Towards Continuous Surveillance of Fruit Flies Using Sensor Networks and Machine Vision

In Australia, the Queensland fruit fly (B. tryoni), is the most destructive insect pest of horticulture, attacking nearly all fruit and vegetable crops. This project has researched and prototyped a system for monitoring fruit flies so that authorities can be alerted when a fly enters a crop in a more efficient manner than is currently used. This paper presents the idea of a sensor platform design as well as the fruit fly detection and recognition algorithm by using machine vision techniques. The experiments showed that the designed trap and sensor platform can capture quality fly images and the invasive flies can be detected with an average precision of 80%.