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Wildlife has been endangered due to illegal activities. This requires more effective surveillance measures. Felling timber and poaching are regular illegal activities but challenging to detect. Hence authorities should resort to modern technologies such as employing autonoumous surveillance to stop them. The Malaysian forest audio data were recorded to lay a foundation in initiating a cheaper and practical approach. Hence this paper reports the collection, processing and analysis of audio data in preparation to develop an autonomous sound event detection system. The recording was an emulation of possible illegal activities in a reserved forest. Sounds of chainsaw and hand hatchet cutting tree trunks were taken. It was found that there was a distinct pattern in the Mel-log energies audio feature of the sound, which could be used to identify illegal activities. Thus, it is believed that a detection through audio is a possible approach to be employed as one of the methods to stop illegal activities in the tropical reserve forests like those in Malaysia.
Acoustic features, Sound event detection, Wildlife protection, Audio processing, Anti-poaching
Acoustic features, Sound event detection, Wildlife protection, Audio processing, Anti-poaching
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