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271 results about "Crop pest" patented technology

The most varied and numerous species of crop pests are arthropods: insects, arachnids (mites), and some species of millipedes and crustaceans (wood lice). The most injurious pests are insects, chiefly because of their biological characteristics, abundance of species, high fecundity, and rapid reproduction.

System for intelligently monitoring and controlling crop pests and diseases

The invention relates to a system for intelligently monitoring and controlling crop pests and diseases. The system is characterized by comprising a monitoring computer and a pesticide spraying device which is arranged in a crop growing place, wherein the monitoring computer drives the pesticide spraying device which is connected with the monitoring computer; a time controller and a pesticide spraying selective driving module are arranged in the monitoring computer; and the time controller controls and starts a corresponding spray head of the pesticide spraying device through the pesticide spraying selective driving module. The system has the following advantages that: 1, intelligentization is realized, the degree of automation is high, the control modes are diversified, the control is performed in time, and the using effect is good; 2, the solar energy is used as a power supply of monitoring equipment, so that the energy-saving effect is good; 3, the monitoring equipment not only can automatically control the water supply or the pesticide spraying of cultivated crops, but also has a multi-aspect management and control ability of controlling pests and diseases of the crops in different areas of the same place; and 4, the health condition of the crops is monitored in real time by using a monitoring probe, so that the crop pests and diseases are pre-warned in time and are controlled appropriately. Therefore, the system is not only favorable for ensuring the growth of the crops and the production bumper harvest of agriculture, forestry and tea industry, but also can greatly reduce medicament waste and pesticide pollution.
Owner:FUJIAN HONGBAOSHAN BIOLOGICAL SCI & TECH

Crop pest identification method and system based on Android platform

The invention relates to a crop pest identification method based on an Android platform. The method comprises the steps of starting application software of a mobile phone with the Android platform, enabling the mobile phone to be connected with a wireless network, selecting the type of a crop, collecting a pest image, transmitting the pest image to an application program server, cutting the pest image with the application program server, and judging whether the expected threshold value is reached or not; if yes, conducting preprocessing, feature extraction and multi-feature fusion on the pest image in sequence; if not, cutting the pest image again; identifying features of the pest image, and transmitting the identified result and the corresponding pest control method to the mobile phone with the Android platform. The invention further discloses a crop pest identification system based on the Android platform. According to the crop pest identification method and system based on the Android platform, a user can intelligently diagnose crop pests anytime and anywhere, the limitation of simply relying on an agricultural specialist is avoided, the Android mobile phone platform is utilized, a traditional crop pest diagnosis mode is completely changed, farmland management efficiency is improved, and convenience is brought to the user.
Owner:HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI +1

Intelligent prevention and control system based on internet of things for crop pests and diseases

The invention belongs to the technical field of intelligent control systems for crop pests and diseases, and particularly relates to an intelligent prevention and control system based on an internet of things for the crop pests and diseases. The system comprises a collection system, the collection system collects crop information, the information is transmitted to a control center through internetof things monitoring nodes and a gateway dielectric for forwarding, and the control center sends a control instruction corresponding to data to execution equipment and detection equipment through a transmission module. Compared with the prior art, the system has the advantages that the preliminary monitoring complexity is simplified, the accuracy of detecting the crop pests and diseases is improved at the same time, the crop pests and diseases can be timely found before the occurrence of the crop pests and diseases or in the early period of the occurrence of the crop pests and diseases, and corresponding measures are taken; the problems are effectively solved that according to existing monitoring systems, collected data cannot be effectively processed, and the network robustness is poor;the incidence of the crop diseases and pests can be greatly reduced, the yield of crops is increased, the quality of the crops is improved, the situation is reduced that a large quantity of pesticidesare needed due to serious pests and disease disasters, the large-scale popularization is facilitated, and the agricultural production level can be increased.
Owner:来安县威光绿园生态农业专业合作社

Improved hybrid attention module-based crop pest and disease damage fine-grained identification method

ActiveCN111985370AReduce the mapping intervalPreserve the details of the original imageScene recognitionNeural architecturesCrop pestAlgorithm
The invention discloses an improved hybrid attention module-based crop pest and disease damage fine-grained identification method. The method comprises the following steps of: firstly, inputting a crop disease and insect pest picture, performing feature extraction through a convolution layer after preprocessing, and taking a feature map F obtained by the convolution layer as input of attention I _CBAM by using an Inception thought in combination with a residual connection structure in a forward propagation process to obtain weights MC (F) and MS (F); and finally, obtaining a feature map F2, and generating a final prediction probability by using a softmax function. In order to improve the accuracy of a disease and pest identification model and detect diseases and pests in time, the hybridattention CBAM is improved; through a parallel connection structure of channel attention and space attention, the problem of interference generated by serial connection of channel attention and spaceattention is solved, and the direct generalization of I _ CBAM in different models is ensured while the improvement of the accuracy of a pest and disease damage fine-grained identification model afterattention adding is more stable.
Owner:SOUTH CHINA AGRI UNIV
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