| Author Name | Affiliation | | Sireesha Abotula | Department of Computer Science and Engineering, GITAM Deemed to be University,Visakhapatnam 530045, India
Department of Information Technology, Andhra University, Visakhapatnam 530003, India | | Srinivas Gorla | Department of Computer Science and Engineering, GITAM Deemed to be University,Visakhapatnam 530045, India | | Prasad Reddy PVGD | Department of Computer Science and Systems Engineering，Andhra University, Visakhapatnam 530003, India | | Mohankrishna S | Department of Computer Science and Engineering, GITAM Deemed to be University,Visakhapatnam 530045, India |
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| Abstract: |
| Birds are a huge hazard to agriculture all around the world, causing harm to profitable field crops. Growers use a variety of techniques to keep them away, including visual, auditory, tactile, and olfactory deterrents. This study presents a comprehensive overview of current bird repellant approaches used in agricultural contexts, as well as potential new ways. The bird repellent techniques include Internet of Things technology, Deep Learning, Convolutional Neural Network, Unmanned Aerial Vehicles, Wireless Sensor Networks and Laser biotechnology. This study's goal is to find and review about previous approach towards repellent of birds in the crop fields using various technologies. |
| Key words: Bird repellent, crop protection, IoT, UAV, Deep Learning |
| DOI：10.11916/j.issn.1005-9113.2023011 |
| Clc Number:TP39, X171 |
| Fund: |
