Developing Intelligent Feeding Systems based on Deep Learning

Autor:	Ping-Hsin Hsieh, Hsin-Te Wu, Wu-Chih Hu, Jun-We Zhan
Rok vydání:	2020
Předmět:	Guard (information security) Computer science business.industry Deep learning ComputerApplications_COMPUTERSINOTHERSYSTEMS Workload Cage culture Convolutional neural network Risk analysis (engineering) Power consumption Workforce Artificial intelligence Aquaculture industry business
Zdroj:	ICEA
DOI:	10.1145/3440943.3444343
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::147f22ec76c73ff3c260d6c1915adb97 https://doi.org/10.1145/3440943.3444343 Zobrazit plný text záznamu