Model for Detecting Illegal Tree Felling in the Protected Area of Bagua in Amazonas Using Convolutional Neural Networks

Calle Carbajal W.; Raúl Huamán Llantoy J.; Dextre Alarcon J. · International Conference on Web Information Systems and Technologies, WEBIST - Proceedings (2024) · DOI: 10.5220/0012948400003825

Resumen

Illegal logging is a problem that occurs in different regions of Peru, causing deforestation, biodiversity loss, and contributing to climate change.Despite the efforts of organizations and governments to combat this problem, constant detection and monitoring are challenging due to the vast extension of forests and the lack of human resources to effectively monitor all areas.Therefore, the use of a detection model is proposed as a solution to detect illegal logging in real time through chainsaw sound. This model consists of four phases: Input, Analysis, Execution, and Output.Phase 1 focuses on the collection of sounds from recording devices. Phase 2 analyzes and processes the characteristic chainsaw sounds. Phase 3 focuses on the execution of the model. Phase 4 will display the result of the detection as a numerical value 1 or 0 as the case may be.The results of the experimental validation were obtained by using mobile devices to record and send audio to the detection model. These results were positive and acceptable in terms of accuracy in detecting illegal logging activities, achieving a 10% reduction in such activities. Copyright

Instituciones: Universidad Peruana de Ciencias Aplicadas