期刊
AQUACULTURE INTERNATIONAL
卷 28, 期 1, 页码 41-57出版社
SPRINGER
DOI: 10.1007/s10499-019-00443-w
关键词
Wireless sensor network; IoT; Decision Support System; Computer vision
类别
资金
- sub-project Tecnologie digitali integrate per il rafforzamento sostenibile di produzioni e trasformazioni agroalimentari (AgroFiliere) (AgriDigit program) - Ministry of Agricultural, Food, Forestry and Tourism Policies (MiPAAFT) [DM 36503/7305/2018]
Aquaculture is presented as a sustainable alternative to the consumption of wild fish, for example, reducing inputs (such as feed), optimizing outputs, and reducing pollution. Extending to the agricultural framework, in this context, different technologies are being used to diminish those environmental hazards, giving rise to the precision agriculture/aquaculture being this a management concept based on observing, measuring, and responding space/temporal variability of productions. The scope of the precision aquaculture is to apply control-engineering principles to the production, to direct farmers to a better monitoring, control, and documentation of biological processes in fish farms. The aim of this review is to show an overview (enriched by a terms mapping analysis) of the precision aquaculture engineering innovations, with some examples of commercial systems, even if most of them are not specifically addressed in the precision aquaculture framework, in terms of: computer vision for animal monitoring, environmental monitoring tools, and sensor network (i.e., wireless sensor network, and long-range), robotics, and finally data interpretation and decision tools (i.e., algorithms, Internet of Things, and Decision Support Systems). Over the Internet of Things, cyber-physical systems communicate and cooperate with each other and with humans in real-time both internally and across organizational services offered and used by participants of the value chain. To increase the production and ameliorate the fish product quality and animal welfare issues, it is becoming even more important to monitor and control the production process.
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