{"title":"基于深度学习的智能喂养系统开发","authors":"Wu-Chih Hu, Hsin-Te Wu, Jun-We Zhan, Ping-Hsin Hsieh","doi":"10.1145/3440943.3444343","DOIUrl":null,"url":null,"abstract":"1The system can reduce the calculating workload of the IoT development board, as well as lowering the power consumption and guard the pool against water pollution. The intelligent feeding system offered by this study can effectively ease the workforce of the aquaculture industry. In the future, cage culture can also implement such a method to increase the safety of the operators. According to the experimental result of this study, the approach is feasible.","PeriodicalId":310247,"journal":{"name":"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Developing Intelligent Feeding Systems based on Deep Learning\",\"authors\":\"Wu-Chih Hu, Hsin-Te Wu, Jun-We Zhan, Ping-Hsin Hsieh\",\"doi\":\"10.1145/3440943.3444343\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"1The system can reduce the calculating workload of the IoT development board, as well as lowering the power consumption and guard the pool against water pollution. The intelligent feeding system offered by this study can effectively ease the workforce of the aquaculture industry. In the future, cage culture can also implement such a method to increase the safety of the operators. According to the experimental result of this study, the approach is feasible.\",\"PeriodicalId\":310247,\"journal\":{\"name\":\"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3440943.3444343\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3440943.3444343","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Developing Intelligent Feeding Systems based on Deep Learning
1The system can reduce the calculating workload of the IoT development board, as well as lowering the power consumption and guard the pool against water pollution. The intelligent feeding system offered by this study can effectively ease the workforce of the aquaculture industry. In the future, cage culture can also implement such a method to increase the safety of the operators. According to the experimental result of this study, the approach is feasible.
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