Abstract
Much research and numerous attempts have been made to apply the new emerging technology to agricultural areas. The main objective of this research is to protect the crop from animal attacks. The conventional techniques have the conventional same security applied to all the types of animals detected based on a Passive IR sensor, and only single-stage protection is applied. The images were captured and identified with the help of support vector machine and convolution neural network techniques, and with the help of IoT devices, the information was sent to the farm owner if the primary protection fails. Cameras were fixed to capture the image for processing to identify the animals; based on the animal identification, different levels of security were applied. Based on the animal level of the reciprocating sound dB level will change. The accuracy of the proposed method can be estimated by comparing the conventional technique based on the complexity of the technique, implementation cost, reciprocating time, and accuracy of animal detection.
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Amarendra, C., Rama Reddy, T. (2023). Solar Energy-Based Intelligent Animal Reciprocating Device for Crop Protection Using Deep Learning Techniques. In: Chaki, N., Devarakonda, N., Cortesi, A. (eds) Proceedings of International Conference on Computational Intelligence and Data Engineering. ICCIDE 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 163. Springer, Singapore. https://doi.org/10.1007/978-981-99-0609-3_7
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