Design and implementation of the intelligent system for automatically monitoring waterbirds in Quanzhou Bar Wetland

Abstract

The abundance and quantity of waterbird species are often used to evaluate the ecological status of wetlands because most waterbirds are sensitive to the environment. Traditional methods of detecting waterbirds are not only time-consuming but also inaccurate. Some investigations may even be at risk of the natural environment, E.g., bad weather or wild animal attacks. To address this issue, we designed an intelligent waterbird automatic identification system based on Model-View-Viewmodel (MVVM) framework which can support high effectively, safe and long-time monitoring the native wetland waterbirds. To implement the system, we trained a waterbird identification model (WIM) using the YOLOv5 algorithm and deployed it on a back-end for real-time detections, species identifications, and recording counts at different time intervals. It was integrated into a WebGIS-based application, which can be helpful for user to observe the spatial distributions of waterbirds of different species and analyzing their changing laws. We employed a PostgreSQL Database to manage geospatial data and designed the corresponding data access APIs. In addition, a tool for uploading and labeling images online was implemented for pre-training, retraining, and updating the WIM. In our current system, the image Database plays a vital role and it is designed to be auto-update, which means that once our users finished uploading a new image, the pretrained WIM on the back-end will be updated automatically. Although the system is still on its initial testing phase, some results show that it works well. The identifying rate and recall of native waterbird can reach 81.00% and 99.00%, respectively. The ongoing system is able to meet the basic requirements of detecting native wetland waterbird species and record the maximum number of observations of different species within a certain time interval specified by users. And it will provide more information about for managers to better understand the waterbirds and the wetland environment.