Enhanced Frequency Domain Analysis for Detecting Wild Elephants in Asia using Acoustics
- Publisher:
- IEEE
- Publication Type:
- Conference Proceeding
- Citation:
- 2023 IEEE 17th International Conference on Industrial and Information Systems (ICIIS), 2023, 00, pp. 140-145
- Issue Date:
- 2023-09-20
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| Enhanced_Frequency_Domain_Analysis_for_Detecting_Wild_Elephants_in_Asia_using_Acoustics.pdf | Published version | 2.28 MB |
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Human elephant conflict in Asia and Africa calls for an early warning system to reduce risks and harm for both elephants and humans Acoustic based warning systems offer a promising solution due to their non invasive and cost effective nature In this paper we propose a novel approach for detecting wild elephants using acoustic signals targeting the Asian elephant population in Sri Lanka The proposed method introduces a unique data preprocessing technique followed by feature extraction using a deep convolutional neural network followed by fully connected layers for classification Spectro grams are used as input data and transfer learning is employed with YAMNet model layers Additionally we have developed a hardware system capable of capturing infra sound signals although a detailed description of the system is beyond the scope of this paper as it is crucial for detecting elephant activity The proposed method is evaluated on a large data set recorded under natural field conditions in Sri Lanka and it demonstrates 97 77 accuracy in detecting elephants and robustness to noise sources Proposed approach has the potential to develop into a non invasive early warning system for elephant detection in the wild contributing to the mitigation of human elephant conflict and wildlife preservation
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