Research On Intelligent Monitoring And Object Recognition Of Marine Ranching

The area of ocean accounts for 71% of the total surface area of the earth.It contains abundant biological resources so it is called "Blue Granary".But in recent years,due to problems such as overfishing and unreasonable aquaculture planning,environmental destruction and the depletion of marine living resources have been caused.Using scientific methods to achieve marine resources restoration and realize the increase of fish volume is an important significance of marine ranching.This paper researches the environmental monitoring and intelligent fishing detection in the construction of marine grazing land and proposes a set of marine pasture breeding system based on Internet of Things.Environmental monitoring is mainly about conducting long-term multi-point monitoring of the quality of marine ranching.Perceptual layer select dissolved oxygen,salinity,temperature,and p H values for data acquisition.Network layer adopts Zigbee ad hoc network.Topology of WiFi access to the Internet outside the system.Application layer design a host computer software as the data display and storage center for simple data analysis.At present,the fishing of the marine ranching is still done by human.It is not only dangerous,but also unsuitable for the fishermen to go fishing in the lower water temperature in the winter.Intelligent fishing is divided into the study of simplified control and object recognition of robotic arm.The robotic arm acts as the main actuator of the sensing layer and is used for underwater detection and underwater biological fishing.It also incorporates a binocular camera for observation of the submarine environment and automatic fishing.The innovation of this article is the simplification of the control algorithm of the robotic arm.The traditional control algorithm is more complex,and it takes a long time to control the robot arm to move to a specified position.According to actual condition,adding appropriate constraints to the robotic arm,an inverse kinematics algorithm based on end-position coordinates for rapid control is proposed.Due to the complexity of the undersea environment and dim lighting,it is suitable to apply computer vision and deep learning these intelligent methods to object recognition in marine grazing.Through practical application,it can be seen that the system can perform real-time multi-point monitoring of marine ranches.And in-position accuracy and arrival time of the inverse algorithm of the robot arm satisfy the crawling requirement.Object recognition can distinguish between strawberry and orange,its Short recognition time,high precision,ranging accuracy features can be applied to the robot arm's automatic grab.Adoption of the data set published in the first underwater robot picking contest in 2017.The trained model can well identify marine organisms such as sea cucumbers,sea urchins and scallops in marine grazing lands.