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Technical Name 眼見為憑:應用於蝦子養殖之人工智慧水下監控養殖系統
Project Operator National Sun Yat-Sen University
Project Host 黃英哲
Summary
The Artificial Intelligence Underwater MonitoringManagement system is a system that integrates aquacultureinformation technology, which can collect image data of shrimp 24/7 by using IoT devices, then next enhance the images that collected under different light, water qualityturbidity. The system will recordanalyze the number, size, healtheating status of white shrimp, checking the amount of leftovers feed on the feeding tray, then manage the feeding strategycontrol water quality based on the above analysis.
Technical Film
Scientific Breakthrough
1. AI white shrimp identification system increases the observation quantity by 60~100 times compare to traditional method.
2. AI accurately feeding system can help farmer to grasp the eating status of shrimp more accurately.
3. Growth rate of shrimp is easily accessible for farmers with AI shrimp length measurement system.
4. AI intestine recognition system analyze the health of shrimps, can be used as the reference of daily feeding rate.
5. Automatic management system makes it possible to manage a farm through a mobile phone
Industrial Applicability
The system uses AI to greatly increase the number of shrimp observations by 60 to 100 time, provides accurate AI analyzed data to farmers for decision-making, altogether the system can help boosting productivity, mitigating risks, reducing costs,reforming the gradually aged industrial structure. We have submitted more than 6 patents. With appropriate authorization, these patents are suitable for commercial usage in aquaculturein fisheryelectricity symbiosis as a total solution. We believe this system will evolve to be a bright spot in Taiwan aquaculture in the near future.
Matching Needs
1.欲媒合之產業領域:資訊與通訊、機械與系統、綠能與環境。2.欲媒合項目:技術合作、技術轉移、技術協助、生產製造、供應商尋找、投資合作。
Keyword AI in aquaculture Shrimp farm monitoring system AI shrimp Precision feeding Water quality monitoring Aquaculture risk management Growth of white shrimp Health detection Underwater video AI recognition
Notes
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