for shrimps with the help of image processing, This will help with the monitoring and early detection of shrimp diseases. We approached and utilized some machine learning models to train and test on our dataset, then evaluated the results to progress towards our target of building a complete system or platform to successfully detect diseases at an early stage for the farmers.
