학술논문

UAV Based System For Detection in Integrated Insect Management for Agriculture Using Deep Learning
Document Type
Conference
Source
2023 2nd International Conference on Futuristic Technologies (INCOFT) Futuristic Technologies (INCOFT), 2023 2nd International Conference on. :1-6 Nov, 2023
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Deep learning
Insects
Crops
Autonomous aerial vehicles
Agriculture
Water resources
Stress
Unmanned Aerial Vehicle(UAV)
Detection and classification
YOLOv3/YOLOv5 (You Only Look Once)
Convolutional Neural Network (CNN)
Language
Abstract
This abstract describes about a system that uses Unmanned Aerial Vehicles (UAV) with high resolution cameras and deep learning algorithms to detect insects in agriculture. This device would make it possible to quickly and precisely detect insects in crops and determine their species and infestation degree . The same technology can also identify other problems affecting crops, like fertilizer shortages or water stress. The deep learning program can find patterns and signs of these problems by examining the images acquired by the UAV, enabling farmers to take appropriate action before serious damage happens. This method has the potential to greatly reduce the time and resources needed for manual crop scouting and monitoring, as well as enhance insect detection precision and lower the use of insecticides. An important factor of using deep learning is not only it detects insects but also classify them into useful and harmful category.