Modern Techniques for The Identification and Monitoring of Insect Populations

https://doi.org/10.5281/zenodo.20579752

Abstract

Insect identification is a crucial process and requires Specialisation. The use of technology, namely AI, Machine Learning, and drones, has been constantly increasing in entomological research. AI technologies, especially deep learning, computer vision, and neural networks, are being constantly used across various subsections of entomological research, such as insect identification, monitoring, detection, and classification, pest management, vector-borne disease control, and medical and forensic entomology. Use of drones (UAVs) and image-based monitoring systems improves the pollination studies, hence may be beneficial in agriculture. Adult and Life stages of Insects forms identification, Post Mortem Internal estimation, and Crime investigation can also be enhanced by using the latest AI technology. Thus, this paper reviews the use of modern technology, AI-driven approaches, and deep learning models in various entomological Applications.

Keywords: Artificial Intelligence, Machine Learning, Insect Identification, Pest Management, Deep Learning Models.