Bird Species Classification for Waterbird Census Using Machine Vision Module Arya Harditya(a*), Syafiga Arinda(b), Fatmaliza Zaki Abdad(c)
Faculty of Engineering and Technology, Sampoerna University
L^Avenue Office and Residence, Jl. Pasar Minggu Raya Kav.16
arya.harditya[at]sampoernauniversity.ac.id
Abstract
The research aims to train machine vision in recognizing type of birds in the field and converts it into data that later can be visualized in gaming environment. To achieve the goal, the research initialized and participated in an activity called Asian Waterbird Census (AWC) in January 2022, an annual citizen science activity conducted by Burung Indonesia that also involves common society to monitor water birds population in Rambut Island, Jakarta. The goal of AWC is to introduce society of water birds variety as well as raising awareness in preserving its habitat. Rambut Island is chosen for AWC activity because it is one of 228 prominent locations for birds and biodiversity in Indonesia, it is also the most important functional wetland in the world. This is aligned with the goal the research, to create a data-driven augmented space, which then can raise awareness to common society of biodiversity importance in contemporary situation. This article is creating dataset of Milky Stork (Bangau Bluwok) species and deploy trained model to a Machine Vision camera module.
