Development of imaging technology for wireless insect monitoring

Technological advances have paved the way to modern agriculture including efficient pesticide applications, automation of farming practices and use of imaging technology for precision agriculture. In particular, imaging technology has been extensively used for stress detection (e.g., water, nutrient, pests, etc.) and post-harvest processing. However, there has been limited advances in the use of imaging technology in pest-specific detection and monitoring. Moreover, current monitoring practices are less efficient and labor intensive. Thus, the objective of this project is to develop an imaging platform that can be attached to various insect trap designs, identify target insects and remotely record data. This project will require three phases, first is image collection of the target pest to train the artificial intelligence (AI), second is the development of the hardware, and third, is field validation. This will be tested with pecan weevil traps in commercial pecan orchards in Georgia. Although the initial tests will be conducted with one pest, the AI will be designed to easily identify any target insect. Thereby, such technology has potential wide-ranging applications for trap-based insect monitoring for pest management and bio-surveillance of invasive pests.