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Intelligent feeding system based on deep learning

A deep learning and intelligent technology, applied in the general control system, neural learning method, control/regulation system, etc., can solve the problems of high cost, high cost, and low feeding efficiency of manual feeding, and achieve low input cost and judgment The results are precise

Active Publication Date: 2018-08-28
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although artificial feeding can control the remaining amount of residual bait to a certain extent, there are problems such as high cost, low feeding efficiency, and poor stability.
Although traditional feeding machine feeding can solve the problems of high cost, low feeding efficiency and poor stability of manual feeding to a certain extent, it is difficult to control the residual bait and insufficient feeding. question
To sum up, pond recirculating aquaculture is a new, environment-friendly and high-yield farming model, and the problem of feed feeding has largely limited the further promotion of this farming model.

Method used

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  • Intelligent feeding system based on deep learning
  • Intelligent feeding system based on deep learning

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Embodiment Construction

[0039] The specific implementation manner of the present invention will be described in detail below in conjunction with the examples and accompanying drawings.

[0040] A schematic diagram of the structure of the system of the present invention is as attached figure 1 As shown, it mainly consists of four parts: mechanical feeding part, breeding tank data collection part, deep learning server, and feeding control part. Among them, the mechanical feeding part is the specific implementation device, the breeding tank data collection part is to provide data sources for deep learning services, and the deep learning server analyzes the obtained data to make feeding judgments, and sends corresponding feedback to the feeding control unit. Instructions, the feeding control unit controls the mechanical parts to collectively implement actions by receiving instructions. The whole system is a closed-loop intelligent control system.

[0041] The mechanical feeding part mainly consists of si...

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Abstract

The invention discloses an intelligent feeding system based on deep learning. The system mainly comprises a mechanical feeding part, a breeding tank datum collection part, a deep learning server and afeeding control part; and the breeding tank datum collection part collects water body temperature, environment temperature, and pollution collection data of a breeding tank and fish shoal behavior data and transmits the collected data into the deep learning server, the deep learning server performs analysis integration and training learning, determines whether to feed or not at present, a feedingamount and feeding duration, and sends a corresponding instruction to the feeding control part, and the feeding control part controls action of a relevant mechanical feeding part according to the instruction. The system disclosed by the invention has strong pertinence, can continuously perform self learning and self improvement, and can make a judgment result more accurate and more reasonable; and a final realization function of the system is equivalent to cultivation of a worker with rich feeding experience, and the system has judgement ability of people, is more stable than artificial workand has lower input costs.

Description

technical field [0001] The present invention relates to an intelligent feeding system for circulating aquaculture in ponds, and in particular to an intelligent feeding system based on deep learning. The deep learning server analyzes these feedback data in real time, and the server can learn and improve itself, simulate artificial feeding behavior, make the analysis result closer to the actual situation of fish feeding, and transmit the analysis result to the feeding system The control unit makes corresponding feeding adjustments according to the real-time analysis results. Combining the advantages of artificial feeding and feeding with traditional feeding equipment, it makes feeding more scientific. Background technique [0002] With the improvement of people's material living standards in our country, green, pollution-free healthy food has become the first choice of people, and aquatic products are rich in nutrients, and are more and more favored by consumers. Aquaculture...

Claims

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Application Information

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IPC IPC(8): A01K61/80G06N3/08G05B13/02
CPCA01K61/80G05B13/027G06N3/08Y02A40/81
Inventor 叶章颖朋泽群赵建张丰登朱松明
Owner ZHEJIANG UNIV
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