Integrating Artificial Intelligence with Insect Phototaxis: Transformative Innovations in Pest Control

Phototaxis or the responsiveness of insects with light stimuli represents an important mechanistic basis upon which pest management methods are approached. Traditional use of phototaxis-based technologies frequently employs merely a light trap for inducing the changing behavioral patterns observed among insects in pest management and the like. A great deal can change with novel approaches such as the application of AI. This paper explores the biological underpinnings of phototaxis, examines both conventional and modern applications of light-based pest control, and introduces the integration of AI to enhance precision and effectiveness. Recent breakthroughs, such as the use of tailored wavelengths of light to target specific insect species, are discussed in detail alongside emerging applications like smart farming systems that employ AI-driven decision-making. Energy efficiency, cost, and environmental impacts are all part of the discussion, making clear that sustainability needs to be found. Furthermore, the research will discuss future research directions in areas such as adaptive light-based traps, real-time monitoring, and AI-based predictive models that may respond dynamically to changing pest behavior and environmental conditions. By fusing insights derived from biological findings with state-of-the-art AI technologies, this paper looks forward to the prospect of presenting revolutionary phototaxis-driven strategies in pest management. The aim is to highlight how these integrated approaches might result in more environmentally friendly, highly efficient, and species-specific pest control methods that align with the principles of sustainable agriculture. Seen through this interdisciplinary lens, this paper contributes to the growing discourse about merging biological knowledge with technological innovation for global agricultural challenges.