High-Level Project Summary
Our new technology can be applied into the forecast and warning system by improving two aspects: one is the way it collect the information of the associated weather condition, and the other is its data analysis module. Our system can be improved. By using ArcGIS 9.340 and/or free software QGIS 2.16, 39, you can easily search for attribute information and spatial distribution. With the accumulation of the IPOAW, the relevant analysis will be more robust, which can help improve the quality of pest prediction. In addition, remote sensing retrieval technology provides more fine-scale weather information for plant and pest dynamic research
Link to Project "Demo"
Link to Final Project
Detailed Project Description
we use a CNN model in machine learning to recognize insect and use meteorologicalinformation in forest insect pest forecast and warning systems.
Space Agency Data
movebank
Hackathon Journey
we learning many new knowledge in the prcess of construct the two model we made, becase the 4 members of our team are all fond of animal and we quickly have idea when we see this challenge,we collect data, refer to paper and solve the challenge. i want to thank to out teacher and members.
References
1.Jiang-Lin Qin,New technology for using meteorologicalinformation in forest insect pest forecast and warning systems,2017.
2.A P Naufa,Insects identification with convolutional neural network ,technique in the sweet corn field,2020.
3.Dušan Markovi´c,Prediction of Pest Insect Appearance Using Sensors and Machine Learning,2021.
4.zhangxiaorong and gang chen,An Automatic Insect Recognition Algorithm in Complex Background Based on Convolution Neural Network,2020
Tags
#machine learning#insect recognition #insect predict#CNN
Global Judging
This project has been submitted for consideration during the Judging process.