Convolutional Neural Networks for Real Time Classification of Beehive Acoustic Patterns on Constrained Devices
Antonio Robles-Guerrero,
Salvador Gómez-Jiménez,
Tonatiuh Saucedo-Anaya
et al.
Abstract:Recent research has demonstrated the effectiveness of convolutional neural networks (CNN) in assessing the health status of bee colonies by classifying acoustic patterns. However, developing a monitoring system using CNNs compared to conventional machine learning models can result in higher computation costs, greater energy demand, and longer inference times. This study examines the potential of CNN architectures in developing a monitoring system based on constrained hardware. The experimentation involved test… Show more
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