Utilizing GPT-4 for Morphological Identification of Bed Bugs

Abstract

Artificial Intelligence (AI) is transforming technology. GhatGPT-4 is a cutting-edge language model that enhances human-computer interaction and understanding. This study addresses the resurgence of bed bugs, a global concern due to increased international travel, pesticide resistance, and evolving pest control practices. It focuses on the distinct morphological features of Cimex lectularius and Cimex hemipterus, two species of bed bugs that predominantly feed on humans. These morphological differences facilitate their accurate identification, vital for effective pest management and public health. By developing a user-friendly application, this research contributes to various aspects of bed bug control. It promotes collaboration among researchers, enables the public to identify these pests easily, aids communicable disease control centers, expedites survey studies, and offers practical applications in airports, hotels, and ports for efficient pest species recognition, ultimately enhancing bed bug management efforts. This study emphasizes the morphological differences between C. lectularius and C. hemipterus, which can significantly impact the monitoring and management of bedbug infestations.