Machine Learning-Driven Thermal Imaging Frame Work for Early Detection of Red Palm Weevil Infestation

The red palm weevil (RPW) is a destructive insect that causes severe damage to palm plants, necessitating early discovery and effective eradication. Thermal imaging, with its capacity to catch small temperature differences, provides a noninvasive way to detect infestations in their early stages. This paper provides a machine learning-driven preprocessing system to improve the interpretation of thermal images for RPW identification. The framework contains thermal- specific image processing and feature extraction algorithms. Advanced methods, such as Convolutional Neural Networks (CNN), Support Vector Machine (SVM) and Recurrent Neural Network (RNN) are used to detect patterns related with RPW.